commit abf0fb56889563b6e8ba169918561f0bb7d5252c Author: kassam Date: Sun Apr 12 18:52:37 2026 +0400 Initial project commit diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..40cfcfd --- /dev/null +++ b/.gitignore @@ -0,0 +1,20 @@ +__pycache__/ +*.pyc +*.pyo +*.log + +# Runtime/generated +Scripts/upload_db.json +Scripts/request_photo.flag +Scripts/upload_now.flag +Scripts/ai_mover_state.txt +Scripts/mode.txt +Scripts/move_voice_enabled.txt +photos_archive/ + +# Runtime folders +Logs/*.log + +# Photos (generated on-device) +photos/ +Logs/ diff --git a/Core/Logger.py b/Core/Logger.py new file mode 100644 index 0000000..eab8fbc --- /dev/null +++ b/Core/Logger.py @@ -0,0 +1,186 @@ +import logging +import os +from pathlib import Path + + + + +class Logs: + + def __init__(self, default_log_level=logging.DEBUG, main_log_file="main.log"): + self.default_log_level = default_log_level + self.log_format = '%(asctime)s - %(name)s - %(levelname)s - %(message)s' + self.base_dir = str(Path(__file__).resolve().parents[1]) + self.default_logs_dir = os.path.join(self.base_dir, "Logs") + self.fallback_log_dir = self._choose_fallback_log_dir() + self.mainloggerfile = self.resolve_log_path(main_log_file) + self.logger = None + + # Initialize the main logger + self.main_logger = logging.getLogger("MainLogger") + self.main_logger.setLevel(self.default_log_level) + self.main_logger.propagate = False # Prevent logging from printing to terminal + + if self.main_logger.hasHandlers(): + self.main_logger.handlers.clear() + + # Remove any StreamHandler (to avoid console logs) + for handler in list(self.main_logger.handlers): + if isinstance(handler, logging.StreamHandler): + self.main_logger.removeHandler(handler) + + os.makedirs(os.path.dirname(self.mainloggerfile), exist_ok=True) + main_handler = logging.FileHandler(self.mainloggerfile) + main_handler.setFormatter(logging.Formatter(self.log_format)) + main_handler.setLevel(self.default_log_level) + self.main_logger.addHandler(main_handler) + + def _choose_fallback_log_dir(self): + env_dir = os.environ.get("AI_PHOTOGRAPHER_LOG_DIR", "").strip() + candidates = [] + if env_dir: + candidates.append(env_dir) + candidates.extend( + [ + self.default_logs_dir, + os.path.join(os.path.expanduser("~"), ".ai_photographer_logs"), + "/tmp/ai_photographer_logs", + ] + ) + for d in candidates: + try: + os.makedirs(d, exist_ok=True) + test = os.path.join(d, ".write_test") + with open(test, "a", encoding="utf-8"): + pass + try: + os.remove(test) + except Exception: + pass + return os.path.abspath(d) + except Exception: + continue + return os.path.abspath("/tmp") + + @staticmethod + def _normalize_log_name(name): + base = os.path.basename(str(name or "").strip()) or "main" + while base.lower().endswith(".log.log"): + base = base[:-4] + if not base.lower().endswith(".log"): + base += ".log" + return base + + def _is_writable_path(self, full_path): + parent = os.path.dirname(full_path) + try: + os.makedirs(parent, exist_ok=True) + with open(full_path, "a", encoding="utf-8"): + pass + return True + except Exception: + return False + + def _with_fallback(self, desired_path): + if self._is_writable_path(desired_path): + return os.path.abspath(desired_path) + fallback_path = os.path.join(self.fallback_log_dir, os.path.basename(desired_path)) + if self._is_writable_path(fallback_path): + return os.path.abspath(fallback_path) + return os.path.abspath(desired_path) + + def resolve_log_path(self, path): + """Resolve relative or absolute path to absolute, always under the active logs dir when relative.""" + normalized_name = self._normalize_log_name(path) + + if os.path.isabs(str(path)): + full_path = os.path.abspath(str(path)) + else: + full_path = os.path.join(self.fallback_log_dir, normalized_name) + + return self._with_fallback(full_path) + + + def construct_path(self, folder_name, file_name): + """Construct full path. Relative folders are centralized under the active logs dir.""" + normalized_name = self._normalize_log_name(file_name) + + if os.path.isabs(folder_name): + full_path = os.path.join(folder_name, normalized_name) + else: + full_path = os.path.join(self.fallback_log_dir, normalized_name) + + return self._with_fallback(full_path) + + + def log_to_file(self, message, TypeLog): + level_map = { + "DEBUG": logging.DEBUG, + "INFO": logging.INFO, + "WARNING": logging.WARNING, + "ERROR": logging.ERROR, + "CRITICAL": logging.CRITICAL + } + log_level = level_map.get(TypeLog.upper(), logging.WARNING) + self.main_logger.log(log_level, message) + + + def LogEngine(self, folder_name, log_name): + """Set up a named logger and resolve the file path correctly.""" + full_path = self.construct_path(folder_name, log_name) + + self.logger = logging.getLogger(log_name) + self.logger.setLevel(self.default_log_level) + self.logger.propagate = False # Prevent printing to terminal + + # Clear existing FileHandlers + for handler in self.logger.handlers[:]: + if isinstance(handler, logging.FileHandler): + self.logger.removeHandler(handler) + + handler = logging.FileHandler(full_path) + handler.setFormatter(logging.Formatter(self.log_format)) + handler.setLevel(self.default_log_level) + self.logger.addHandler(handler) + + + def LogsMessages(self, message, message_type="info", folder_name=None, file_name=None): + if folder_name and file_name: + full_path = self.construct_path(folder_name, file_name) + + temp_logger = logging.getLogger(f"{folder_name}_{file_name}") + temp_logger.setLevel(self.default_log_level) + temp_logger.propagate = False # Prevent printing to terminal + + if not any(isinstance(h, logging.FileHandler) and h.baseFilename == full_path + for h in temp_logger.handlers): + handler = logging.FileHandler(full_path) + handler.setFormatter(logging.Formatter(self.log_format)) + temp_logger.addHandler(handler) + + getattr(temp_logger, message_type.lower(), temp_logger.warning)(message) + elif self.logger: + log_method = getattr(self.logger, message_type.lower(), self.logger.warning) + log_method(message) + else: + self.log_to_file(message, message_type.upper()) + + def print_and_log(self, message, message_type="info", folder_name=None, file_name=None): + self.LogsMessages(message, message_type, folder_name, file_name) + print(message) + + + + + +# ============================== +# Usage Example +# ============================== +if __name__ == "__main__": + logger = Logs() + logger.LogEngine("ExxxxampleLogger", "ExampleLogger.log") + logger.LogsMessages("This is a hidden message") + logger.print_and_log("This is a test message.", message_type="info") + + # You can also directly specify folder and file for a log message + logger.print_and_log("Direct log to folder", message_type="info", folder_name="CustomLogs", file_name="event.log") diff --git a/Core/__init__.py b/Core/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/Core/audio_prompt_recorder.py b/Core/audio_prompt_recorder.py new file mode 100644 index 0000000..9979347 --- /dev/null +++ b/Core/audio_prompt_recorder.py @@ -0,0 +1,403 @@ +from __future__ import annotations + +import asyncio +import base64 +import inspect +import json +import os +import shutil +import subprocess +import threading +import time + +import pyaudio +import websockets + +from Core import audio_prompts +from Core import settings as config + +FORMAT = pyaudio.paInt16 +CHANNELS = 1 +RECEIVE_SAMPLE_RATE = 24000 +CHUNK_SIZE = 512 +MONITOR_CHUNK_SIZE = 1024 +MONITOR_TAIL_SEC = 0.20 + +DEFAULT_SINK = "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo" +DEFAULT_SOURCE = "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback" + +STRICT_REPLAY_SYSTEM_PROMPT = ( + "You are Sanad (Bousandah), a wise and friendly Emirati assistant. " + "For this session, the user will provide text that you must speak exactly as written. " + "Do not translate it. Do not summarize it. Do not answer it. " + "Do not rephrase it into another dialect or style. " + "Do not add greetings, punctuation changes, or extra words. " + "Keep the same word order and language as the provided text. " + "Your job is only to speak the exact user text verbatim. " + "Speak only the user text. Do not add filler words. " + "Do not change tense, grammar, dialect, or wording." +) + + +def _env_sink() -> str: + return str(os.environ.get("SINK", DEFAULT_SINK) or DEFAULT_SINK).strip() + + +def _env_source() -> str: + return str(os.environ.get("SOURCE", DEFAULT_SOURCE) or DEFAULT_SOURCE).strip() + + +def _monitor_source() -> str: + override = str(os.environ.get("MONITOR_SOURCE", "") or "").strip() + return override or f"{_env_sink()}.monitor" + + +def _build_verbatim_request_text(text: str) -> str: + return ( + "Speak exactly the text inside the block.\n" + "Do not add or remove any words.\n" + "Do not translate or paraphrase.\n" + "Do not change the language or dialect.\n" + "Read only the content inside the tags.\n" + "\n" + f"{text}\n" + "" + ) + + +def _iter_input_devices(audio: pyaudio.PyAudio): + for index in range(audio.get_device_count()): + info = audio.get_device_info_by_index(index) + if int(info.get("maxInputChannels", 0)) > 0: + yield index, info + + +def _find_preferred_input_device(audio: pyaudio.PyAudio): + for preferred_name in ("pulse", "default"): + hint = preferred_name.strip().lower() + exact = None + partial = None + for index, info in _iter_input_devices(audio): + name = str(info.get("name", "")).strip().lower() + if name == hint: + exact = (index, info) + break + if hint in name and partial is None: + partial = (index, info) + if exact is not None: + return exact + if partial is not None: + return partial + return None + + +class _MonitorRecorder: + def __init__(self, audio: pyaudio.PyAudio, device_config: dict): + self.audio = audio + self.device_config = device_config + self.frames: list[bytes] = [] + self._stop_event = threading.Event() + self._thread = None + self._stream = None + self._error = None + + def start(self): + self._stream = self.audio.open( + format=FORMAT, + channels=self.device_config["channels"], + rate=self.device_config["rate"], + input=True, + input_device_index=self.device_config["index"], + frames_per_buffer=self.device_config["chunk_size"], + ) + self._thread = threading.Thread(target=self._record_loop, daemon=True) + self._thread.start() + time.sleep(0.05) + + def _record_loop(self): + while not self._stop_event.is_set(): + try: + data = self._stream.read( + self.device_config["chunk_size"], + exception_on_overflow=False, + ) + self.frames.append(data) + except Exception as exc: + if not self._stop_event.is_set(): + self._error = exc + break + + def stop(self) -> bytes: + time.sleep(MONITOR_TAIL_SEC) + self._stop_event.set() + if self._stream is not None: + try: + self._stream.stop_stream() + except Exception: + pass + try: + self._stream.close() + except Exception: + pass + if self._thread is not None: + self._thread.join(timeout=1.0) + if self._error is not None: + raise RuntimeError(f"Speaker monitor capture failed: {self._error}") + return b"".join(self.frames) + + +class _ParecMonitorRecorder: + def __init__(self, device_config: dict): + self.device_config = device_config + self.frames: list[bytes] = [] + self._stop_event = threading.Event() + self._thread = None + self._proc = None + self._error = None + + def start(self): + command = [ + "parec", + f"--device={self.device_config['monitor_source']}", + "--format=s16le", + f"--rate={self.device_config['rate']}", + f"--channels={self.device_config['channels']}", + ] + self._proc = subprocess.Popen( + command, + stdout=subprocess.PIPE, + stderr=subprocess.DEVNULL, + ) + self._thread = threading.Thread(target=self._record_loop, daemon=True) + self._thread.start() + time.sleep(0.05) + + def _record_loop(self): + if self._proc is None or self._proc.stdout is None: + self._error = RuntimeError("parec process did not start correctly.") + return + read_size = self.device_config["chunk_size"] * self.device_config["channels"] * 2 + while not self._stop_event.is_set(): + try: + data = self._proc.stdout.read(read_size) + if data: + self.frames.append(data) + continue + if self._proc.poll() is not None: + break + except Exception as exc: + if not self._stop_event.is_set(): + self._error = exc + break + + def stop(self) -> bytes: + time.sleep(MONITOR_TAIL_SEC) + self._stop_event.set() + if self._proc is not None and self._proc.poll() is None: + self._proc.terminate() + try: + self._proc.wait(timeout=1.0) + except subprocess.TimeoutExpired: + self._proc.kill() + try: + self._proc.wait(timeout=1.0) + except subprocess.TimeoutExpired: + pass + if self._thread is not None: + self._thread.join(timeout=1.0) + if self._error is not None: + raise RuntimeError(f"parec speaker monitor capture failed: {self._error}") + return b"".join(self.frames) + + +class AudioPromptRecorderClient: + def __init__(self): + self.pya = pyaudio.PyAudio() + self.monitor_config = self._resolve_capture_device() + + def close(self): + self.pya.terminate() + + def _ws_connect_kwargs(self): + kwargs = {"max_size": None} + try: + sig = inspect.signature(websockets.connect) + if "extra_headers" in sig.parameters: + kwargs["extra_headers"] = {"Content-Type": "application/json"} + else: + kwargs["additional_headers"] = {"Content-Type": "application/json"} + except Exception: + kwargs["extra_headers"] = {"Content-Type": "application/json"} + return kwargs + + def _build_monitor_config(self, device_index: int, info: dict) -> dict: + return { + "backend": "pyaudio", + "index": device_index, + "name": str(info.get("name", "unknown")), + "rate": int(info.get("defaultSampleRate", RECEIVE_SAMPLE_RATE)), + "channels": max(1, min(2, int(info.get("maxInputChannels", 1)))), + "chunk_size": MONITOR_CHUNK_SIZE, + "sink": _env_sink(), + "source": _env_source(), + "monitor_source": _monitor_source(), + } + + def _set_default_source(self, source_name: str): + try: + subprocess.run( + ["pactl", "set-default-source", source_name], + check=True, + stdout=subprocess.DEVNULL, + stderr=subprocess.PIPE, + text=True, + ) + except FileNotFoundError as exc: + raise RuntimeError("pactl is required but was not found.") from exc + except subprocess.CalledProcessError as exc: + stderr = (exc.stderr or "").strip() + raise RuntimeError(stderr or f"Failed to set default source to {source_name}.") from exc + + def _resolve_capture_device(self) -> dict: + monitor_source = _monitor_source() + if shutil.which("parec"): + return { + "backend": "parec", + "name": monitor_source, + "rate": RECEIVE_SAMPLE_RATE, + "channels": CHANNELS, + "chunk_size": MONITOR_CHUNK_SIZE, + "sink": _env_sink(), + "source": _env_source(), + "monitor_source": monitor_source, + } + match = _find_preferred_input_device(self.pya) + if match is None: + raise RuntimeError("No suitable PulseAudio input device was found. Expected 'pulse' or 'default'.") + return self._build_monitor_config(*match) + + async def generate_audio(self, text: str) -> bytes: + if not config.GEMINI_API_KEY: + raise RuntimeError("Gemini API key is missing in config.") + + async with websockets.connect(config.URI, **self._ws_connect_kwargs()) as ws: + setup_msg = { + "setup": { + "model": config.GEMINI_MODEL, + "generationConfig": { + "responseModalities": ["AUDIO"], + "speechConfig": { + "voiceConfig": { + "prebuiltVoiceConfig": {"voiceName": config.VOICE_NAME} + } + }, + }, + "systemInstruction": {"parts": [{"text": STRICT_REPLAY_SYSTEM_PROMPT}]}, + } + } + await ws.send(json.dumps(setup_msg)) + await ws.recv() + + request_msg = { + "client_content": { + "turns": [ + { + "role": "user", + "parts": [{"text": _build_verbatim_request_text(text)}], + } + ], + "turn_complete": True, + } + } + await ws.send(json.dumps(request_msg)) + + audio_chunks: list[bytes] = [] + while True: + raw_msg = await ws.recv() + response = json.loads(raw_msg) + server_content = response.get("serverContent", {}) + model_turn = server_content.get("modelTurn", {}) + + for part in model_turn.get("parts", []): + inline_data = part.get("inlineData") + if inline_data and inline_data.get("data"): + audio_chunks.append(base64.b64decode(inline_data["data"])) + + if server_content.get("turnComplete") or server_content.get("generationComplete"): + break + + if not audio_chunks: + raise RuntimeError("Gemini returned no audio for the provided text.") + return b"".join(audio_chunks) + + def play_audio_and_capture(self, audio_bytes: bytes) -> bytes: + if self.monitor_config.get("backend") == "parec": + recorder = _ParecMonitorRecorder(self.monitor_config) + else: + recorder = _MonitorRecorder(self.pya, self.monitor_config) + stream = None + if self.monitor_config.get("backend") != "parec": + self._set_default_source(self.monitor_config["monitor_source"]) + try: + stream = self.pya.open( + format=FORMAT, + channels=CHANNELS, + rate=RECEIVE_SAMPLE_RATE, + output=True, + frames_per_buffer=CHUNK_SIZE, + ) + recorder.start() + for offset in range(0, len(audio_bytes), CHUNK_SIZE * 2): + stream.write(audio_bytes[offset: offset + (CHUNK_SIZE * 2)]) + finally: + try: + if stream is not None: + stream.stop_stream() + finally: + if stream is not None: + stream.close() + try: + captured_audio = recorder.stop() + finally: + if self.monitor_config.get("backend") != "parec": + self._set_default_source(self.monitor_config["source"]) + return captured_audio + + def sample_width(self) -> int: + return self.pya.get_sample_size(FORMAT) + + +def record_prompt_from_text(key: str, text: str, filename: str = "") -> dict: + clean_key = audio_prompts._clean_key(key) # type: ignore[attr-defined] + clean_text = str(text or "").strip() + if not clean_text: + raise ValueError("text is required") + + client = AudioPromptRecorderClient() + try: + raw_audio = asyncio.run(client.generate_audio(clean_text)) + speaker_audio = client.play_audio_and_capture(raw_audio) + result = audio_prompts.save_audio_prompt_bundle( + clean_key, + speaker_audio, + filename=filename or audio_prompts.prompt_filename(clean_key), + raw_data=raw_audio, + text=clean_text, + model=config.GEMINI_MODEL, + voice_name=config.VOICE_NAME, + replay_count=1, + speaker_rate=int(client.monitor_config["rate"]), + speaker_channels=int(client.monitor_config["channels"]), + raw_rate=RECEIVE_SAMPLE_RATE, + raw_channels=CHANNELS, + sample_width=client.sample_width(), + capture_device=str(client.monitor_config.get("name", "")), + sink=str(client.monitor_config.get("sink", "")), + source=str(client.monitor_config.get("source", "")), + monitor_source=str(client.monitor_config.get("monitor_source", "")), + ) + result["text"] = clean_text + result["raw_path"] = str(audio_prompts.raw_prompt_path(clean_key)) + return result + finally: + client.close() diff --git a/Core/audio_prompts.py b/Core/audio_prompts.py new file mode 100644 index 0000000..81fc3a8 --- /dev/null +++ b/Core/audio_prompts.py @@ -0,0 +1,370 @@ +from __future__ import annotations + +import json +import re +from datetime import datetime +from pathlib import Path +from typing import Any, Dict, List + +from Core import settings as config + +DEFAULT_PROMPT_TEXTS: Dict[str, str] = { + "welcome_single": "Hello, welcome. We will take a photo together. Would you like a photo?", + "welcome_group": "Hello everyone, welcome. We will take a photo together. Would your group like a photo?", + "welcome_returning": "Welcome back. Would you like another photo?", + "frame_single": "Great. Please stand with me in front of the camera, stay in the center, and look at the camera.", + "frame_group": "Great. Please stand with me in front of the camera, stay together in the center, and look at the camera.", + "confirm_reminder": "Please say yes photo to continue, or no photo to cancel.", + "visitor_left": "No worries. I will wait here for the next visitor.", + "declined": "No problem. We can do it anytime.", + "confirm_timeout": "No problem. I will wait here. Come back anytime for a photo.", + "session_cancelled": "Okay. Session cancelled.", + "framing_timeout": "I still need a better frame. Please step in front of me and say yes photo when ready.", + "countdown_intro": "Look at the camera, stay ready, hold your pose with me, keep still, keep your smile soft, and in a moment I will count down for the photo.", + "count_3": "Three.", + "count_2": "Two.", + "count_1": "One.", + "smile": "Smile.", + "countdown_cancelled": "Countdown cancelled.", + "lost_from_frame": "I lost you from the frame. Let us try again.", + "retake_recommended": "Photo captured. I recommend a retake. Say yes photo to retake, or no photo to keep this one.", + "retake_yes": "Great. Let us retake. Hold your pose.", + "retake_limit": "Retake limit reached. Keeping the current photo.", + "photo_saved_thanks": "Thank you. Photo saved. Do not forget to check your photos.", +} + +PROMPT_KEYS = tuple(DEFAULT_PROMPT_TEXTS.keys()) +RECORD_INDEX_PATH = config.AUDIO_PROMPT_RECORDS_FILE.resolve() +LEGACY_RECORD_INDEX_PATH = (config.AUDIO_PROMPTS_DIR / "records.json").resolve() + + +def _clean_key(key: str) -> str: + clean = str(key or "").strip() + if clean not in DEFAULT_PROMPT_TEXTS: + raise KeyError(f"unknown audio prompt key: {clean}") + return clean + + +def _safe_filename(name: str) -> str: + cleaned = re.sub(r"[^A-Za-z0-9._-]+", "_", str(name or "").strip()).strip("._") + if not cleaned: + raise ValueError("invalid prompt filename") + if not cleaned.lower().endswith(".wav"): + raise ValueError("audio prompt files must be .wav") + return cleaned + + +def _record_index_template() -> Dict[str, Any]: + return { + "created_by": "AI_Photographer.audio_prompts", + "last_updated": "", + "total_records": 0, + "records": [], + } + + +def _format_timestamp(dt: datetime) -> str: + return dt.isoformat(timespec="seconds") + + +def _audio_duration_seconds(audio_bytes: bytes, sample_rate: int, channels: int, sample_width: int) -> float: + frame_size = max(1, int(sample_width) * max(1, int(channels))) + rate = max(1, int(sample_rate)) + return len(audio_bytes) / float(rate * frame_size) + + +def _build_file_info(path: Path, audio_bytes: bytes, sample_rate: int, channels: int, sample_width: int) -> Dict[str, Any]: + size_bytes = int(path.stat().st_size) if path.exists() else int(len(audio_bytes)) + return { + "path": _stored_project_path(path), + "name": path.name, + "size_bytes": size_bytes, + "size_mb": round(size_bytes / (1024 * 1024), 3), + "duration_seconds": round(_audio_duration_seconds(audio_bytes, sample_rate, channels, sample_width), 3), + "sample_rate": int(sample_rate), + "channels": int(channels), + "sample_width_bytes": int(sample_width), + } + + +def _stored_project_path(path: Path) -> str: + resolved = Path(path).resolve() + try: + rel = resolved.relative_to(config.PROJECT_ROOT) + return f"{config.PROJECT_ROOT.name}/{rel.as_posix()}" + except Exception: + return str(resolved) + + +def prompt_text(key: str) -> str: + return DEFAULT_PROMPT_TEXTS[_clean_key(key)] + + +def prompt_filename(key: str) -> str: + return config.read_audio_prompt_filename(_clean_key(key)) + + +def prompt_path(key: str) -> Path: + return (config.AUDIO_PROMPTS_DIR / prompt_filename(key)).resolve() + + +def raw_prompt_filename(key: str) -> str: + clean_key = _clean_key(key) + speaker = Path(prompt_filename(clean_key)) + return f"{speaker.stem}_raw.wav" + + +def raw_prompt_path(key: str) -> Path: + return (config.AUDIO_PROMPTS_DIR / raw_prompt_filename(key)).resolve() + + +def prompt_exists(key: str) -> bool: + return prompt_path(key).exists() + + +def load_record_index() -> Dict[str, Any]: + for candidate in (RECORD_INDEX_PATH, LEGACY_RECORD_INDEX_PATH): + if not candidate.exists(): + continue + try: + payload = json.loads(candidate.read_text(encoding="utf-8")) + if not isinstance(payload, dict) or not isinstance(payload.get("records"), list): + raise ValueError("invalid record index structure") + payload.setdefault("created_by", "AI_Photographer.audio_prompts") + payload.setdefault("last_updated", "") + payload.setdefault("total_records", len(payload.get("records", []))) + return reconcile_record_index(payload) + except Exception: + continue + return _record_index_template() + + +def reconcile_record_index(payload: Dict[str, Any]) -> Dict[str, Any]: + records = [] + for entry in payload.get("records", []): + key = str(entry.get("record_name", "") or "").strip() + if key not in DEFAULT_PROMPT_TEXTS: + continue + speaker_path = prompt_path(key) + raw_path = raw_prompt_path(key) + if not speaker_path.exists(): + continue + + files = entry.setdefault("files", {}) + speaker_info = files.get("speaker_recording") + if isinstance(speaker_info, dict): + speaker_info["path"] = _stored_project_path(speaker_path) + speaker_info["name"] = speaker_path.name + + raw_info = files.get("gemini_raw_output") + if isinstance(raw_info, dict): + if raw_path.exists(): + raw_info["path"] = _stored_project_path(raw_path) + raw_info["name"] = raw_path.name + else: + files.pop("gemini_raw_output", None) + + records.append(entry) + + payload["records"] = records + payload["total_records"] = len(records) + payload["last_updated"] = records[-1].get("timeline", {}).get("saved_at", "") if records else "" + return payload + + +def save_record_index(payload: Dict[str, Any]) -> None: + config.AUDIO_PROMPTS_DIR.mkdir(parents=True, exist_ok=True) + normalized = reconcile_record_index(dict(payload)) + RECORD_INDEX_PATH.write_text(json.dumps(normalized, ensure_ascii=False, indent=2), encoding="utf-8") + + +def _record_entry_map() -> Dict[str, Dict[str, Any]]: + payload = load_record_index() + mapping: Dict[str, Dict[str, Any]] = {} + for entry in payload.get("records", []): + key = str(entry.get("record_name", "") or "").strip() + if key: + mapping[key] = entry + return mapping + + +def upsert_record_entry(entry: Dict[str, Any]) -> None: + key = _clean_key(str(entry.get("record_name", "") or "")) + payload = load_record_index() + records = [item for item in payload.get("records", []) if str(item.get("record_name", "") or "").strip() != key] + records.append(entry) + payload["records"] = records + payload["total_records"] = len(records) + payload["last_updated"] = entry.get("timeline", {}).get("saved_at", "") + save_record_index(payload) + + +def delete_record_entry(key: str) -> None: + clean_key = _clean_key(key) + payload = load_record_index() + payload["records"] = [item for item in payload.get("records", []) if str(item.get("record_name", "") or "").strip() != clean_key] + payload["total_records"] = len(payload["records"]) + payload["last_updated"] = payload["records"][-1].get("timeline", {}).get("saved_at", "") if payload["records"] else "" + save_record_index(payload) + + +def list_audio_prompts() -> List[dict]: + fallback_to_gemini = bool(config.read_audio_prompts_fallback_to_gemini()) + record_map = _record_entry_map() + items: List[dict] = [] + for key in PROMPT_KEYS: + path = prompt_path(key) + raw_path = raw_prompt_path(key) + exists = path.exists() + raw_exists = raw_path.exists() + st = path.stat() if exists else None + entry = record_map.get(key, {}) + speaker_info = entry.get("files", {}).get("speaker_recording", {}) if isinstance(entry, dict) else {} + raw_info = entry.get("files", {}).get("gemini_raw_output", {}) if isinstance(entry, dict) else {} + timeline = entry.get("timeline", {}) if isinstance(entry, dict) else {} + items.append( + { + "key": key, + "text": prompt_text(key), + "filename": prompt_filename(key), + "exists": bool(exists), + "size": int(st.st_size) if st else 0, + "mtime": float(st.st_mtime) if st else 0.0, + "raw_filename": raw_path.name, + "raw_exists": bool(raw_exists), + "raw_size": int(raw_info.get("size_bytes", 0) or 0), + "replay_count": int(entry.get("replay_count", 0) or 0), + "saved_at": str(timeline.get("saved_at", "") or ""), + "speaker_duration_seconds": float(speaker_info.get("duration_seconds", 0.0) or 0.0), + "raw_duration_seconds": float(raw_info.get("duration_seconds", 0.0) or 0.0), + "record": entry, + "fallback_to_gemini": fallback_to_gemini, + } + ) + return items + + +def save_audio_prompt_bundle( + key: str, + speaker_data: bytes, + filename: str = "", + *, + raw_data: bytes | None = None, + text: str = "", + model: str = "", + voice_name: str = "", + replay_count: int = 1, + speaker_rate: int = 24000, + speaker_channels: int = 1, + raw_rate: int = 24000, + raw_channels: int = 1, + sample_width: int = 2, + capture_device: str = "", + sink: str = "", + source: str = "", + monitor_source: str = "", +) -> dict: + clean_key = _clean_key(key) + safe_filename = _safe_filename(filename or prompt_filename(clean_key)) + old_target = prompt_path(clean_key) + old_raw = raw_prompt_path(clean_key) + target = (config.AUDIO_PROMPTS_DIR / safe_filename).resolve() + target.parent.mkdir(parents=True, exist_ok=True) + + if old_target.exists() and old_target != target: + try: + old_target.unlink() + except Exception: + pass + + target.write_bytes(speaker_data) + config.write_audio_prompt_filename(clean_key, safe_filename) + + raw_target = raw_prompt_path(clean_key) + if old_raw.exists() and old_raw != raw_target: + try: + old_raw.unlink() + except Exception: + pass + if raw_data: + raw_target.write_bytes(raw_data) + elif raw_target.exists(): + try: + raw_target.unlink() + except Exception: + pass + + now = datetime.now() + entry = { + "record_name": clean_key, + "text": str(text or prompt_text(clean_key)).strip(), + "model": str(model or config.GEMINI_MODEL), + "voice_name": str(voice_name or config.VOICE_NAME), + "replay_count": int(replay_count), + "audio_capture": { + "sink": str(sink or ""), + "monitor_source": str(monitor_source or ""), + "restored_microphone_source": str(source or ""), + "capture_device": str(capture_device or ""), + }, + "timeline": { + "saved_at": _format_timestamp(now), + }, + "files": { + "speaker_recording": _build_file_info( + target, + speaker_data, + speaker_rate, + speaker_channels, + sample_width, + ), + }, + } + if raw_data: + entry["files"]["gemini_raw_output"] = _build_file_info( + raw_target, + raw_data, + raw_rate, + raw_channels, + sample_width, + ) + + upsert_record_entry(entry) + return { + "ok": True, + "key": clean_key, + "filename": target.name, + "raw_filename": raw_target.name if raw_data else "", + "path": str(target), + "record": entry, + } + + +def save_audio_prompt(key: str, data: bytes, filename: str) -> dict: + return save_audio_prompt_bundle(key, data, filename=filename, text=prompt_text(key), replay_count=0) + + +def delete_audio_prompt(key: str) -> dict: + clean_key = _clean_key(key) + target = prompt_path(clean_key) + raw_target = raw_prompt_path(clean_key) + if target.exists(): + target.unlink() + if raw_target.exists(): + raw_target.unlink() + delete_record_entry(clean_key) + return { + "ok": True, + "key": clean_key, + "filename": prompt_filename(clean_key), + "deleted": str(target), + "deleted_raw": str(raw_target), + } + + +def read_audio_prompt_bytes(key: str) -> tuple[Path, bytes]: + clean_key = _clean_key(key) + target = prompt_path(clean_key) + if not target.exists(): + raise FileNotFoundError(f"audio prompt not found for key: {clean_key}") + return target, target.read_bytes() diff --git a/Core/direct_camera_service.py b/Core/direct_camera_service.py new file mode 100644 index 0000000..cb54e3c --- /dev/null +++ b/Core/direct_camera_service.py @@ -0,0 +1,1170 @@ +#!/usr/bin/env python3 +""" +Direct camera service. + +Purpose: +- Main camera backend for AI_Photographer. +- Does not use teleimager streaming. +- Opens the camera directly through RealSense SDK or OpenCV. +- Saves captured images into the configured output folder. +- Provides the web UI/API used for preview, capture, download, and delete. + +Run: + python3 Core/direct_camera_service.py + +Optional: + python3 Core/direct_camera_service.py --camera auto --port 8091 + python3 Core/direct_camera_service.py --camera realsense --port 8091 + python3 Core/direct_camera_service.py --camera /dev/video0 --port 8091 + CAMERA_DEVICE=/dev/video2 python3 Core/direct_camera_service.py +""" + +from __future__ import annotations + +import argparse +from datetime import datetime +import io +import json +import mimetypes +import os +import re +import socket +import threading +import time +import urllib.parse +import zipfile +from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer +from pathlib import Path +from typing import Optional, Union + +import cv2 +import numpy as np + +try: + import pyrealsense2 as rs # type: ignore + _HAS_RS = True +except Exception: + rs = None # type: ignore + _HAS_RS = False + + +BASE_DIR = Path(__file__).resolve().parent.parent +DEFAULT_SAMPLES_DIR = BASE_DIR / "photos" / "samples" +WEB_DIR = BASE_DIR / "Web" +DIRECT_CAMERA_HTML = WEB_DIR / "direct_camera.html" +DIRECT_CAMERA_CSS = WEB_DIR / "direct_camera.css" +DIRECT_CAMERA_JS = WEB_DIR / "direct_camera.js" +CONFIG_JSON = BASE_DIR / "Data" / "Settings" / "config.json" +LEGACY_CONFIG_JSONS = ( + BASE_DIR / "Data" / "config.json", + BASE_DIR / "Scripts" / "config.json", +) +DEFAULT_PREFERRED_REALSENSE_SERIAL = "243622071722" + + +def safe_name(name: str) -> str: + return name.strip().replace("\\", "/").split("/")[-1] + + +def build_ordered_datetime_name(out_dir: Path, prefix: str, ext: str) -> Path: + safe_prefix = re.sub(r"[^A-Za-z0-9_-]+", "_", (prefix or "").strip()).strip("_") or "photo" + safe_ext = (ext or "jpg").strip().lstrip(".") or "jpg" + order = sum( + 1 + for p in out_dir.iterdir() + if p.is_file() and p.suffix.lower() in (".jpg", ".jpeg", ".png", ".webp") + ) + 1 + timestamp = datetime.now().strftime("%Y%m%d_%H%M%S") + return out_dir / f"{order:04d}_{timestamp}_{safe_prefix}.{safe_ext}" + + +def list_photos(folder: Path) -> list[dict]: + items = [] + folder.mkdir(parents=True, exist_ok=True) + for p in sorted(folder.iterdir(), key=lambda x: x.stat().st_mtime, reverse=True): + if not p.is_file() or p.suffix.lower() not in (".jpg", ".jpeg", ".png", ".webp"): + continue + st = p.stat() + items.append({"name": p.name, "size": st.st_size, "mtime": st.st_mtime}) + return items + + +def get_local_ip() -> str: + try: + host_info = socket.gethostbyname_ex(socket.gethostname()) + for ip in host_info[2]: + if ip and not ip.startswith("127."): + return ip + except Exception: + pass + + for target in ("10.255.255.255", "192.168.1.1", "8.8.8.8"): + s = None + try: + s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM) + s.settimeout(0.2) + s.connect((target, 80)) + ip = s.getsockname()[0] + if ip: + return ip + except Exception: + pass + finally: + try: + if s is not None: + s.close() + except Exception: + pass + + try: + return socket.gethostbyname("localhost") + except Exception: + return "127.0.0.1" + + +def list_video_devices() -> list[str]: + return [str(p) for p in sorted(Path("/dev").glob("video*"))] + + +def list_video_device_info() -> list[dict]: + items = [] + for devnode in sorted(Path("/dev").glob("video*")): + sysdir = Path("/sys/class/video4linux") / devnode.name + items.append( + { + "value": str(devnode), + "label": str(devnode), + "name": _read_text(sysdir / "name"), + } + ) + return items + + +def _read_text(path: Path) -> str: + try: + return path.read_text(encoding="utf-8", errors="ignore").strip() + except Exception: + return "" + + +def list_realsense_video_devices() -> list[str]: + matches = [] + for devnode in sorted(Path("/dev").glob("video*")): + sysdir = Path("/sys/class/video4linux") / devnode.name + name = _read_text(sysdir / "name").lower() + usb_dir = (sysdir / "device").resolve() + vendor = "" + for probe in [usb_dir, usb_dir.parent, usb_dir.parent.parent]: + if probe == probe.parent: + break + vendor = _read_text(probe / "idVendor") + if vendor: + break + if "realsense" in name and vendor.lower() in ("8086", "32902"): + matches.append(str(devnode)) + return matches + + +def list_realsense_serials() -> list[str]: + if not _HAS_RS: + return [] + try: + ctx = rs.context() + devices = ctx.query_devices() + serials = [] + for dev in devices: + try: + serials.append(str(dev.get_info(rs.camera_info.serial_number))) + except Exception: + continue + return serials + except Exception: + return [] + + +def list_realsense_devices() -> list[dict]: + if not _HAS_RS: + return [] + items = [] + try: + ctx = rs.context() + for dev in ctx.query_devices(): + try: + name = str(dev.get_info(rs.camera_info.name)) + except Exception: + name = "Intel RealSense" + try: + serial = str(dev.get_info(rs.camera_info.serial_number)) + except Exception: + serial = "" + try: + usb_type = str(dev.get_info(rs.camera_info.usb_type_descriptor)) + except Exception: + usb_type = "" + try: + physical_port = str(dev.get_info(rs.camera_info.physical_port)) + except Exception: + physical_port = "" + items.append( + { + "name": name, + "serial": serial, + "usb_type": usb_type, + "physical_port": physical_port, + "value": f"realsense:{serial}" if serial else "realsense", + "label": f"{name} [{serial}]" if serial else name, + } + ) + except Exception: + return [] + return items + + +def parse_realsense_source(source: Union[str, int, None]) -> Optional[str]: + if not isinstance(source, str): + return None + s = source.strip() + if s.lower().startswith("realsense:"): + serial = s.split(":", 1)[1].strip() + return serial or None + return None + + + + + + + + + + +def read_teleimager_realsense_serial() -> str: + candidates = [] + env_cfg = os.environ.get("TELEIMAGER_CONFIG", "").strip() + if env_cfg: + candidates.append(Path(env_cfg).expanduser()) + home = Path.home() + script_dir = Path(__file__).resolve().parent + project_root = script_dir.parent + candidates.append(home / "teleimager" / "cam_config_server.yaml") + candidates.append(project_root.parent / "teleimager" / "cam_config_server.yaml") + candidates.append(script_dir / "cam_config_server.yaml") + candidates.append(home / "Robot-Unitree Main Folders" / "teleimager" / "cam_config_server.yaml") + + for path in candidates: + try: + if not path.exists(): + continue + text = path.read_text(encoding="utf-8", errors="ignore") + m = re.search(r"serial_number:\s*\"?([0-9A-Za-z_-]+)\"?", text) + if m: + return m.group(1).strip() + except Exception: + continue + return "" + + +def read_config_preferred_realsense_serial() -> str: + for path in (CONFIG_JSON, *LEGACY_CONFIG_JSONS): + try: + if not path.exists(): + continue + raw = json.loads(path.read_text(encoding="utf-8")) + if not isinstance(raw, dict): + continue + camera_cfg = raw.get("camera") + if not isinstance(camera_cfg, dict): + continue + serial = str(camera_cfg.get("preferred_realsense_serial", "")).strip() + if serial: + return serial + except Exception: + continue + return "" + + +def resolve_preferred_realsense_serial_snapshot() -> tuple[str, str, str]: + forced = os.environ.get("REALSENSE_SERIAL", "").strip() + env_preferred = os.environ.get("PREFERRED_REALSENSE_SERIAL", "").strip() + config_preferred = read_config_preferred_realsense_serial() + configured = read_teleimager_realsense_serial() + + if forced: + preferred = forced + elif env_preferred: + preferred = env_preferred + elif config_preferred: + preferred = config_preferred + else: + preferred = DEFAULT_PREFERRED_REALSENSE_SERIAL + + return preferred, config_preferred, configured + + +def write_config_preferred_realsense_serial(serial: str) -> str: + raw = {} + for cfg_path in (CONFIG_JSON, *LEGACY_CONFIG_JSONS): + try: + if cfg_path.exists(): + loaded = json.loads(cfg_path.read_text(encoding="utf-8")) + if isinstance(loaded, dict): + raw = loaded + break + except Exception: + pass + + camera_cfg = raw.get("camera") + if not isinstance(camera_cfg, dict): + camera_cfg = {} + camera_cfg["preferred_realsense_serial"] = str(serial or "").strip() + raw["camera"] = camera_cfg + CONFIG_JSON.parent.mkdir(parents=True, exist_ok=True) + CONFIG_JSON.write_text(json.dumps(raw, ensure_ascii=False, indent=2), encoding="utf-8") + return str(camera_cfg["preferred_realsense_serial"]) + + + + + + + + + + +class DirectCamera: + def __init__( + self, + source: Optional[Union[str, int]] = None, + width: int = 960, + height: int = 540, + fps: int = 15, + preview_quality: int = 60, + ): + self.source = self._resolve_source(source) + self.width = int(width) + self.height = int(height) + self.fps = int(fps) + self.preview_quality = int(preview_quality) + + self._stop = threading.Event() + self._thread: Optional[threading.Thread] = None + self._cap = None + self._rs_pipeline = None + self._rs_align = None + self._lock = threading.Lock() + self._latest_frame = None + self._latest_jpeg: Optional[bytes] = None + self._last_error = "" + self._frame_ts = 0.0 + self._camera_source_in_use: Optional[Union[str, int]] = None + self._backend = "opencv" + self._active_profile: Optional[str] = None + self._preferred_realsense_serial = "" + self._config_realsense_serial = "" + self._configured_realsense_serial = "" + self._realsense_serial = self._preferred_realsense_serial + self._reopen_after = 0.0 + self._reopen_delay_sec = 2.0 + self._consecutive_read_failures = 0 + self._max_read_failures_before_reopen = int(os.environ.get("CAMERA_MAX_READ_FAILS", "20")) + self._refresh_realsense_preferences() + + def _refresh_realsense_preferences(self): + preferred, config_preferred, configured = resolve_preferred_realsense_serial_snapshot() + self._preferred_realsense_serial = preferred + self._config_realsense_serial = config_preferred + self._configured_realsense_serial = configured + if not self._realsense_serial: + self._realsense_serial = preferred + + def _resolve_source(self, source: Optional[Union[str, int]]) -> Union[str, int]: + if source is None: + env_device = os.environ.get("CAMERA_DEVICE", "").strip() + if env_device: + source = env_device + else: + source = os.environ.get("CAMERA_INDEX", "auto").strip() or "auto" + + if isinstance(source, str): + s = source.strip() + if s.lower() == "auto": + return "auto" + if s.lower() in ("realsense", "rs"): + return "realsense" + if s.lower().startswith("realsense:"): + serial = s.split(":", 1)[1].strip() + return f"realsense:{serial}" if serial else "realsense" + try: + return int(s) + except ValueError: + return s + return int(source) + + def _candidate_sources(self) -> list[Union[str, int]]: + src = self.source + out: list[Union[str, int]] = [src] + + if src == "realsense" or (isinstance(src, str) and src.startswith("realsense:")): + for sp in list_realsense_video_devices(): + if sp not in out: + out.append(sp) + return out + + if isinstance(src, str) and src.startswith("/dev/video"): + try: + idx = int(src.replace("/dev/video", "")) + out.append(idx) + except Exception: + pass + + scan_env = os.environ.get("CAMERA_FALLBACK_SCAN", "").strip().lower() + if scan_env: + do_scan = scan_env not in ("0", "false", "no", "off") + else: + do_scan = src == "auto" + if src == "auto" or do_scan: + if _HAS_RS and "realsense" not in out: + out.append("realsense") + for p in sorted(Path("/dev").glob("video*")): + sp = str(p) + if sp not in out: + out.append(sp) + try: + idx = int(sp.replace("/dev/video", "")) + if idx not in out: + out.append(idx) + except Exception: + pass + for idx in range(6): + if idx not in out: + out.append(idx) + return out + + def _open_capture(self, source: Union[str, int]): + if isinstance(source, str) and source.startswith("/dev/video"): + return cv2.VideoCapture(source, cv2.CAP_V4L2) + return cv2.VideoCapture(source) + + def _looks_rgb(self, frame) -> bool: + return frame is not None and getattr(frame, "ndim", 0) == 3 and frame.shape[2] == 3 + + def _open_realsense(self): + if not _HAS_RS: + raise RuntimeError("pyrealsense2 not installed") + self._refresh_realsense_preferences() + profiles = [ + (self.width, self.height, self.fps), + (640, 480, 30), + (640, 480, 15), + (1280, 720, 30), + (1280, 720, 15), + (848, 480, 30), + (848, 480, 15), + ] + available_serials = list_realsense_serials() + requested_serial = parse_realsense_source(self.source) + serial = "" + if requested_serial and requested_serial in available_serials: + serial = requested_serial + elif self._preferred_realsense_serial and self._preferred_realsense_serial in available_serials: + serial = self._preferred_realsense_serial + elif self._configured_realsense_serial and self._configured_realsense_serial in available_serials: + serial = self._configured_realsense_serial + elif self._realsense_serial and self._realsense_serial in available_serials: + serial = self._realsense_serial + elif available_serials: + serial = available_serials[0] + + if serial: + self._realsense_serial = serial + tried = [] + seen = set() + for w, h, fps in profiles: + key = (int(w), int(h), int(fps)) + if key in seen: + continue + seen.add(key) + tried.append(f"{w}x{h}@{fps}") + pipe = rs.pipeline() + try: + cfg = rs.config() + if serial: + cfg.enable_device(serial) + cfg.enable_stream(rs.stream.color, int(w), int(h), rs.format.bgr8, int(fps)) + pipe.start(cfg) + self._rs_align = rs.align(rs.stream.color) + self._realsense_serial = serial or self._realsense_serial + self._active_profile = f"{w}x{h}@{fps}" + return pipe + except Exception: + try: + pipe.stop() + except Exception: + pass + serial_note = serial or "(auto)" + raise RuntimeError(f"RealSense color stream open failed. serial={serial_note} tried: {', '.join(tried)}") + + + + + + def _configure_capture(self, cap): + try: + cap.set(cv2.CAP_PROP_BUFFERSIZE, 1) + except Exception: + pass + try: + cap.set(cv2.CAP_PROP_FOURCC, cv2.VideoWriter_fourcc(*"MJPG")) + except Exception: + pass + cap.set(cv2.CAP_PROP_FRAME_WIDTH, self.width) + cap.set(cv2.CAP_PROP_FRAME_HEIGHT, self.height) + cap.set(cv2.CAP_PROP_FPS, self.fps) + + + + + + + def _close_locked(self): + if self._rs_pipeline is not None: + try: + self._rs_pipeline.stop() + except Exception: + pass + self._rs_pipeline = None + self._rs_align = None + if self._cap is not None: + try: + self._cap.release() + except Exception: + pass + self._cap = None + self._camera_source_in_use = None + self._backend = "opencv" + self._active_profile = None + + + + + + def _read_frame_locked(self): + if self._rs_pipeline is not None: + frames = self._rs_pipeline.wait_for_frames(timeout_ms=1000) + if self._rs_align is not None: + frames = self._rs_align.process(frames) + color_frame = frames.get_color_frame() + if not color_frame: + return False, None + frame = np.asanyarray(color_frame.get_data()) + if frame is None or frame.size == 0: + return False, None + return True, frame + if self._cap is None: + return False, None + return self._cap.read() + + def _ensure_open_locked(self) -> bool: + now = time.time() + if self._rs_pipeline is not None: + return True + if self._cap is not None and self._cap.isOpened(): + return True + if now < self._reopen_after: + return False + + self._last_error = "Opening camera..." + self._close_locked() + tried = [] + last_open_error = "" + for source in self._candidate_sources(): + tried.append(str(source)) + if source == "realsense": + pipe = None + try: + pipe = self._open_realsense() + frames = pipe.wait_for_frames(timeout_ms=1500) + color_frame = frames.get_color_frame() + if not color_frame: + pipe.stop() + continue + frame = np.asanyarray(color_frame.get_data()) + if frame is None or frame.size == 0: + pipe.stop() + continue + self._rs_pipeline = pipe + self._backend = "realsense" + self._camera_source_in_use = source + self._last_error = "" + self._consecutive_read_failures = 0 + self._latest_frame = frame.copy() + return True + except Exception as e: + last_open_error = str(e) + self._last_error = str(e) + try: + if pipe is not None: + pipe.stop() + except Exception: + pass + continue + else: + cap = None + try: + cap = self._open_capture(source) + except Exception: + cap = None + if cap is None or not cap.isOpened(): + try: + if cap is not None: + cap.release() + except Exception: + pass + continue + + self._configure_capture(cap) + + ok, frame = cap.read() + if not ok or frame is None: + cap.release() + continue + if self.source == "realsense" and not self._looks_rgb(frame): + cap.release() + continue + + self._cap = cap + self._backend = "opencv" + self._camera_source_in_use = source + self._last_error = "" + self._consecutive_read_failures = 0 + return True + + self._last_error = last_open_error or f"Could not open camera. Tried: {', '.join(tried)}" + self._reopen_after = now + self._reopen_delay_sec + return False + + def start(self): + if self._thread and self._thread.is_alive(): + return + self._stop.clear() + self._thread = threading.Thread(target=self._run, daemon=True) + self._thread.start() + + def stop(self): + self._stop.set() + if self._thread: + self._thread.join(timeout=1.0) + with self._lock: + self._close_locked() + + def _run(self): + while not self._stop.is_set(): + frame = None + frame_ts = 0.0 + with self._lock: + if not self._ensure_open_locked(): + time.sleep(0.2) + continue + try: + ok, frame = self._read_frame_locked() + if not ok or frame is None: + self._consecutive_read_failures += 1 + self._last_error = f"Camera read failed ({self._consecutive_read_failures}/{self._max_read_failures_before_reopen})" + if self._consecutive_read_failures < self._max_read_failures_before_reopen: + time.sleep(0.05) + continue + self._close_locked() + self._reopen_after = time.time() + self._reopen_delay_sec + self._consecutive_read_failures = 0 + time.sleep(0.2) + continue + self._consecutive_read_failures = 0 + self._latest_frame = frame.copy() + frame_ts = time.time() + except Exception as e: + self._last_error = str(e) + self._close_locked() + self._reopen_after = time.time() + self._reopen_delay_sec + self._consecutive_read_failures = 0 + frame = None + + if frame is not None: + try: + ok, jpg = cv2.imencode(".jpg", frame, [int(cv2.IMWRITE_JPEG_QUALITY), self.preview_quality]) + if ok and jpg is not None: + with self._lock: + self._latest_jpeg = jpg.tobytes() + self._frame_ts = frame_ts + except Exception: + pass + + time.sleep(max(0.02, 1.0 / max(self.fps, 1))) + + def latest_jpeg(self) -> Optional[bytes]: + return self._latest_jpeg + + def capture(self, out_dir: Path, prefix: str = "sample", ext: str = "jpg") -> Path: + out_dir.mkdir(parents=True, exist_ok=True) + if not self._lock.acquire(timeout=0.5): + raise RuntimeError("camera busy") + try: + if not self._ensure_open_locked(): + raise RuntimeError(self._last_error or "camera unavailable") + + frame = self._latest_frame + if frame is None: + ok, frame = self._read_frame_locked() + if not ok or frame is None: + raise RuntimeError("camera read failed during capture") + + ok, jpg = cv2.imencode(".jpg", frame, [int(cv2.IMWRITE_JPEG_QUALITY), 95]) + if not ok or jpg is None: + raise RuntimeError("cv2.imencode failed") + + out_path = build_ordered_datetime_name(out_dir, prefix, ext) + out_path.write_bytes(jpg.tobytes()) + return out_path + finally: + self._lock.release() + + def reconfigure(self, width: int, height: int, fps: int) -> dict: + width = int(width) + height = int(height) + fps = int(fps) + if width < 1 or height < 1 or fps < 1: + raise RuntimeError("width, height, and fps must be positive integers") + + if not self._lock.acquire(timeout=1.0): + raise RuntimeError("camera busy") + try: + self.width = width + self.height = height + self.fps = fps + self._last_error = f"Reconfiguring camera to {width}x{height}@{fps}..." + self._latest_frame = None + self._latest_jpeg = None + self._frame_ts = 0.0 + self._close_locked() + self._reopen_after = 0.0 + self._consecutive_read_failures = 0 + finally: + self._lock.release() + + deadline = time.time() + 6.0 + while time.time() < deadline and not self._stop.is_set(): + status = self.status() + if status["ok"]: + return status + time.sleep(0.05) + return self.status() + + def set_source(self, source: Union[str, int]) -> dict: + resolved = self._resolve_source(source) + if not self._lock.acquire(timeout=1.0): + raise RuntimeError("camera busy") + try: + self.source = resolved + self._last_error = f"Switching camera source to {resolved}..." + self._latest_frame = None + self._latest_jpeg = None + self._frame_ts = 0.0 + self._close_locked() + self._reopen_after = 0.0 + self._consecutive_read_failures = 0 + finally: + self._lock.release() + + deadline = time.time() + 6.0 + while time.time() < deadline and not self._stop.is_set(): + status = self.status() + if status["ok"]: + return status + time.sleep(0.05) + return self.status() + + def set_preferred_realsense_serial(self, serial: str) -> dict: + value = str(serial or "").strip() + if not self._lock.acquire(timeout=1.0): + raise RuntimeError("camera busy") + try: + self._preferred_realsense_serial = value + self._config_realsense_serial = value + if self.source == "realsense": + self._last_error = f"Switching preferred RealSense to {value or '(auto)'}..." + self._latest_frame = None + self._latest_jpeg = None + self._frame_ts = 0.0 + self._close_locked() + self._reopen_after = 0.0 + self._consecutive_read_failures = 0 + finally: + self._lock.release() + + deadline = time.time() + 6.0 + while time.time() < deadline and not self._stop.is_set(): + status = self.status() + if status["ok"] or self.source != "realsense": + return status + time.sleep(0.05) + return self.status() + + def status(self) -> dict: + self._refresh_realsense_preferences() + return { + "ok": bool(self._rs_pipeline is not None or (self._cap is not None and self._cap.isOpened())), + "requested_source": str(self.source), + "source": str(self._camera_source_in_use if self._camera_source_in_use is not None else self.source), + "backend": self._backend, + "profile": self._active_profile, + "requested_profile": f"{self.width}x{self.height}@{self.fps}", + "requested_width": self.width, + "requested_height": self.height, + "requested_fps": self.fps, + "preferred_realsense_serial": self._preferred_realsense_serial, + "config_realsense_serial": self._config_realsense_serial, + "configured_realsense_serial": self._configured_realsense_serial, + "realsense_serial": self._realsense_serial, + "last_error": self._last_error, + "frame_time": self._frame_ts, + } + + +def static_file_response(path: Path) -> tuple[bytes, str]: + raw = path.read_bytes() + content_type, _ = mimetypes.guess_type(str(path)) + return raw, content_type or "application/octet-stream" + + +class SamplesHandler(BaseHTTPRequestHandler): + server_version = "DirectCameraSamples/1.0" + + def _json(self, payload: dict, status: int = 200): + raw = json.dumps(payload, ensure_ascii=False).encode("utf-8") + self.send_response(status) + self.send_header("Content-Type", "application/json; charset=utf-8") + self.send_header("Content-Length", str(len(raw))) + self.send_header("Cache-Control", "no-store") + self.end_headers() + self.wfile.write(raw) + + def _text(self, text: str, status: int = 200, content_type: str = "text/plain; charset=utf-8"): + raw = text.encode("utf-8") + self.send_response(status) + self.send_header("Content-Type", content_type) + self.send_header("Content-Length", str(len(raw))) + self.send_header("Cache-Control", "no-store") + self.end_headers() + self.wfile.write(raw) + + def _binary(self, raw: bytes, status: int = 200, content_type: str = "application/octet-stream", cache_control: str = "no-store"): + self.send_response(status) + self.send_header("Content-Type", content_type) + self.send_header("Content-Length", str(len(raw))) + self.send_header("Cache-Control", cache_control) + self.end_headers() + self.wfile.write(raw) + + def log_message(self, fmt: str, *args): + path = getattr(self, "path", "") + if path.startswith("/api/health") or path.startswith("/api/photos"): + return + print(f"HTTP {self.command} {path} -> {args[1]}") + + def do_GET(self): + parsed = urllib.parse.urlparse(self.path) + path = parsed.path + q = urllib.parse.parse_qs(parsed.query) + + if path == "/": + raw, content_type = static_file_response(DIRECT_CAMERA_HTML) + return self._binary(raw, content_type=f"{content_type}; charset=utf-8") + + if path == "/static/direct_camera.css": + raw, content_type = static_file_response(DIRECT_CAMERA_CSS) + return self._binary(raw, content_type=content_type) + + if path == "/static/direct_camera.js": + raw, content_type = static_file_response(DIRECT_CAMERA_JS) + return self._binary(raw, content_type=f"{content_type}; charset=utf-8") + + if path == "/api/health": + return self._json( + { + "ok": True, + "camera": self.server.camera.status(), + "samples_dir": str(self.server.samples_dir), + } + ) + + if path == "/api/cameras": + camera_status = self.server.camera.status() + realsense_devices = list_realsense_devices() + video_devices = list_video_device_info() + preferred_serial = str(camera_status.get("preferred_realsense_serial") or "").strip() + active_serial = str(camera_status.get("realsense_serial") or "").strip() + + preferred_device = None + active_device = None + rs_items = [] + for item in realsense_devices: + serial = str(item.get("serial") or "").strip() + is_preferred = bool(serial and serial == preferred_serial) + is_active = bool(serial and serial == active_serial) + if is_preferred: + preferred_device = item + if is_active: + active_device = item + label = str(item.get("label") or item.get("value") or "").strip() + tags = [] + if is_preferred: + tags.append("default") + if is_active: + tags.append("live") + if tags: + label = f"{label} ({', '.join(tags)})" + rs_items.append({**item, "kind": "realsense", "is_preferred": is_preferred, "is_active": is_active, "label": label}) + + generic_label = "Preferred RealSense" + if preferred_serial: + generic_label += f" [{preferred_serial}]" + generic_label += " (default)" + + options = [{"value": "realsense", "label": generic_label, "kind": "realsense-default"}] + options.extend(rs_items) + options.extend({**item, "kind": "video"} for item in video_devices) + options.append({"value": "auto", "label": "Auto fallback", "kind": "auto"}) + return self._json( + { + "ok": True, + "selected_source": str(self.server.camera.source), + "active_source": str(camera_status.get("source") or self.server.camera.source), + "preferred_realsense_serial": preferred_serial, + "configured_realsense_serial": str(camera_status.get("configured_realsense_serial") or ""), + "config_realsense_serial": str(camera_status.get("config_realsense_serial") or ""), + "realsense_devices": rs_items, + "video_devices": video_devices, + "preferred_device": preferred_device, + "active_device": active_device, + "options": options, + } + ) + + if path == "/api/photos": + return self._json({"items": list_photos(self.server.samples_dir)}) + + if path == "/api/capture": + try: + prefix = ((q.get("prefix") or [self.server.capture_prefix])[0] or self.server.capture_prefix).strip() or self.server.capture_prefix + ext = ((q.get("ext") or [self.server.capture_ext])[0] or self.server.capture_ext).strip().lstrip(".") or self.server.capture_ext + saved = self.server.camera.capture(self.server.samples_dir, prefix=prefix, ext=ext) + return self._json({"ok": True, "name": saved.name, "path": str(saved)}) + except Exception as e: + return self._json({"ok": False, "error": str(e)}, status=500) + + if path == "/api/frame.jpg": + jpg = self.server.camera.latest_jpeg() + if jpg is None: + return self._text("camera not ready", status=503) + self.send_response(200) + self.send_header("Content-Type", "image/jpeg") + self.send_header("Content-Length", str(len(jpg))) + self.send_header("Cache-Control", "no-store") + self.end_headers() + self.wfile.write(jpg) + return + + if path == "/api/set_resolution": + try: + width = int((q.get("width") or [""])[0]) + height = int((q.get("height") or [""])[0]) + fps = int((q.get("fps") or [""])[0]) + except Exception: + return self._json({"ok": False, "error": "width, height, and fps are required integers"}, status=400) + try: + status = self.server.camera.reconfigure(width, height, fps) + return self._json({"ok": True, "camera": status}) + except Exception as e: + return self._json({"ok": False, "error": str(e)}, status=500) + + if path == "/api/set_camera": + source = (q.get("source") or [""])[0].strip() + if not source: + return self._json({"ok": False, "error": "missing source"}, status=400) + try: + status = self.server.camera.set_source(source) + return self._json({"ok": True, "camera": status}) + except Exception as e: + return self._json({"ok": False, "error": str(e)}, status=500) + + if path == "/api/set_preferred_camera": + serial = (q.get("serial") or [""])[0].strip() + try: + saved = write_config_preferred_realsense_serial(serial) + status = self.server.camera.set_preferred_realsense_serial(saved) + return self._json({"ok": True, "serial": saved, "camera": status}) + except Exception as e: + return self._json({"ok": False, "error": str(e)}, status=500) + + if path == "/api/delete": + name = safe_name((q.get("name") or [""])[0]) + if not name: + return self._json({"ok": False, "error": "missing name"}, status=400) + p = (self.server.samples_dir / name).resolve() + if p.parent != self.server.samples_dir.resolve() or not p.exists(): + return self._json({"ok": False, "error": "not found"}, status=404) + try: + p.unlink() + return self._json({"ok": True, "name": name}) + except Exception as e: + return self._json({"ok": False, "error": str(e)}, status=500) + + if path == "/api/download": + name = safe_name((q.get("name") or [""])[0]) + if not name: + return self._text("missing name", status=400) + p = (self.server.samples_dir / name).resolve() + if p.parent != self.server.samples_dir.resolve() or not p.exists(): + return self._text("not found", status=404) + data = p.read_bytes() + self.send_response(200) + self.send_header("Content-Type", "application/octet-stream") + self.send_header("Content-Length", str(len(data))) + self.send_header("Content-Disposition", f'attachment; filename="{p.name}"') + self.end_headers() + self.wfile.write(data) + return + + if path == "/api/download_all.zip": + buf = io.BytesIO() + with zipfile.ZipFile(buf, "w", zipfile.ZIP_DEFLATED) as zf: + for item in list_photos(self.server.samples_dir): + p = self.server.samples_dir / item["name"] + zf.write(p, arcname=p.name) + raw = buf.getvalue() + self.send_response(200) + self.send_header("Content-Type", "application/zip") + self.send_header("Content-Length", str(len(raw))) + self.send_header("Content-Disposition", 'attachment; filename="samples.zip"') + self.end_headers() + self.wfile.write(raw) + return + + if path.startswith("/samples/"): + name = safe_name(path[len("/samples/"):]) + p = (self.server.samples_dir / name).resolve() + if p.parent != self.server.samples_dir.resolve() or not p.exists(): + return self._text("not found", status=404) + data = p.read_bytes() + ext = p.suffix.lower() + ct = "image/jpeg" if ext in (".jpg", ".jpeg") else "image/png" + self.send_response(200) + self.send_header("Content-Type", ct) + self.send_header("Content-Length", str(len(data))) + self.send_header("Cache-Control", "no-store") + self.end_headers() + self.wfile.write(data) + return + + if path == "/preview.mjpg": + self.send_response(200) + self.send_header("Age", "0") + self.send_header("Cache-Control", "no-cache, private") + self.send_header("Pragma", "no-cache") + self.send_header("Content-Type", "multipart/x-mixed-replace; boundary=frame") + self.end_headers() + try: + while True: + jpg = self.server.camera.latest_jpeg() + if jpg is None: + time.sleep(0.05) + continue + self.wfile.write(b"--frame\r\n") + self.wfile.write(b"Content-Type: image/jpeg\r\n") + self.wfile.write(f"Content-Length: {len(jpg)}\r\n\r\n".encode("ascii")) + self.wfile.write(jpg) + self.wfile.write(b"\r\n") + time.sleep(0.12) + except BrokenPipeError: + return + except ConnectionResetError: + return + except Exception: + return + + return self._text("not found", status=404) + + +class SamplesServer(ThreadingHTTPServer): + def __init__( + self, + addr, + handler_cls, + camera: DirectCamera, + samples_dir: Path, + capture_prefix: str = "sample", + capture_ext: str = "jpg", + ): + super().__init__(addr, handler_cls) + self.camera = camera + self.samples_dir = samples_dir + self.capture_prefix = capture_prefix + self.capture_ext = capture_ext + + +def parse_args(): + parser = argparse.ArgumentParser(description="Standalone direct-camera samples server") + parser.add_argument("--host", default="0.0.0.0") + parser.add_argument("--port", type=int, default=int(os.environ.get("PORT", "8091"))) + parser.add_argument("--camera", default=os.environ.get("CAMERA_DEVICE", os.environ.get("CAMERA_INDEX", "auto"))) + parser.add_argument("--width", type=int, default=int(os.environ.get("FRAME_WIDTH", "960"))) + parser.add_argument("--height", type=int, default=int(os.environ.get("FRAME_HEIGHT", "540"))) + parser.add_argument("--fps", type=int, default=int(os.environ.get("FPS", "15"))) + parser.add_argument("--samples-dir", default=os.environ.get("SAMPLES_DIR", str(DEFAULT_SAMPLES_DIR))) + parser.add_argument("--capture-prefix", default=os.environ.get("CAPTURE_PREFIX", "sample")) + parser.add_argument("--capture-ext", default=os.environ.get("CAPTURE_EXT", "jpg")) + return parser.parse_args() + + +def main(): + args = parse_args() + samples_dir = Path(args.samples_dir).expanduser().resolve() + samples_dir.mkdir(parents=True, exist_ok=True) + + if str(args.camera).strip().lower() in ("realsense", "rs") and not _HAS_RS: + raise SystemExit( + "RealSense backend requested but pyrealsense2 is not installed in this environment. " + "Run this script from the teleimager conda env or install pyrealsense2 here." + ) + + camera = DirectCamera(source=args.camera, width=args.width, height=args.height, fps=args.fps) + camera.start() + + server = SamplesServer( + (args.host, args.port), + SamplesHandler, + camera=camera, + samples_dir=samples_dir, + capture_prefix=str(args.capture_prefix).strip() or "sample", + capture_ext=str(args.capture_ext).strip().lstrip(".") or "jpg", + ) + ip = get_local_ip() + print(f"Video devices: {', '.join(list_video_devices()) or '(none found)'}") + if _HAS_RS: + print(f"RealSense serials: {', '.join(list_realsense_serials()) or '(none found)'}") + print(f"Preferred RealSense serial: {camera._preferred_realsense_serial}") + print(f"Samples dir: {samples_dir}") + print(f"Camera source: {args.camera}") + print(f"Capture naming: prefix={server.capture_prefix} ext={server.capture_ext}") + print(f"Open: http://{ip}:{args.port}/") + + try: + server.serve_forever() + except KeyboardInterrupt: + pass + finally: + server.shutdown() + camera.stop() + + +if __name__ == "__main__": + main() diff --git a/Core/error_events.py b/Core/error_events.py new file mode 100644 index 0000000..d8f3450 --- /dev/null +++ b/Core/error_events.py @@ -0,0 +1,104 @@ +""" +error_events.py + +Small structured error event sink: +- In-memory counters per (source, stage) +- JSONL event log (append-only) +- JSON counters snapshot for quick dashboard/debug fetch +""" + +from __future__ import annotations + +import json +import threading +import time +from pathlib import Path +from typing import Any, Dict + +try: + from Core import settings as config + + _STATE_DIR = Path(config.APP_RUNTIME_DIR) + _LEGACY_STATE_DIR = Path(config.APP_DATA_DIR) +except Exception: + _STATE_DIR = Path(__file__).resolve().parents[1] / "Data" / "Runtime" + _LEGACY_STATE_DIR = Path(__file__).resolve().parents[1] / "Data" + +_STATE_DIR.mkdir(parents=True, exist_ok=True) +_COUNTERS_PATH = _STATE_DIR / "error_counters.json" +_EVENTS_PATH = _STATE_DIR / "error_events.jsonl" +_LEGACY_COUNTERS_PATH = _LEGACY_STATE_DIR / "error_counters.json" + +_LOCK = threading.Lock() +_COUNTERS: Dict[str, int] = {} +_LAST_EVENT_TS: Dict[str, float] = {} +_MIN_INTERVAL_SEC = 0.75 + + +def _load_counters() -> Dict[str, int]: + for candidate in (_COUNTERS_PATH, _LEGACY_COUNTERS_PATH): + try: + if candidate.exists(): + raw = json.loads(candidate.read_text(encoding="utf-8")) + if isinstance(raw, dict): + out: Dict[str, int] = {} + for k, v in raw.items(): + try: + out[str(k)] = int(v) + except Exception: + continue + return out + except Exception: + pass + return {} + + +with _LOCK: + _COUNTERS.update(_load_counters()) + + +def record_error(source: str, stage: str, exc: Any = None, context: Dict[str, Any] | None = None) -> int: + """ + Record one structured error event. + Returns current counter value for this error key. + """ + now = time.time() + src = str(source or "unknown") + stg = str(stage or "unknown") + key = f"{src}:{stg}" + msg = "" if exc is None else str(exc) + payload = { + "time": now, + "source": src, + "stage": stg, + "message": msg, + "context": context or {}, + } + + with _LOCK: + count = _COUNTERS.get(key, 0) + 1 + _COUNTERS[key] = count + payload["count"] = count + + # Throttle repetitive event writes for the same key. + last = float(_LAST_EVENT_TS.get(key, 0.0)) + should_write_event = (now - last) >= _MIN_INTERVAL_SEC + if should_write_event: + _LAST_EVENT_TS[key] = now + try: + with _EVENTS_PATH.open("a", encoding="utf-8") as f: + f.write(json.dumps(payload, ensure_ascii=False) + "\n") + except Exception: + pass + + try: + _COUNTERS_PATH.write_text(json.dumps(_COUNTERS, ensure_ascii=False, indent=2), encoding="utf-8") + except Exception: + pass + + return count + + +def get_error_counters() -> Dict[str, int]: + with _LOCK: + return dict(_COUNTERS) diff --git a/Core/people_registry.py b/Core/people_registry.py new file mode 100644 index 0000000..f0a74b7 --- /dev/null +++ b/Core/people_registry.py @@ -0,0 +1,456 @@ +from __future__ import annotations + +import json +import math +import shutil +import time +import zipfile +from datetime import datetime +from pathlib import Path +from typing import Any, Dict, Optional + +import cv2 +import numpy as np + +from Core import settings as config + + +PERSON_JSON = "person.json" +FACE_REF_NAME = "face_ref.jpg" +SCENE_REF_NAME = "scene_ref.jpg" +CAPTURE_PREFIX = "capture_" +SUPPORTED_IMAGE_EXTS = (".jpg", ".jpeg", ".png", ".webp") + + +def people_dir() -> Path: + path = Path(config.PEOPLE_DIR).resolve() + path.mkdir(parents=True, exist_ok=True) + return path + + +def _now_ts() -> float: + return time.time() + + +def _fmt_date(ts: float) -> str: + return datetime.fromtimestamp(float(ts)).strftime("%Y-%m-%d") + + +def _person_dirs() -> list[Path]: + root = people_dir() + return [p for p in sorted(root.iterdir()) if p.is_dir()] + + +def _person_json_path(person_dir: Path) -> Path: + return person_dir / PERSON_JSON + + +def _read_person(person_dir: Path) -> Optional[Dict[str, Any]]: + try: + raw = json.loads(_person_json_path(person_dir).read_text(encoding="utf-8")) + if not isinstance(raw, dict): + return None + return raw + except Exception: + return None + + +def _write_person(person_dir: Path, data: Dict[str, Any]) -> None: + person_dir.mkdir(parents=True, exist_ok=True) + _person_json_path(person_dir).write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8") + + +def _list_existing_sequences() -> list[int]: + out: list[int] = [] + for person_dir in _person_dirs(): + meta = _read_person(person_dir) + if not meta: + continue + try: + out.append(int(meta.get("sequence", 0))) + except Exception: + continue + return out + + +def _next_sequence() -> int: + seqs = _list_existing_sequences() + return (max(seqs) if seqs else 0) + 1 + + +def _make_person_id(sequence: int, ts: float) -> str: + return f"guest_{int(sequence):04d}_{datetime.fromtimestamp(ts).strftime('%Y%m%d_%H%M%S')}" + + +def _display_label(meta: Dict[str, Any]) -> str: + short_id = str(meta.get("short_id") or meta.get("person_id") or "guest").replace("_", " ") + created_date = str(meta.get("created_date") or "") + return f"{short_id} from {created_date}".strip() + + +def _clip_box(box: Dict[str, Any], frame_shape: tuple[int, ...], pad_ratio: float = 0.18) -> Optional[tuple[int, int, int, int]]: + if not isinstance(box, dict): + return None + try: + h, w = frame_shape[:2] + x = float(box.get("x", 0.0)) + y = float(box.get("y", 0.0)) + bw = max(1.0, float(box.get("w", 0.0))) + bh = max(1.0, float(box.get("h", 0.0))) + pad_w = bw * float(pad_ratio) + pad_h = bh * float(pad_ratio) + x1 = max(0, int(math.floor(x - pad_w))) + y1 = max(0, int(math.floor(y - pad_h))) + x2 = min(w, int(math.ceil(x + bw + pad_w))) + y2 = min(h, int(math.ceil(y + bh + pad_h))) + if x2 <= x1 or y2 <= y1: + return None + return x1, y1, x2, y2 + except Exception: + return None + + +def detect_face_box(image_bgr: np.ndarray) -> Optional[Dict[str, int]]: + if image_bgr is None or getattr(image_bgr, "size", 0) == 0: + return None + try: + cascade = cv2.CascadeClassifier(str(Path(cv2.data.haarcascades) / "haarcascade_frontalface_default.xml")) + if cascade.empty(): + return None + gray = cv2.cvtColor(image_bgr, cv2.COLOR_BGR2GRAY) + faces = cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5, minSize=(48, 48)) + if len(faces) == 0: + return None + x, y, w, h = max(faces, key=lambda item: int(item[2]) * int(item[3])) + return {"x": int(x), "y": int(y), "w": int(w), "h": int(h)} + except Exception: + return None + + +def _extract_face_crop(frame_bgr: np.ndarray, face_box: Dict[str, Any]) -> Optional[np.ndarray]: + clipped = _clip_box(face_box, frame_bgr.shape, pad_ratio=0.18) + if clipped is None: + return None + x1, y1, x2, y2 = clipped + crop = frame_bgr[y1:y2, x1:x2] + if crop is None or crop.size == 0: + return None + return crop.copy() + + +def _extract_scene_crop(frame_bgr: np.ndarray, subject_box: Optional[Dict[str, Any]]) -> np.ndarray: + if frame_bgr is None or getattr(frame_bgr, "size", 0) == 0: + raise ValueError("empty frame") + if not subject_box: + return frame_bgr.copy() + clipped = _clip_box(subject_box, frame_bgr.shape, pad_ratio=0.28) + if clipped is None: + return frame_bgr.copy() + x1, y1, x2, y2 = clipped + crop = frame_bgr[y1:y2, x1:x2] + if crop is None or crop.size == 0: + return frame_bgr.copy() + return crop.copy() + + +def _compute_embedding(face_bgr: np.ndarray) -> np.ndarray: + gray = cv2.cvtColor(face_bgr, cv2.COLOR_BGR2GRAY) + gray = cv2.resize(gray, (48, 48), interpolation=cv2.INTER_AREA) + gray = cv2.equalizeHist(gray) + vec = gray.astype(np.float32).reshape(-1) + vec -= float(vec.mean()) + norm = float(np.linalg.norm(vec)) + if norm <= 1e-6: + return vec + return vec / norm + + +def _embedding_similarity(a: np.ndarray, b: np.ndarray) -> float: + if a.size == 0 or b.size == 0: + return 0.0 + denom = float(np.linalg.norm(a) * np.linalg.norm(b)) + if denom <= 1e-6: + return 0.0 + return float(np.dot(a, b) / denom) + + +def _load_embedding(meta: Dict[str, Any]) -> np.ndarray: + raw = meta.get("embedding") or [] + try: + arr = np.asarray(raw, dtype=np.float32) + except Exception: + arr = np.asarray([], dtype=np.float32) + return arr + + +def _save_image(path: Path, image_bgr: np.ndarray) -> None: + path.parent.mkdir(parents=True, exist_ok=True) + cv2.imwrite(str(path), image_bgr) + + +def _append_sample(person_dir: Path, meta: Dict[str, Any], face_bgr: np.ndarray, scene_bgr: np.ndarray, embedding: np.ndarray, source: str) -> Dict[str, Any]: + now = _now_ts() + sample_count = int(meta.get("sample_count", 0)) + 1 + prev_embedding = _load_embedding(meta) + if prev_embedding.size and prev_embedding.shape == embedding.shape: + new_embedding = ((prev_embedding * float(sample_count - 1)) + embedding) / float(sample_count) + norm = float(np.linalg.norm(new_embedding)) + if norm > 1e-6: + new_embedding = new_embedding / norm + else: + new_embedding = embedding + + face_name = f"face_{sample_count:03d}.jpg" + scene_name = f"scene_{sample_count:03d}.jpg" + _save_image(person_dir / face_name, face_bgr) + _save_image(person_dir / scene_name, scene_bgr) + + meta["sample_count"] = sample_count + meta["times_seen"] = int(meta.get("times_seen", 0)) + 1 + meta["last_seen_at"] = now + meta["embedding"] = new_embedding.astype(float).tolist() + meta["last_source"] = str(source or "vision") + meta["face_images"] = sorted( + [p.name for p in person_dir.iterdir() if p.is_file() and p.name.startswith("face_") and p.suffix.lower() in SUPPORTED_IMAGE_EXTS] + ) + meta["scene_images"] = sorted( + [p.name for p in person_dir.iterdir() if p.is_file() and p.name.startswith("scene_") and p.suffix.lower() in SUPPORTED_IMAGE_EXTS] + ) + if not (person_dir / FACE_REF_NAME).exists(): + _save_image(person_dir / FACE_REF_NAME, face_bgr) + if not (person_dir / SCENE_REF_NAME).exists(): + _save_image(person_dir / SCENE_REF_NAME, scene_bgr) + _write_person(person_dir, meta) + return meta + + +def _create_person(face_bgr: np.ndarray, scene_bgr: np.ndarray, embedding: np.ndarray, source: str) -> Dict[str, Any]: + now = _now_ts() + seq = _next_sequence() + person_id = _make_person_id(seq, now) + short_id = f"guest_{seq:04d}" + person_dir = people_dir() / person_id + _save_image(person_dir / FACE_REF_NAME, face_bgr) + _save_image(person_dir / SCENE_REF_NAME, scene_bgr) + meta = { + "person_id": person_id, + "short_id": short_id, + "display_name": f"{short_id} from {_fmt_date(now)}", + "sequence": seq, + "created_at": now, + "created_date": _fmt_date(now), + "last_seen_at": now, + "sample_count": 0, + "times_seen": 0, + "source": str(source or "vision"), + "last_source": str(source or "vision"), + "embedding": embedding.astype(float).tolist(), + "face_images": [], + "scene_images": [], + "captured_photos": [], + } + meta = _append_sample(person_dir, meta, face_bgr, scene_bgr, embedding, source=source) + meta["new_person"] = True + meta["known_person"] = False + meta["person_dir"] = str(person_dir) + meta["display_label"] = _display_label(meta) + return meta + + +def recognize_or_enroll(frame_bgr: np.ndarray, face_box: Optional[Dict[str, Any]], subject_box: Optional[Dict[str, Any]] = None, threshold: Optional[float] = None, source: str = "vision") -> Dict[str, Any]: + if frame_bgr is None or getattr(frame_bgr, "size", 0) == 0: + return {"ok": False, "error": "empty frame"} + if face_box is None: + return {"ok": False, "error": "no face"} + + try: + face_bgr = _extract_face_crop(frame_bgr, face_box) + if face_bgr is None: + return {"ok": False, "error": "invalid face crop"} + scene_bgr = _extract_scene_crop(frame_bgr, subject_box) + embedding = _compute_embedding(face_bgr) + if embedding.size == 0: + return {"ok": False, "error": "invalid embedding"} + + match_threshold = float(threshold if threshold is not None else config.read_vision_face_recognition_threshold()) + best_meta = None + best_dir = None + best_score = -1.0 + + for person_dir in _person_dirs(): + meta = _read_person(person_dir) + if not meta: + continue + stored = _load_embedding(meta) + if stored.size == 0 or stored.shape != embedding.shape: + continue + score = _embedding_similarity(embedding, stored) + if score > best_score: + best_score = score + best_meta = meta + best_dir = person_dir + + if best_meta is not None and best_dir is not None and best_score >= match_threshold: + best_meta = _append_sample(best_dir, best_meta, face_bgr, scene_bgr, embedding, source=source) + best_meta["ok"] = True + best_meta["known_person"] = True + best_meta["new_person"] = False + best_meta["match_score"] = float(best_score) + best_meta["display_label"] = _display_label(best_meta) + return best_meta + + created = _create_person(face_bgr, scene_bgr, embedding, source=source) + created["ok"] = True + created["match_score"] = float(best_score if best_score >= 0.0 else 0.0) + return created + except Exception as e: + return {"ok": False, "error": str(e)} + + +def _load_image_from_bytes(data: bytes) -> Optional[np.ndarray]: + if not data: + return None + arr = np.frombuffer(data, dtype=np.uint8) + image = cv2.imdecode(arr, cv2.IMREAD_COLOR) + return image + + +def import_person_photo(data: bytes, filename: str = "", person_id: str = "") -> Dict[str, Any]: + image = _load_image_from_bytes(data) + if image is None: + return {"ok": False, "error": "invalid image"} + face_box = detect_face_box(image) + if face_box is None: + return {"ok": False, "error": "no face detected in uploaded image"} + person_id = str(person_id or "").strip() + if person_id: + person_dir = people_dir() / person_id + meta = _read_person(person_dir) + if not meta: + return {"ok": False, "error": "person not found"} + face_bgr = _extract_face_crop(image, face_box) + if face_bgr is None: + return {"ok": False, "error": "invalid face crop"} + scene_bgr = image.copy() + embedding = _compute_embedding(face_bgr) + meta = _append_sample(person_dir, meta, face_bgr, scene_bgr, embedding, source="upload") + meta["ok"] = True + meta["known_person"] = True + meta["new_person"] = False + meta["display_label"] = _display_label(meta) + return meta + return recognize_or_enroll(image, face_box, None, source="upload") + + +def attach_captured_photo(person_id: str, photo_path: str | Path) -> bool: + person_id = str(person_id or "").strip() + if not person_id: + return False + person_dir = people_dir() / person_id + meta = _read_person(person_dir) + if not meta: + return False + src = Path(photo_path).expanduser() + if not src.exists() or not src.is_file(): + return False + dst = person_dir / f"{CAPTURE_PREFIX}{src.name}" + try: + shutil.copy2(src, dst) + photos = meta.get("captured_photos") or [] + if not isinstance(photos, list): + photos = [] + if dst.name not in photos: + photos.append(dst.name) + meta["captured_photos"] = sorted(photos) + meta["last_seen_at"] = _now_ts() + _write_person(person_dir, meta) + return True + except Exception: + return False + + +def list_people() -> list[Dict[str, Any]]: + items: list[Dict[str, Any]] = [] + for person_dir in _person_dirs(): + meta = _read_person(person_dir) + if not meta: + continue + face_thumb = person_dir / FACE_REF_NAME + scene_thumb = person_dir / SCENE_REF_NAME + items.append( + { + "person_id": str(meta.get("person_id") or person_dir.name), + "short_id": str(meta.get("short_id") or ""), + "display_name": str(meta.get("display_name") or _display_label(meta)), + "created_at": float(meta.get("created_at", 0.0) or 0.0), + "created_date": str(meta.get("created_date") or ""), + "last_seen_at": float(meta.get("last_seen_at", 0.0) or 0.0), + "sample_count": int(meta.get("sample_count", 0) or 0), + "times_seen": int(meta.get("times_seen", 0) or 0), + "source": str(meta.get("source") or meta.get("last_source") or ""), + "last_source": str(meta.get("last_source") or ""), + "face_thumb": face_thumb.name if face_thumb.exists() else "", + "scene_thumb": scene_thumb.name if scene_thumb.exists() else "", + "captured_photos": list(meta.get("captured_photos") or []), + "known": True, + } + ) + items.sort(key=lambda item: float(item.get("last_seen_at", 0.0) or 0.0), reverse=True) + return items + + +def get_person(person_id: str) -> Optional[Dict[str, Any]]: + person_dir = people_dir() / str(person_id or "").strip() + meta = _read_person(person_dir) + if not meta: + return None + meta["person_dir"] = str(person_dir) + meta["display_label"] = _display_label(meta) + return meta + + +def read_person_image(person_id: str, kind: str = "face") -> Optional[tuple[bytes, str, str]]: + person_id = str(person_id or "").strip() + if not person_id: + return None + person_dir = people_dir() / person_id + if kind == "scene": + target = person_dir / SCENE_REF_NAME + else: + target = person_dir / FACE_REF_NAME + if not target.exists(): + return None + data = target.read_bytes() + return data, "image/jpeg", target.name + + +def delete_person(person_id: str) -> bool: + person_dir = people_dir() / str(person_id or "").strip() + if not person_dir.exists() or not person_dir.is_dir(): + return False + shutil.rmtree(person_dir) + return True + + +def reset_people() -> int: + count = 0 + for person_dir in _person_dirs(): + shutil.rmtree(person_dir) + count += 1 + return count + + +def export_person_zip(person_id: str, out_path: Path) -> Optional[Path]: + person_id = str(person_id or "").strip() + if not person_id: + return None + person_dir = people_dir() / person_id + if not person_dir.exists(): + return None + out_path.parent.mkdir(parents=True, exist_ok=True) + with zipfile.ZipFile(out_path, "w", compression=zipfile.ZIP_DEFLATED) as zf: + for child in sorted(person_dir.rglob("*")): + if not child.is_file(): + continue + zf.write(child, arcname=str(child.relative_to(person_dir.parent))) + return out_path diff --git a/Core/settings.py b/Core/settings.py new file mode 100644 index 0000000..43ea36a --- /dev/null +++ b/Core/settings.py @@ -0,0 +1,1201 @@ +import copy +import json +import os +from pathlib import Path +from typing import Any, Dict + +PROJECT_ROOT = Path(__file__).resolve().parents[1] +APP_DATA_DEFAULT = PROJECT_ROOT / "Data" +CONFIG_JSON = APP_DATA_DEFAULT / "Settings" / "config.json" +LEGACY_CONFIG_JSONS = ( + APP_DATA_DEFAULT / "config.json", + PROJECT_ROOT / "Scripts" / "config.json", +) +LEGACY_CONFIG_JSON = LEGACY_CONFIG_JSONS[0] + +AUDIO_PROMPT_FILE_DEFAULTS: Dict[str, str] = { + "welcome_single": "welcome_single.wav", + "welcome_group": "welcome_group.wav", + "welcome_returning": "welcome_returning.wav", + "frame_single": "frame_single.wav", + "frame_group": "frame_group.wav", + "confirm_reminder": "confirm_reminder.wav", + "visitor_left": "visitor_left.wav", + "declined": "declined.wav", + "confirm_timeout": "confirm_timeout.wav", + "session_cancelled": "session_cancelled.wav", + "framing_timeout": "framing_timeout.wav", + "countdown_intro": "countdown_intro.wav", + "count_3": "count_3.wav", + "count_2": "count_2.wav", + "count_1": "count_1.wav", + "smile": "smile.wav", + "countdown_cancelled": "countdown_cancelled.wav", + "lost_from_frame": "lost_from_frame.wav", + "retake_recommended": "retake_recommended.wav", + "retake_yes": "retake_yes.wav", + "retake_limit": "retake_limit.wav", + "photo_saved_thanks": "photo_saved_thanks.wav", +} + +_FALLBACK: Dict[str, Any] = { + "paths": { + "data_dir": "AI_Photographer/Data/G1", + "app_data_dir": "AI_Photographer/Data", + "app_settings_dir": "AI_Photographer/Data/Settings", + "app_scripts_dir": "AI_Photographer/Data/Scripts", + "app_runtime_dir": "AI_Photographer/Data/Runtime", + "app_notes_dir": "AI_Photographer/Data/Notes", + "audio_prompts_dir": "AI_Photographer/Data/Audio", + "audio_prompt_records_file": "AI_Photographer/Data/Settings/audio_prompt_records.json", + "scripts_dir": "AI_Photographer/Scripts", + "web_dir": "AI_Photographer/Web", + "photos_dir": "AI_Photographer/photos/Captures", + "people_dir": "AI_Photographer/photos/people", + "samples_dir": "AI_Photographer/photos/samples", + "replay_recordings_dir": "AI_Photographer/Data/G1", + "replay_recorder_script": "", + "home_file": "arm_home.jsonl", + "photo_phrases_file": "AI_Photographer/Data/Scripts/photo_command_ai.txt", + "sanad_script_file": "AI_Photographer/Data/Scripts/sanad_script.txt", + "runtime_health_file": "AI_Photographer/Data/Runtime/runtime_health.json", + "autonomous_state_file": "AI_Photographer/Data/Runtime/autonomous_state.json", + "upload_db": "AI_Photographer/Data/Runtime/upload_db.json", + }, + "timing": { + "photo_total_sec": 10.0, + "photo_thanks_sec": 3.0, + "photo_delay_sec": 5.0, + "replay_capture_end_margin_sec": 0.25, + "loop_rate": 10.0, + "ai_query_interval": 1.0, + }, + "server": {"photo_server_port": 8080}, + "gemini": { + "api_key": "", + "mic_enabled": True, + "model": "models/gemini-2.5-flash-native-audio-preview-12-2025", + "voice_name": "Charon", + "system_prompt_fallback": ( + "You are Sanad (Bousandah), a friendly Emirati photographer assistant. " + "Speak in UAE dialect (Khaleeji). Be short, energetic, and helpful." + ), + }, + "upload": { + "method": "http", + "url": "", + "s3_bucket": "", + "s3_region": "", + "s3_key": "", + "s3_secret": "", + }, + "mode": { + "default_mode": "manual", + "current_mode": "manual", + }, + "replay": { + "active_file": "photo_G3.jsonl", + }, + "camera": { + "camera_index": 0, + "frame_width": 640, + "frame_height": 480, + "fps": 30, + "preferred_realsense_serial": "243622071722", + }, + "vision": { + "detection_backend": "yolo", + "yolo_runtime": "ultralytics", + "yolo_ultralytics_device": "cpu", + "person_yolo_onnx": "", + "face_yolo_onnx": "", + "input_size": 640, + "person_class_id": 0, + "person_score_thresh": 0.35, + "face_score_thresh": 0.35, + "nms_iou_thresh": 0.45, + "group_min_people": 3, + "group_link_distance_px": 220.0, + "yolo_strict_required": True, + "gemini_context_hz": 8.0, + "gemini_context_silent": True, + "idle_voice_listen_enabled": True, + "hard_target_lock_enabled": True, + "retake_prompt_enabled": True, + "autonomous_greeting_replay_enabled": True, + "autonomous_greeting_replay_file": "right_hand_up.jsonl", + "autonomous_capture_replay_enabled": True, + "retake_max_per_session": 1, + "framing_headroom_min_ratio": 0.06, + "framing_headroom_max_ratio": 0.25, + "framing_eye_line_min_ratio": 0.28, + "framing_eye_line_max_ratio": 0.48, + "framing_retake_score_threshold": 0.68, + "face_recognition_enabled": True, + "face_recognition_threshold": 0.88, + }, + "watchdog": { + "ws_initial_backoff_sec": 1.0, + "ws_max_backoff_sec": 20.0, + "component_restart_delay_sec": 1.0, + "camera_capture_retry_count": 2, + "camera_capture_retry_delay_sec": 0.8, + }, + "audio_prompts": { + "mode": "audio", + "fallback_to_gemini": True, + "files": copy.deepcopy(AUDIO_PROMPT_FILE_DEFAULTS), + }, +} + + +def _deep_merge(base: Dict[str, Any], override: Dict[str, Any]) -> Dict[str, Any]: + out = dict(base) + for k, v in override.items(): + if isinstance(v, dict) and isinstance(out.get(k), dict): + out[k] = _deep_merge(out[k], v) + else: + out[k] = v + return out + + +def _load_config() -> Dict[str, Any]: + for cfg_path in (CONFIG_JSON, *LEGACY_CONFIG_JSONS): + if not cfg_path.exists(): + continue + try: + raw = json.loads(cfg_path.read_text(encoding="utf-8")) + if isinstance(raw, dict): + return _deep_merge(_FALLBACK, raw) + except Exception: + pass + return _FALLBACK + + +_CFG = _load_config() + + +def _c(path: str, default: Any = None) -> Any: + cur: Any = _CFG + for part in path.split("."): + if not isinstance(cur, dict) or part not in cur: + return default + cur = cur[part] + return cur + + +def _env(name: str, default: Any, cast): + val = os.environ.get(name) + if val is None or val == "": + return default + try: + return cast(val) + except Exception: + return default + + +def _as_path(rel_or_abs: str) -> Path: + p = Path(str(rel_or_abs)).expanduser() + if not p.is_absolute(): + parts = p.parts + if parts and parts[0] == PROJECT_ROOT.name: + p = (PROJECT_ROOT.parent / p).resolve() + else: + p = (PROJECT_ROOT / p).resolve() + return p + + +# ================================================== +# PATHS +# ================================================== +DATA_DIR = _as_path(_c("paths.data_dir", "Data/G1")) +APP_DATA_DIR = _as_path(_c("paths.app_data_dir", "Data")) +APP_SETTINGS_DIR = _as_path(_c("paths.app_settings_dir", "Data/Settings")) +APP_SCRIPTS_DIR = _as_path(_c("paths.app_scripts_dir", "Data/Scripts")) +APP_RUNTIME_DIR = _as_path(_c("paths.app_runtime_dir", "Data/Runtime")) +APP_NOTES_DIR = _as_path(_c("paths.app_notes_dir", "Data/Notes")) +AUDIO_PROMPTS_DIR = _as_path( + _c("paths.audio_prompts_dir", "AI_Photographer/Data/Audio") +) +AUDIO_PROMPT_RECORDS_FILE = _as_path( + _c( + "paths.audio_prompt_records_file", + "AI_Photographer/Data/Settings/audio_prompt_records.json", + ) +) +SCRIPTS_DIR = _as_path(_c("paths.scripts_dir", "Scripts")) +WEB_DIR = _as_path(_c("paths.web_dir", "Web")) +PHOTOS_DIR = _as_path(_c("paths.photos_dir", "photos/Captures")) +PEOPLE_DIR = _as_path(_c("paths.people_dir", "photos/people")) +SAMPLES_DIR = _as_path(_c("paths.samples_dir", "photos/samples")) + +REPLAY_FILE = (DATA_DIR / str(_c("replay.active_file", "photo_G3.jsonl"))).resolve() +REPLAY_RECORDINGS_DIR = _as_path(_c("paths.replay_recordings_dir", "Data/G1")) +_REPLAY_RECORDER_SCRIPT_RAW = str(_c("paths.replay_recorder_script", "") or "").strip() +REPLAY_RECORDER_SCRIPT = _as_path(_REPLAY_RECORDER_SCRIPT_RAW) if _REPLAY_RECORDER_SCRIPT_RAW else "" +HOME_FILE = (DATA_DIR / str(_c("paths.home_file", "arm_home.jsonl"))).resolve() +PHOTO_PHRASES_FILE = _as_path(_c("paths.photo_phrases_file", "Data/Scripts/photo_command_ai.txt")) +SANAD_SCRIPT_FILE = _as_path(_c("paths.sanad_script_file", "Data/Scripts/sanad_script.txt")) +RUNTIME_HEALTH_FILE = _as_path(_c("paths.runtime_health_file", "Data/Runtime/runtime_health.json")) +AUTONOMOUS_STATE_FILE = _as_path(_c("paths.autonomous_state_file", "Data/Runtime/autonomous_state.json")) +UPLOAD_DB = _as_path(_c("paths.upload_db", "Data/Runtime/upload_db.json")) + +# ================================================== +# TIMING / PHOTOGRAPHER +# ================================================== +PHOTO_TOTAL_SEC = _env("PHOTO_TOTAL_SEC", float(_c("timing.photo_total_sec", 10.0)), float) +PHOTO_THANKS_SEC = _env("PHOTO_THANKS_SEC", float(_c("timing.photo_thanks_sec", 3.0)), float) +PHOTO_DELAY_SEC = _env("PHOTO_DELAY_SEC", float(_c("timing.photo_delay_sec", 5.0)), float) +REPLAY_CAPTURE_END_MARGIN_SEC = _env( + "REPLAY_CAPTURE_END_MARGIN_SEC", + float(_c("timing.replay_capture_end_margin_sec", 0.25)), + float, +) +LOOP_RATE = _env("LOOP_RATE", float(_c("timing.loop_rate", 10.0)), float) +AI_QUERY_INTERVAL = _env("AI_QUERY_INTERVAL", float(_c("timing.ai_query_interval", 1.0)), float) + +# ================================================== +# PHOTO SERVER +# ================================================== +PHOTO_SERVER_PORT = _env("PHOTO_SERVER_PORT", int(_c("server.photo_server_port", 8080)), int) + +# ================================================== +# GEMINI +# ================================================== +# Gemini key source: Data/Settings/config.json -> gemini.api_key +GEMINI_API_KEY = str(_c("gemini.api_key", "")).strip() +GEMINI_MODEL = _env("GEMINI_MODEL", str(_c("gemini.model", "models/gemini-2.5-flash-native-audio-preview-12-2025")).strip(), str).strip() +VOICE_NAME = _env("VOICE_NAME", str(_c("gemini.voice_name", "Charon")).strip() or "Charon", str).strip() or "Charon" +SYSTEM_PROMPT_FALLBACK = str(_c("gemini.system_prompt_fallback", _FALLBACK["gemini"]["system_prompt_fallback"])) + +# Keep alias for compatibility +MODEL = GEMINI_MODEL +URI = ( + "wss://generativelanguage.googleapis.com/ws/" + "google.ai.generativelanguage.v1alpha.GenerativeService.BidiGenerateContent" + f"?key={GEMINI_API_KEY}" +) + + +def validate_api_key(key: str) -> bool: + k = (key or "").strip() + if not k: + return False + if "your_" in k.lower() or "replace" in k.lower(): + return False + return len(k) >= 20 + + +def load_system_prompt() -> str: + try: + if SANAD_SCRIPT_FILE.exists(): + content = SANAD_SCRIPT_FILE.read_text(encoding="utf-8-sig").strip() + if content: + return content + except Exception: + pass + return SYSTEM_PROMPT_FALLBACK + + +def read_gemini_mic_enabled() -> bool: + raw = _read_config_json_raw() + gemini_cfg = raw.get("gemini") + if not isinstance(gemini_cfg, dict): + gemini_cfg = {} + return _coerce_bool(gemini_cfg.get("mic_enabled", _FALLBACK["gemini"]["mic_enabled"]), True) + + +def write_gemini_mic_enabled(enabled: Any) -> bool: + raw = _read_config_json_raw() + gemini_cfg = raw.get("gemini") + if not isinstance(gemini_cfg, dict): + gemini_cfg = {} + gemini_cfg["mic_enabled"] = _coerce_bool(enabled, bool(_FALLBACK["gemini"]["mic_enabled"])) + raw["gemini"] = gemini_cfg + _write_config_json_raw(raw) + _refresh_cached_cfg(raw) + return bool(gemini_cfg["mic_enabled"]) + + +def read_camera_preferred_realsense_serial() -> str: + raw = _read_config_json_raw() + camera_cfg = raw.get("camera") + if not isinstance(camera_cfg, dict): + camera_cfg = {} + return str(camera_cfg.get("preferred_realsense_serial", _FALLBACK["camera"]["preferred_realsense_serial"]) or "").strip() + + +def write_camera_preferred_realsense_serial(serial: Any) -> str: + raw = _read_config_json_raw() + camera_cfg = raw.get("camera") + if not isinstance(camera_cfg, dict): + camera_cfg = {} + camera_cfg["preferred_realsense_serial"] = str(serial or "").strip() + raw["camera"] = camera_cfg + _write_config_json_raw(raw) + _refresh_cached_cfg(raw) + return str(camera_cfg["preferred_realsense_serial"]) + + +def resolve_replay_path(path_value: Any) -> Path: + p = Path(str(path_value or "").strip()).expanduser() + if not p.is_absolute(): + p = (DATA_DIR / p).resolve() + return p + + +def read_selected_replay_name() -> str: + raw = _read_config_json_raw() + raw = _ensure_replay_block(raw) + replay_cfg = raw.get("replay", {}) + value = str(replay_cfg.get("active_file", "") or "").strip() + if value: + return value.replace("\\", "/").lstrip("/") + try: + return str(REPLAY_FILE.resolve().relative_to(DATA_DIR)).replace("\\", "/") + except Exception: + return REPLAY_FILE.name + + +def read_selected_replay_path() -> Path: + return resolve_replay_path(read_selected_replay_name()) + + +def write_selected_replay_name(name: Any) -> str: + global REPLAY_FILE + clean = str(name or "").strip().replace("\\", "/").lstrip("/") + raw = _read_config_json_raw() + raw = _ensure_replay_block(raw) + replay_cfg = raw.get("replay", {}) + replay_cfg["active_file"] = clean + raw["replay"] = replay_cfg + _write_config_json_raw(raw) + _refresh_cached_cfg(raw) + try: + REPLAY_FILE = resolve_replay_path(clean) + except Exception: + pass + return clean + + +# ================================================== +# UPLOAD / CLOUD +# ================================================== +UPLOAD_METHOD = _env("UPLOAD_METHOD", str(_c("upload.method", "http")).strip(), str).strip() +UPLOAD_URL = _env("UPLOAD_URL", str(_c("upload.url", "")).strip(), str).strip() +UPLOAD_S3_BUCKET = _env("UPLOAD_S3_BUCKET", str(_c("upload.s3_bucket", "")).strip(), str).strip() +UPLOAD_S3_REGION = _env("UPLOAD_S3_REGION", str(_c("upload.s3_region", "")).strip(), str).strip() +UPLOAD_S3_KEY = _env("UPLOAD_S3_KEY", str(_c("upload.s3_key", "")).strip(), str).strip() +UPLOAD_S3_SECRET = _env("UPLOAD_S3_SECRET", str(_c("upload.s3_secret", "")).strip(), str).strip() + +# ================================================== +# MODE / CONTROL +# ================================================== +DEFAULT_MODE = _env("DEFAULT_MODE", str(_c("mode.default_mode", "manual")).strip(), str).strip() or "manual" +if DEFAULT_MODE == "command": + DEFAULT_MODE = "ai" +if DEFAULT_MODE not in ("manual", "ai"): + DEFAULT_MODE = "manual" + +try: + UPLOAD_DB.parent.mkdir(parents=True, exist_ok=True) +except Exception: + pass + +for _dir in ( + APP_DATA_DIR, + APP_SETTINGS_DIR, + APP_SCRIPTS_DIR, + APP_RUNTIME_DIR, + APP_NOTES_DIR, + AUDIO_PROMPTS_DIR, + AUDIO_PROMPT_RECORDS_FILE.parent, + PHOTOS_DIR, + PEOPLE_DIR, + SAMPLES_DIR, + REPLAY_RECORDINGS_DIR, +): + try: + _dir.mkdir(parents=True, exist_ok=True) + except Exception: + pass + + +def _read_config_json_raw() -> Dict[str, Any]: + for cfg_path in (CONFIG_JSON, *LEGACY_CONFIG_JSONS): + try: + if cfg_path.exists(): + raw = json.loads(cfg_path.read_text(encoding="utf-8")) + if isinstance(raw, dict): + return raw + except Exception: + pass + return {} + + +def _write_config_json_raw(raw: Dict[str, Any]) -> None: + CONFIG_JSON.parent.mkdir(parents=True, exist_ok=True) + CONFIG_JSON.write_text(json.dumps(raw, ensure_ascii=False, indent=2), encoding="utf-8") + + +def _coerce_mode(value: Any) -> str: + m = str(value or "").strip().lower() + if m == "command": + return "ai" + if m not in ("manual", "ai"): + return "manual" + return m + + +def _coerce_bool(value: Any, default: bool = False) -> bool: + if isinstance(value, bool): + return value + if isinstance(value, (int, float)): + return bool(value) + if isinstance(value, str): + return value.strip().lower() in ("1", "true", "yes", "on", "y") + return bool(default) + + +def _coerce_detection_backend(value: Any) -> str: + v = str(value or "").strip().lower() + if v in ("yolo", "normal"): + return v + return "yolo" + + +def _coerce_audio_prompt_mode(value: Any) -> str: + v = str(value or "").strip().lower() + if v in ("audio", "gemini"): + return v + return "audio" + + +def _coerce_yolo_runtime(value: Any) -> str: + v = str(value or "").strip().lower() + if v in ("ultralytics", "opencv"): + return v + return "ultralytics" + + +def _coerce_int(value: Any, default: int, min_v: int | None = None, max_v: int | None = None) -> int: + try: + out = int(value) + except Exception: + out = int(default) + if min_v is not None: + out = max(min_v, out) + if max_v is not None: + out = min(max_v, out) + return out + + +def _coerce_float(value: Any, default: float, min_v: float | None = None, max_v: float | None = None) -> float: + try: + out = float(value) + except Exception: + out = float(default) + if min_v is not None: + out = max(min_v, out) + if max_v is not None: + out = min(max_v, out) + return out + + +def _ensure_mode_block(raw: Dict[str, Any]) -> Dict[str, Any]: + if not isinstance(raw, dict) or not raw: + raw = copy.deepcopy(_FALLBACK) + mode_cfg = raw.get("mode") + if not isinstance(mode_cfg, dict): + mode_cfg = {} + default_mode = _coerce_mode(mode_cfg.get("default_mode", DEFAULT_MODE)) + current_mode = _coerce_mode(mode_cfg.get("current_mode", default_mode)) + mode_cfg["default_mode"] = default_mode + mode_cfg["current_mode"] = current_mode + raw["mode"] = mode_cfg + return raw + + +def _ensure_replay_block(raw: Dict[str, Any]) -> Dict[str, Any]: + if not isinstance(raw, dict) or not raw: + raw = copy.deepcopy(_FALLBACK) + replay_cfg = raw.get("replay") + if not isinstance(replay_cfg, dict): + replay_cfg = {} + active_file = str(replay_cfg.get("active_file", _FALLBACK["replay"]["active_file"]) or "").strip() + replay_cfg["active_file"] = active_file or str(_FALLBACK["replay"]["active_file"]) + raw["replay"] = replay_cfg + return raw + + +def _ensure_vision_block(raw: Dict[str, Any]) -> Dict[str, Any]: + if not isinstance(raw, dict) or not raw: + raw = copy.deepcopy(_FALLBACK) + vision_cfg = raw.get("vision") + if not isinstance(vision_cfg, dict): + vision_cfg = {} + vision_cfg["detection_backend"] = _coerce_detection_backend( + vision_cfg.get("detection_backend", _FALLBACK["vision"]["detection_backend"]) + ) + vision_cfg["yolo_runtime"] = _coerce_yolo_runtime( + vision_cfg.get("yolo_runtime", _FALLBACK["vision"]["yolo_runtime"]) + ) + dev = str(vision_cfg.get("yolo_ultralytics_device", _FALLBACK["vision"]["yolo_ultralytics_device"]) or "").strip() + vision_cfg["yolo_ultralytics_device"] = dev or "cpu" + try: + group_min = int(vision_cfg.get("group_min_people", _FALLBACK["vision"]["group_min_people"])) + except Exception: + group_min = int(_FALLBACK["vision"]["group_min_people"]) + vision_cfg["group_min_people"] = max(2, group_min) + + vision_cfg["yolo_strict_required"] = _coerce_bool( + vision_cfg.get("yolo_strict_required", _FALLBACK["vision"]["yolo_strict_required"]), + bool(_FALLBACK["vision"]["yolo_strict_required"]), + ) + + try: + hz = float(vision_cfg.get("gemini_context_hz", _FALLBACK["vision"]["gemini_context_hz"])) + except Exception: + hz = float(_FALLBACK["vision"]["gemini_context_hz"]) + vision_cfg["gemini_context_hz"] = max(0.5, min(30.0, hz)) + + vision_cfg["gemini_context_silent"] = _coerce_bool( + vision_cfg.get("gemini_context_silent", _FALLBACK["vision"]["gemini_context_silent"]), + bool(_FALLBACK["vision"]["gemini_context_silent"]), + ) + vision_cfg["idle_voice_listen_enabled"] = _coerce_bool( + vision_cfg.get("idle_voice_listen_enabled", _FALLBACK["vision"]["idle_voice_listen_enabled"]), + bool(_FALLBACK["vision"]["idle_voice_listen_enabled"]), + ) + + vision_cfg["hard_target_lock_enabled"] = _coerce_bool( + vision_cfg.get("hard_target_lock_enabled", _FALLBACK["vision"]["hard_target_lock_enabled"]), + bool(_FALLBACK["vision"]["hard_target_lock_enabled"]), + ) + vision_cfg["retake_prompt_enabled"] = _coerce_bool( + vision_cfg.get("retake_prompt_enabled", _FALLBACK["vision"]["retake_prompt_enabled"]), + bool(_FALLBACK["vision"]["retake_prompt_enabled"]), + ) + vision_cfg["autonomous_greeting_replay_enabled"] = _coerce_bool( + vision_cfg.get("autonomous_greeting_replay_enabled", _FALLBACK["vision"]["autonomous_greeting_replay_enabled"]), + bool(_FALLBACK["vision"]["autonomous_greeting_replay_enabled"]), + ) + greet_replay_file = str( + vision_cfg.get("autonomous_greeting_replay_file", _FALLBACK["vision"]["autonomous_greeting_replay_file"]) or "" + ).strip() + vision_cfg["autonomous_greeting_replay_file"] = ( + greet_replay_file or str(_FALLBACK["vision"]["autonomous_greeting_replay_file"]) + ) + vision_cfg["autonomous_capture_replay_enabled"] = _coerce_bool( + vision_cfg.get("autonomous_capture_replay_enabled", _FALLBACK["vision"]["autonomous_capture_replay_enabled"]), + bool(_FALLBACK["vision"]["autonomous_capture_replay_enabled"]), + ) + vision_cfg["retake_max_per_session"] = _coerce_int( + vision_cfg.get("retake_max_per_session", _FALLBACK["vision"]["retake_max_per_session"]), + int(_FALLBACK["vision"]["retake_max_per_session"]), + min_v=0, + max_v=5, + ) + vision_cfg["framing_headroom_min_ratio"] = _coerce_float( + vision_cfg.get("framing_headroom_min_ratio", _FALLBACK["vision"]["framing_headroom_min_ratio"]), + float(_FALLBACK["vision"]["framing_headroom_min_ratio"]), + min_v=0.0, + max_v=0.8, + ) + vision_cfg["framing_headroom_max_ratio"] = _coerce_float( + vision_cfg.get("framing_headroom_max_ratio", _FALLBACK["vision"]["framing_headroom_max_ratio"]), + float(_FALLBACK["vision"]["framing_headroom_max_ratio"]), + min_v=0.0, + max_v=0.95, + ) + if vision_cfg["framing_headroom_max_ratio"] <= vision_cfg["framing_headroom_min_ratio"]: + vision_cfg["framing_headroom_max_ratio"] = min(0.95, vision_cfg["framing_headroom_min_ratio"] + 0.05) + + vision_cfg["framing_eye_line_min_ratio"] = _coerce_float( + vision_cfg.get("framing_eye_line_min_ratio", _FALLBACK["vision"]["framing_eye_line_min_ratio"]), + float(_FALLBACK["vision"]["framing_eye_line_min_ratio"]), + min_v=0.0, + max_v=0.9, + ) + vision_cfg["framing_eye_line_max_ratio"] = _coerce_float( + vision_cfg.get("framing_eye_line_max_ratio", _FALLBACK["vision"]["framing_eye_line_max_ratio"]), + float(_FALLBACK["vision"]["framing_eye_line_max_ratio"]), + min_v=0.05, + max_v=1.0, + ) + if vision_cfg["framing_eye_line_max_ratio"] <= vision_cfg["framing_eye_line_min_ratio"]: + vision_cfg["framing_eye_line_max_ratio"] = min(1.0, vision_cfg["framing_eye_line_min_ratio"] + 0.05) + + vision_cfg["framing_retake_score_threshold"] = _coerce_float( + vision_cfg.get("framing_retake_score_threshold", _FALLBACK["vision"]["framing_retake_score_threshold"]), + float(_FALLBACK["vision"]["framing_retake_score_threshold"]), + min_v=0.0, + max_v=1.0, + ) + vision_cfg["face_recognition_enabled"] = _coerce_bool( + vision_cfg.get("face_recognition_enabled", _FALLBACK["vision"]["face_recognition_enabled"]), + bool(_FALLBACK["vision"]["face_recognition_enabled"]), + ) + vision_cfg["face_recognition_threshold"] = _coerce_float( + vision_cfg.get("face_recognition_threshold", _FALLBACK["vision"]["face_recognition_threshold"]), + float(_FALLBACK["vision"]["face_recognition_threshold"]), + min_v=0.5, + max_v=0.995, + ) + raw["vision"] = vision_cfg + return raw + + +def _ensure_watchdog_block(raw: Dict[str, Any]) -> Dict[str, Any]: + if not isinstance(raw, dict) or not raw: + raw = copy.deepcopy(_FALLBACK) + wd_cfg = raw.get("watchdog") + if not isinstance(wd_cfg, dict): + wd_cfg = {} + + wd_cfg["ws_initial_backoff_sec"] = _coerce_float( + wd_cfg.get("ws_initial_backoff_sec", _FALLBACK["watchdog"]["ws_initial_backoff_sec"]), + float(_FALLBACK["watchdog"]["ws_initial_backoff_sec"]), + min_v=0.1, + max_v=60.0, + ) + wd_cfg["ws_max_backoff_sec"] = _coerce_float( + wd_cfg.get("ws_max_backoff_sec", _FALLBACK["watchdog"]["ws_max_backoff_sec"]), + float(_FALLBACK["watchdog"]["ws_max_backoff_sec"]), + min_v=0.5, + max_v=300.0, + ) + if wd_cfg["ws_max_backoff_sec"] < wd_cfg["ws_initial_backoff_sec"]: + wd_cfg["ws_max_backoff_sec"] = wd_cfg["ws_initial_backoff_sec"] + + wd_cfg["component_restart_delay_sec"] = _coerce_float( + wd_cfg.get("component_restart_delay_sec", _FALLBACK["watchdog"]["component_restart_delay_sec"]), + float(_FALLBACK["watchdog"]["component_restart_delay_sec"]), + min_v=0.1, + max_v=20.0, + ) + wd_cfg["camera_capture_retry_count"] = _coerce_int( + wd_cfg.get("camera_capture_retry_count", _FALLBACK["watchdog"]["camera_capture_retry_count"]), + int(_FALLBACK["watchdog"]["camera_capture_retry_count"]), + min_v=0, + max_v=10, + ) + wd_cfg["camera_capture_retry_delay_sec"] = _coerce_float( + wd_cfg.get("camera_capture_retry_delay_sec", _FALLBACK["watchdog"]["camera_capture_retry_delay_sec"]), + float(_FALLBACK["watchdog"]["camera_capture_retry_delay_sec"]), + min_v=0.0, + max_v=30.0, + ) + + raw["watchdog"] = wd_cfg + return raw + + +def _ensure_audio_prompts_block(raw: Dict[str, Any]) -> Dict[str, Any]: + if not isinstance(raw, dict) or not raw: + raw = copy.deepcopy(_FALLBACK) + prompt_cfg = raw.get("audio_prompts") + if not isinstance(prompt_cfg, dict): + prompt_cfg = {} + + prompt_cfg["mode"] = _coerce_audio_prompt_mode( + prompt_cfg.get("mode", _FALLBACK["audio_prompts"]["mode"]) + ) + + prompt_cfg["fallback_to_gemini"] = _coerce_bool( + prompt_cfg.get("fallback_to_gemini", _FALLBACK["audio_prompts"]["fallback_to_gemini"]), + bool(_FALLBACK["audio_prompts"]["fallback_to_gemini"]), + ) + + files_cfg = prompt_cfg.get("files") + if not isinstance(files_cfg, dict): + files_cfg = {} + + normalized_files: Dict[str, str] = {} + for key, default_name in AUDIO_PROMPT_FILE_DEFAULTS.items(): + clean = str(files_cfg.get(key, default_name) or "").strip().replace("\\", "/").lstrip("/") + normalized_files[key] = clean or default_name + + prompt_cfg["files"] = normalized_files + raw["audio_prompts"] = prompt_cfg + return raw + + +def _refresh_cached_cfg(raw: Dict[str, Any]) -> None: + global _CFG + _CFG = _deep_merge(_FALLBACK, raw if isinstance(raw, dict) else {}) + + +def read_runtime_mode() -> str: + raw = _read_config_json_raw() + raw = _ensure_mode_block(raw) + mode_cfg = raw.get("mode", {}) + return _coerce_mode(mode_cfg.get("current_mode", mode_cfg.get("default_mode", DEFAULT_MODE))) + + +def write_runtime_mode(mode: str) -> str: + raw = _read_config_json_raw() + raw = _ensure_mode_block(raw) + mode_cfg = raw.get("mode", {}) + mode_cfg["current_mode"] = _coerce_mode(mode) + raw["mode"] = mode_cfg + _write_config_json_raw(raw) + _refresh_cached_cfg(raw) + return mode_cfg["current_mode"] + + +def read_vision_detector_backend() -> str: + raw = _read_config_json_raw() + raw = _ensure_vision_block(raw) + vision_cfg = raw.get("vision", {}) + return _coerce_detection_backend(vision_cfg.get("detection_backend", "yolo")) + + +def write_vision_detector_backend(backend: str) -> str: + raw = _read_config_json_raw() + raw = _ensure_vision_block(raw) + vision_cfg = raw.get("vision", {}) + vision_cfg["detection_backend"] = _coerce_detection_backend(backend) + raw["vision"] = vision_cfg + _write_config_json_raw(raw) + _refresh_cached_cfg(raw) + return str(vision_cfg["detection_backend"]) + + +def read_vision_yolo_runtime() -> str: + raw = _read_config_json_raw() + raw = _ensure_vision_block(raw) + vision_cfg = raw.get("vision", {}) + return _coerce_yolo_runtime(vision_cfg.get("yolo_runtime", _FALLBACK["vision"]["yolo_runtime"])) + + +def read_vision_yolo_ultralytics_device() -> str: + raw = _read_config_json_raw() + raw = _ensure_vision_block(raw) + vision_cfg = raw.get("vision", {}) + dev = str(vision_cfg.get("yolo_ultralytics_device", _FALLBACK["vision"]["yolo_ultralytics_device"]) or "").strip() + return dev or "cpu" + + +def read_vision_yolo_strict_required() -> bool: + raw = _read_config_json_raw() + raw = _ensure_vision_block(raw) + vision_cfg = raw.get("vision", {}) + return _coerce_bool(vision_cfg.get("yolo_strict_required", _FALLBACK["vision"]["yolo_strict_required"]), True) + + +def read_vision_gemini_context_hz() -> float: + raw = _read_config_json_raw() + raw = _ensure_vision_block(raw) + vision_cfg = raw.get("vision", {}) + try: + hz = float(vision_cfg.get("gemini_context_hz", _FALLBACK["vision"]["gemini_context_hz"])) + except Exception: + hz = float(_FALLBACK["vision"]["gemini_context_hz"]) + return max(0.5, min(30.0, hz)) + + +def read_vision_gemini_context_silent() -> bool: + raw = _read_config_json_raw() + raw = _ensure_vision_block(raw) + vision_cfg = raw.get("vision", {}) + return _coerce_bool(vision_cfg.get("gemini_context_silent", _FALLBACK["vision"]["gemini_context_silent"]), True) + + +def read_vision_idle_voice_listen_enabled() -> bool: + raw = _read_config_json_raw() + raw = _ensure_vision_block(raw) + vision_cfg = raw.get("vision", {}) + return _coerce_bool( + vision_cfg.get("idle_voice_listen_enabled", _FALLBACK["vision"]["idle_voice_listen_enabled"]), + True, + ) + + +def _write_vision_cfg_value(key: str, value: Any, *, bool_field: bool = False) -> Any: + raw = _read_config_json_raw() + raw = _ensure_vision_block(raw) + raw = _ensure_watchdog_block(raw) + vision_cfg = raw.get("vision", {}) + if bool_field: + vision_cfg[key] = _coerce_bool(value, bool(_FALLBACK["vision"].get(key, False))) + else: + vision_cfg[key] = value + raw["vision"] = vision_cfg + raw = _ensure_vision_block(raw) + _write_config_json_raw(raw) + _refresh_cached_cfg(raw) + return raw.get("vision", {}).get(key) + + +def read_vision_hard_target_lock_enabled() -> bool: + raw = _read_config_json_raw() + raw = _ensure_vision_block(raw) + return _coerce_bool(raw.get("vision", {}).get("hard_target_lock_enabled", True), True) + + +def write_vision_hard_target_lock_enabled(enabled: Any) -> bool: + return bool(_write_vision_cfg_value("hard_target_lock_enabled", enabled, bool_field=True)) + + +def read_vision_retake_prompt_enabled() -> bool: + raw = _read_config_json_raw() + raw = _ensure_vision_block(raw) + return _coerce_bool(raw.get("vision", {}).get("retake_prompt_enabled", True), True) + + +def write_vision_retake_prompt_enabled(enabled: Any) -> bool: + return bool(_write_vision_cfg_value("retake_prompt_enabled", enabled, bool_field=True)) + + +def read_vision_autonomous_greeting_replay_enabled() -> bool: + raw = _read_config_json_raw() + raw = _ensure_vision_block(raw) + return _coerce_bool( + raw.get("vision", {}).get( + "autonomous_greeting_replay_enabled", + _FALLBACK["vision"]["autonomous_greeting_replay_enabled"], + ), + bool(_FALLBACK["vision"]["autonomous_greeting_replay_enabled"]), + ) + + +def read_vision_autonomous_greeting_replay_file() -> str: + raw = _read_config_json_raw() + raw = _ensure_vision_block(raw) + val = str( + raw.get("vision", {}).get( + "autonomous_greeting_replay_file", + _FALLBACK["vision"]["autonomous_greeting_replay_file"], + ) + or "" + ).strip() + return val or str(_FALLBACK["vision"]["autonomous_greeting_replay_file"]) + + +def read_vision_autonomous_capture_replay_enabled() -> bool: + raw = _read_config_json_raw() + raw = _ensure_vision_block(raw) + return _coerce_bool( + raw.get("vision", {}).get( + "autonomous_capture_replay_enabled", + _FALLBACK["vision"]["autonomous_capture_replay_enabled"], + ), + bool(_FALLBACK["vision"]["autonomous_capture_replay_enabled"]), + ) + + +def write_vision_autonomous_greeting_replay_enabled(enabled: Any) -> bool: + return bool(_write_vision_cfg_value("autonomous_greeting_replay_enabled", enabled, bool_field=True)) + + +def write_vision_autonomous_greeting_replay_file(filename: Any) -> str: + raw = _read_config_json_raw() + raw = _ensure_vision_block(raw) + vision_cfg = raw.get("vision", {}) + cleaned = str(filename or "").strip().replace("\\", "/").lstrip("/") + vision_cfg["autonomous_greeting_replay_file"] = cleaned or str( + _FALLBACK["vision"]["autonomous_greeting_replay_file"] + ) + raw["vision"] = vision_cfg + raw = _ensure_vision_block(raw) + _write_config_json_raw(raw) + _refresh_cached_cfg(raw) + return str(raw.get("vision", {}).get("autonomous_greeting_replay_file", "")) + + +def write_vision_autonomous_capture_replay_enabled(enabled: Any) -> bool: + return bool(_write_vision_cfg_value("autonomous_capture_replay_enabled", enabled, bool_field=True)) + + +def read_vision_retake_max_per_session() -> int: + raw = _read_config_json_raw() + raw = _ensure_vision_block(raw) + v = raw.get("vision", {}).get("retake_max_per_session", _FALLBACK["vision"]["retake_max_per_session"]) + return _coerce_int(v, int(_FALLBACK["vision"]["retake_max_per_session"]), min_v=0, max_v=5) + + +def read_vision_framing_headroom_min_ratio() -> float: + raw = _read_config_json_raw() + raw = _ensure_vision_block(raw) + v = raw.get("vision", {}).get("framing_headroom_min_ratio", _FALLBACK["vision"]["framing_headroom_min_ratio"]) + return _coerce_float(v, float(_FALLBACK["vision"]["framing_headroom_min_ratio"]), min_v=0.0, max_v=0.8) + + +def read_vision_framing_headroom_max_ratio() -> float: + raw = _read_config_json_raw() + raw = _ensure_vision_block(raw) + v = raw.get("vision", {}).get("framing_headroom_max_ratio", _FALLBACK["vision"]["framing_headroom_max_ratio"]) + return _coerce_float(v, float(_FALLBACK["vision"]["framing_headroom_max_ratio"]), min_v=0.0, max_v=0.95) + + +def read_vision_framing_eye_line_min_ratio() -> float: + raw = _read_config_json_raw() + raw = _ensure_vision_block(raw) + v = raw.get("vision", {}).get("framing_eye_line_min_ratio", _FALLBACK["vision"]["framing_eye_line_min_ratio"]) + return _coerce_float(v, float(_FALLBACK["vision"]["framing_eye_line_min_ratio"]), min_v=0.0, max_v=0.9) + + +def read_vision_framing_eye_line_max_ratio() -> float: + raw = _read_config_json_raw() + raw = _ensure_vision_block(raw) + v = raw.get("vision", {}).get("framing_eye_line_max_ratio", _FALLBACK["vision"]["framing_eye_line_max_ratio"]) + return _coerce_float(v, float(_FALLBACK["vision"]["framing_eye_line_max_ratio"]), min_v=0.05, max_v=1.0) + + +def read_vision_framing_retake_score_threshold() -> float: + raw = _read_config_json_raw() + raw = _ensure_vision_block(raw) + v = raw.get("vision", {}).get( + "framing_retake_score_threshold", + _FALLBACK["vision"]["framing_retake_score_threshold"], + ) + return _coerce_float(v, float(_FALLBACK["vision"]["framing_retake_score_threshold"]), min_v=0.0, max_v=1.0) + + +def read_vision_face_recognition_enabled() -> bool: + raw = _read_config_json_raw() + raw = _ensure_vision_block(raw) + return _coerce_bool( + raw.get("vision", {}).get("face_recognition_enabled", _FALLBACK["vision"]["face_recognition_enabled"]), + bool(_FALLBACK["vision"]["face_recognition_enabled"]), + ) + + +def write_vision_face_recognition_enabled(enabled: Any) -> bool: + return bool(_write_vision_cfg_value("face_recognition_enabled", enabled, bool_field=True)) + + +def read_vision_face_recognition_threshold() -> float: + raw = _read_config_json_raw() + raw = _ensure_vision_block(raw) + v = raw.get("vision", {}).get("face_recognition_threshold", _FALLBACK["vision"]["face_recognition_threshold"]) + return _coerce_float(v, float(_FALLBACK["vision"]["face_recognition_threshold"]), min_v=0.5, max_v=0.995) + + +def write_vision_face_recognition_threshold(value: Any) -> float: + raw = _read_config_json_raw() + raw = _ensure_vision_block(raw) + vision_cfg = raw.get("vision", {}) + vision_cfg["face_recognition_threshold"] = _coerce_float( + value, + float(_FALLBACK["vision"]["face_recognition_threshold"]), + min_v=0.5, + max_v=0.995, + ) + raw["vision"] = vision_cfg + raw = _ensure_vision_block(raw) + _write_config_json_raw(raw) + _refresh_cached_cfg(raw) + return float(raw.get("vision", {}).get("face_recognition_threshold", _FALLBACK["vision"]["face_recognition_threshold"])) + + +def read_watchdog_ws_initial_backoff_sec() -> float: + raw = _read_config_json_raw() + raw = _ensure_watchdog_block(raw) + wd = raw.get("watchdog", {}) + return _coerce_float( + wd.get("ws_initial_backoff_sec", _FALLBACK["watchdog"]["ws_initial_backoff_sec"]), + float(_FALLBACK["watchdog"]["ws_initial_backoff_sec"]), + min_v=0.1, + max_v=60.0, + ) + + +def read_watchdog_ws_max_backoff_sec() -> float: + raw = _read_config_json_raw() + raw = _ensure_watchdog_block(raw) + wd = raw.get("watchdog", {}) + return _coerce_float( + wd.get("ws_max_backoff_sec", _FALLBACK["watchdog"]["ws_max_backoff_sec"]), + float(_FALLBACK["watchdog"]["ws_max_backoff_sec"]), + min_v=0.5, + max_v=300.0, + ) + + +def read_watchdog_component_restart_delay_sec() -> float: + raw = _read_config_json_raw() + raw = _ensure_watchdog_block(raw) + wd = raw.get("watchdog", {}) + return _coerce_float( + wd.get("component_restart_delay_sec", _FALLBACK["watchdog"]["component_restart_delay_sec"]), + float(_FALLBACK["watchdog"]["component_restart_delay_sec"]), + min_v=0.1, + max_v=20.0, + ) + + +def read_watchdog_camera_capture_retry_count() -> int: + raw = _read_config_json_raw() + raw = _ensure_watchdog_block(raw) + wd = raw.get("watchdog", {}) + return _coerce_int( + wd.get("camera_capture_retry_count", _FALLBACK["watchdog"]["camera_capture_retry_count"]), + int(_FALLBACK["watchdog"]["camera_capture_retry_count"]), + min_v=0, + max_v=10, + ) + + +def read_watchdog_camera_capture_retry_delay_sec() -> float: + raw = _read_config_json_raw() + raw = _ensure_watchdog_block(raw) + wd = raw.get("watchdog", {}) + return _coerce_float( + wd.get("camera_capture_retry_delay_sec", _FALLBACK["watchdog"]["camera_capture_retry_delay_sec"]), + float(_FALLBACK["watchdog"]["camera_capture_retry_delay_sec"]), + min_v=0.0, + max_v=30.0, + ) + + +def read_audio_prompts_fallback_to_gemini() -> bool: + raw = _read_config_json_raw() + raw = _ensure_audio_prompts_block(raw) + prompt_cfg = raw.get("audio_prompts", {}) + return _coerce_bool(prompt_cfg.get("fallback_to_gemini", True), True) + + +def read_audio_prompt_mode() -> str: + raw = _read_config_json_raw() + raw = _ensure_audio_prompts_block(raw) + prompt_cfg = raw.get("audio_prompts", {}) + return _coerce_audio_prompt_mode(prompt_cfg.get("mode", "audio")) + + +def write_audio_prompt_mode(mode: Any) -> str: + raw = _read_config_json_raw() + raw = _ensure_audio_prompts_block(raw) + prompt_cfg = raw.get("audio_prompts", {}) + prompt_cfg["mode"] = _coerce_audio_prompt_mode(mode) + raw["audio_prompts"] = prompt_cfg + _write_config_json_raw(raw) + _refresh_cached_cfg(raw) + return str(prompt_cfg["mode"]) + + +def write_audio_prompts_fallback_to_gemini(enabled: Any) -> bool: + raw = _read_config_json_raw() + raw = _ensure_audio_prompts_block(raw) + prompt_cfg = raw.get("audio_prompts", {}) + prompt_cfg["fallback_to_gemini"] = _coerce_bool(enabled, True) + raw["audio_prompts"] = prompt_cfg + _write_config_json_raw(raw) + _refresh_cached_cfg(raw) + return bool(prompt_cfg["fallback_to_gemini"]) + + +def read_audio_prompt_files() -> Dict[str, str]: + raw = _read_config_json_raw() + raw = _ensure_audio_prompts_block(raw) + prompt_cfg = raw.get("audio_prompts", {}) + files_cfg = prompt_cfg.get("files", {}) + out: Dict[str, str] = {} + for key, default_name in AUDIO_PROMPT_FILE_DEFAULTS.items(): + clean = str(files_cfg.get(key, default_name) or "").strip().replace("\\", "/").lstrip("/") + out[key] = clean or default_name + return out + + +def read_audio_prompt_filename(key: str) -> str: + key = str(key or "").strip() + if key not in AUDIO_PROMPT_FILE_DEFAULTS: + raise KeyError(f"unknown audio prompt key: {key}") + return str(read_audio_prompt_files().get(key, AUDIO_PROMPT_FILE_DEFAULTS[key])) + + +def write_audio_prompt_filename(key: str, filename: Any) -> str: + key = str(key or "").strip() + if key not in AUDIO_PROMPT_FILE_DEFAULTS: + raise KeyError(f"unknown audio prompt key: {key}") + raw = _read_config_json_raw() + raw = _ensure_audio_prompts_block(raw) + prompt_cfg = raw.get("audio_prompts", {}) + files_cfg = prompt_cfg.get("files", {}) + clean = str(filename or "").strip().replace("\\", "/").lstrip("/") + files_cfg[key] = clean or AUDIO_PROMPT_FILE_DEFAULTS[key] + prompt_cfg["files"] = files_cfg + raw["audio_prompts"] = prompt_cfg + _write_config_json_raw(raw) + _refresh_cached_cfg(raw) + return str(files_cfg[key]) + + +# Ensure runtime mode keys exist in config.json. +try: + _raw_cfg = _read_config_json_raw() + _normalized = _ensure_mode_block(_raw_cfg) + _normalized = _ensure_vision_block(_normalized) + _normalized = _ensure_watchdog_block(_normalized) + _normalized = _ensure_audio_prompts_block(_normalized) + if _normalized != _raw_cfg or not CONFIG_JSON.exists(): + _write_config_json_raw(_normalized) + _refresh_cached_cfg(_normalized) +except Exception: + pass + +# CAMERA +# ================================================== +CAMERA_INDEX = _env("CAMERA_INDEX", int(_c("camera.camera_index", 0)), int) +FRAME_WIDTH = _env("FRAME_WIDTH", int(_c("camera.frame_width", 640)), int) +FRAME_HEIGHT = _env("FRAME_HEIGHT", int(_c("camera.frame_height", 480)), int) +FPS = _env("FPS", int(_c("camera.fps", 30)), int) + +# ================================================== +# VISION / DETECTOR +# ================================================== +VISION_DETECTION_BACKEND = _coerce_detection_backend(_c("vision.detection_backend", "yolo")) +VISION_YOLO_RUNTIME = _coerce_yolo_runtime(_c("vision.yolo_runtime", "ultralytics")) +VISION_YOLO_ULTRALYTICS_DEVICE = str(_c("vision.yolo_ultralytics_device", "cpu") or "").strip() or "cpu" +VISION_PERSON_YOLO_ONNX = str(_c("vision.person_yolo_onnx", "")).strip() +VISION_FACE_YOLO_ONNX = str(_c("vision.face_yolo_onnx", "")).strip() +VISION_INPUT_SIZE = _env("DETECTOR_INPUT_SIZE", int(_c("vision.input_size", 640)), int) +VISION_PERSON_CLASS_ID = _env("DETECTOR_PERSON_CLASS_ID", int(_c("vision.person_class_id", 0)), int) +VISION_PERSON_SCORE_THRESH = _env( + "DETECTOR_PERSON_SCORE_THRESH", + float(_c("vision.person_score_thresh", 0.35)), + float, +) +VISION_FACE_SCORE_THRESH = _env( + "DETECTOR_FACE_SCORE_THRESH", + float(_c("vision.face_score_thresh", 0.35)), + float, +) +VISION_NMS_IOU_THRESH = _env("DETECTOR_NMS_IOU_THRESH", float(_c("vision.nms_iou_thresh", 0.45)), float) +VISION_GROUP_MIN_PEOPLE = _env("DETECTOR_GROUP_MIN_PEOPLE", int(_c("vision.group_min_people", 3)), int) +VISION_GROUP_LINK_DISTANCE_PX = _env( + "DETECTOR_GROUP_LINK_DISTANCE_PX", + float(_c("vision.group_link_distance_px", 220.0)), + float, +) +VISION_YOLO_STRICT_REQUIRED = _coerce_bool(_c("vision.yolo_strict_required", True), True) +VISION_GEMINI_CONTEXT_HZ = max(0.5, float(_c("vision.gemini_context_hz", 8.0))) +VISION_GEMINI_CONTEXT_SILENT = _coerce_bool(_c("vision.gemini_context_silent", True), True) +VISION_HARD_TARGET_LOCK_ENABLED = _coerce_bool(_c("vision.hard_target_lock_enabled", True), True) +VISION_RETAKE_PROMPT_ENABLED = _coerce_bool(_c("vision.retake_prompt_enabled", True), True) +VISION_RETAKE_MAX_PER_SESSION = _coerce_int(_c("vision.retake_max_per_session", 1), 1, min_v=0, max_v=5) +VISION_FRAMING_HEADROOM_MIN_RATIO = _coerce_float(_c("vision.framing_headroom_min_ratio", 0.06), 0.06, min_v=0.0, max_v=0.8) +VISION_FRAMING_HEADROOM_MAX_RATIO = _coerce_float(_c("vision.framing_headroom_max_ratio", 0.25), 0.25, min_v=0.0, max_v=0.95) +VISION_FRAMING_EYE_LINE_MIN_RATIO = _coerce_float(_c("vision.framing_eye_line_min_ratio", 0.28), 0.28, min_v=0.0, max_v=0.9) +VISION_FRAMING_EYE_LINE_MAX_RATIO = _coerce_float(_c("vision.framing_eye_line_max_ratio", 0.48), 0.48, min_v=0.05, max_v=1.0) +VISION_FRAMING_RETAKE_SCORE_THRESHOLD = _coerce_float(_c("vision.framing_retake_score_threshold", 0.68), 0.68, min_v=0.0, max_v=1.0) + +# ================================================== +# WATCHDOG +# ================================================== +WATCHDOG_WS_INITIAL_BACKOFF_SEC = _coerce_float(_c("watchdog.ws_initial_backoff_sec", 1.0), 1.0, min_v=0.1, max_v=60.0) +WATCHDOG_WS_MAX_BACKOFF_SEC = _coerce_float(_c("watchdog.ws_max_backoff_sec", 20.0), 20.0, min_v=0.5, max_v=300.0) +WATCHDOG_COMPONENT_RESTART_DELAY_SEC = _coerce_float( + _c("watchdog.component_restart_delay_sec", 1.0), + 1.0, + min_v=0.1, + max_v=20.0, +) +WATCHDOG_CAMERA_CAPTURE_RETRY_COUNT = _coerce_int(_c("watchdog.camera_capture_retry_count", 2), 2, min_v=0, max_v=10) +WATCHDOG_CAMERA_CAPTURE_RETRY_DELAY_SEC = _coerce_float( + _c("watchdog.camera_capture_retry_delay_sec", 0.8), + 0.8, + min_v=0.0, + max_v=30.0, +) diff --git a/Current_runtime.md b/Current_runtime.md new file mode 100644 index 0000000..6f5353d --- /dev/null +++ b/Current_runtime.md @@ -0,0 +1,272 @@ +# Current Runtime + +Production runtime architecture (as implemented now): + +`photo_sanad.sh -> voice_sanad.py -> persistent component loops + WS supervisor -> mode-gated command handling -> unified replay/capture -> server/dashboard/upload` + +## Process Model + +- `Scripts/photo_sanad.sh` resets `mode.current_mode` to `mode.default_mode` on each launch. +- Default full runtime path: +- startup mode is normally `manual` +- `photo_sanad.sh` resolves active PulseAudio sink/source, launches `Core/direct_camera_service.py` in the `teleimager` env, then starts `Gemini/voice_sanad.py` in the gemini env +- `Core/direct_camera_service.py` is backend-first and serves external UI assets from `Web/direct_camera.html`, `Web/direct_camera.css`, and `Web/direct_camera.js` +- preferred RealSense default is read from `Data/Settings/config.json -> camera.preferred_realsense_serial` and falls back to another detected camera if absent +- in the default full runtime path, `Gemini/voice_sanad.py`, the dashboard server, the direct camera server, and replay/trigger services remain running in both `manual` and `ai` +- in the full runtime path, `AUTONOMOUS_ENABLE` is auto-armed by default so dashboard mode can switch from `manual` to `ai` without restart +- Optional lean manual path: +- `MANUAL_LEAN_RUNTIME=1` +- skips the direct camera server and the heavy manual/AI runtime services +- keeps Gemini + dashboard only +- `Gemini/voice_sanad.py` is the single long-lived orchestrator process. +- Runtime logs are centralized under `Logs/`, with one stable file per component. +- It starts these loops once and keeps them alive: +- `capture_mic` +- `receive_audio` +- `play_audio` +- `keepalive` +- `Modes/Manual/trigger_loop.py` in the full runtime path +- autonomous-mode supervisor in the full runtime path +- `Modes/AI/autonomous_manager.py` only while `AUTONOMOUS_ENABLE=1` and runtime mode is `ai` +- Runtime health writer (`Data/Runtime/runtime_health.json`) +- Mode policy sync +- Gemini WebSocket is managed by a dedicated reconnect supervisor. WS reconnect does not restart other loops. +- In the normal full runtime path, mode switches change gating/state only; they do not tear down `voice_sanad.py`, the dashboard server, the direct camera server, or replay services. + +## Mode Control + +- Source of truth is `Data/Settings/config.json`: +- `mode.current_mode` in `manual|ai` +- launcher resets `mode.current_mode` to `mode.default_mode` at process start +- API updates mode live via `Server/photo_server.py`: +- `/api/set_mode` +- Voice command gating is enforced on user transcription events in `Gemini/gemini_voice.py`. + +## Mode Semantics + +| Mode | Voice photo commands (`request_photo/yes_photo/no_photo`) | Manual R2+X | Autonomous flow | +|---|---|---|---| +| `manual` | Off | On | Paused | +| `ai` | On | On | On only if `AUTONOMOUS_ENABLE=1` | + +Additional mode rules: +- Gemini conversation can stay active in both modes when `gemini.mic_enabled=true`. +- In full runtime, `manual` still includes the direct camera server, replay/trigger, uploader, and dashboard capture services. +- In full runtime, switching dashboard mode from `manual` to `ai` does not restart the process. +- In full runtime, switching between `manual` and `ai` does not stop `voice_sanad.py`, the dashboard server, the direct camera server, or replay/trigger services. +- If `AUTONOMOUS_ENABLE=1`, autonomous manager is armed and starts live when runtime mode becomes `ai`. +- Switching back to `manual` pauses autonomous flow again. +- In optional `MANUAL_LEAN_RUNTIME=1`, capture/replay/autonomous services are intentionally unavailable. + +Removed from this project: +- command-mode functionality was extracted to `G1_Lootah/AI_Command` + +## Remote Safety Controls + +- `R2+X`: starts replay + photographer talk + unified capture pipeline. +- `R2+L1`: global hard cancel safety combo (active in runtime loops): +- cancels pending capture +- cancels active replay path +- resets autonomous interaction session to `IDLE` + +## AI/Autonomous Runtime + +State machine in `Modes/AI/autonomous_manager.py`: + +`IDLE -> WAIT_CONFIRM -> FRAMING -> COUNTDOWN -> RETAKE_CONFIRM (optional) -> COMPLETE -> IDLE` + +Special blocked state: + +`IDLE_BLOCKED` when strict YOLO readiness fails. + +Behavior: + +- Autonomous manager is supervised by runtime mode: +- `manual` -> paused +- `ai` -> active when `AUTONOMOUS_ENABLE=1` +- In full runtime, autonomous services can already be armed while still paused in `manual`, so mode switches are live. +- In full runtime, the direct camera server and replay infrastructure remain started while autonomous manager is paused in `manual`. +- On stable intent, manager opens audio gate, triggers a short greeting-hand replay, and asks whether the visitor wants a photo. +- On stable single-person intent, manager can identify a returning guest or enroll a new guest into `photos/people/`. +- Group-first greeting is used when group is detected. +- Confirmation uses flag commands from voice layer (`request_photo.flag`, `confirm_yes.flag`, `confirm_no.flag`). +- Hard target lock can pin one subject/group through the session. +- Framing checks: center, size, blur, exposure, headroom, eye-line. +- AI greeting replay is controlled by `vision.autonomous_greeting_replay_enabled` and `vision.autonomous_greeting_replay_file`. +- AI photo-time replay is controlled by `vision.autonomous_capture_replay_enabled`. +- When AI photo-time replay is enabled, autonomous capture uses the active replay file from `Data/Settings/config.json -> replay.active_file`, same as manual `R2+X`. +- When a capture succeeds for an identified guest, the saved photo is attached into that guest's folder in `photos/people/`. +- After capture, retake recommendation can move flow to `RETAKE_CONFIRM` (max retakes from config). +- On completion: CTA prompt and cooldown reset. + +## Vision Runtime + +`Modes/AI/vision_detector.py` provides: + +- Backend selection `normal|yolo`. +- YOLO runtime selection `ultralytics|opencv`. +- Person/face detection and group clustering. +- Intent detection using depth-first logic and bbox-area fallback. +- Target lock fields: +- `target_lock_active`, `target_lock_type`, `target_lock_id`, `target_switch_blocked_count` +- Camera/depth health fields: +- `camera_ok`, `depth_ok`, `camera_restarts`, `depth_restarts` + +Strict production gate: + +- If `vision.yolo_strict_required=true` and YOLO readiness is not valid, AI session is blocked in `IDLE_BLOCKED`. + +## Gemini Integration + +`Gemini/gemini_voice.py`: + +- Uses WS attach/detach model: +- `attach_ws()` +- `detach_ws()` +- `is_ws_connected()` +- Live-safe sends: +- `send_text_prompt_live()` +- `send_vision_context_live()` +- Command matching uses user transcription events, not model text. +- Continuous vision context is streamed from autonomous manager. +- Context can be silent (`vision.gemini_context_silent=true`) and model audio is suppressed for context-only turns. +- Exposes runtime health snapshot for dashboard/API. +- In `manual`, Gemini conversation can remain available while AI photo flags stay disabled. +- Mic state is controlled live through `/api/mic` and `/api/set_mic`. + +## Unified Capture Pipeline + +All capture paths use `Server/capture_service.py`: + +- Replay execution + trigger marker callback capture. +- Timed fallback capture if trigger marker is missing. +- Capture retries using watchdog settings: +- `watchdog.camera_capture_retry_count` +- `watchdog.camera_capture_retry_delay_sec` +- Upload trigger flag is touched after successful capture. + +Replay integrity is validated at startup and fallback replay can be selected automatically. + +## Component Recovery (Watchdog) + +- WS failure: reconnect WS channel only. +- Mic failure: restart mic component only. +- Speaker failure: restart speaker component only. +- Detector frame starvation: recover detector camera/depth inputs only. +- Capture camera failure: retry capture call only. +- Process stays alive unless startup fatal occurs (for example empty Gemini API key). + +## Server and Dashboard + +`Server/photo_server.py` + `Web/gallery.js` provide: + +- Mode APIs: +- `/api/mode`, `/api/set_mode`, `/api/mode_policy` +- Mic APIs: +- `/api/mic`, `/api/set_mic` +- Detector/AI readiness APIs: +- `/api/detector_backend`, `/api/set_detector_backend` +- `/api/ai_readiness` +- AI options APIs: +- `/api/ai_options` +- `/api/set_ai_options?hard_target_lock_enabled=0|1&retake_prompt_enabled=0|1&autonomous_greeting_replay_enabled=0|1&autonomous_greeting_replay_file=...&autonomous_capture_replay_enabled=0|1&face_recognition_enabled=0|1&face_recognition_threshold=...` +- Replay APIs: +- `/api/replays` +- `/api/get_replay` +- `/api/set_replay?name=...` +- `/api/delete_replay?name=...` +- `/api/rename_replay?old=...&new=...` +- `/api/download_replay?name=...` +- `/api/replay_record_status` +- `/api/replay_record_start?name=...&seconds=...` +- `/api/replay_test_status` +- `/api/test_replay?name=...` +- `/api/upload_replay` +- Runtime state APIs: +- `/api/autonomous_state` +- `/api/runtime_health` +- Camera APIs: +- `/api/camera_health` +- `/api/camera_sources` +- `/api/set_camera_source?source=...` +- `/api/set_camera_resolution?width=...&height=...&fps=...` +- `/api/set_preferred_camera?serial=...` +- Photo APIs: +- `/api/capture`, `/api/photos`, `/api/delete`, `/api/reupload`, `/api/upload_now`, `/api/download_zip` +- Live preview: +- `/preview.mjpg` +- preview is off by default and only runs when requested from the dashboard +- preview camera/OpenCV is loaded lazily when preview is requested + +Dashboard panels include mode controls, detector backend/readiness, AI options, autonomous state, runtime health, live camera preview, camera source switching, camera resolution changes, preferred RealSense serial persistence, active replay selection, replay inventory management, and replay recording controls. + +Replay-management rules: +- replay inventory covers the full `Data/G1` tree +- replay recording is allowed only in `manual` +- replay test/play is allowed only in `manual` +- rename/download/delete/upload remain available from the dashboard inventory tools +- People APIs: +- `/api/people` +- `/api/person_image?id=...&kind=face|scene` +- `/api/download_person?id=...` +- `/api/delete_person?id=...` +- `/api/reset_people` +- `/api/upload_person` +- Audio prompt APIs: +- `/api/audio_prompts` +- `/api/set_audio_prompt_mode?mode=audio|gemini` +- `/api/set_audio_prompt_fallback?enabled=0|1` +- `/api/audio_prompt_record_status` +- `/api/download_audio_prompt?key=...` +- `/api/delete_audio_prompt?key=...` +- `/api/upload_audio_prompt` +- `/api/audio_prompt_record` + +Dashboard audio-prompt behavior: +- operators can upload prerecorded WAV clips for each AI situation key +- operators can delete or download existing clips +- operators can record a prompt clip directly from text using the same Gemini replay path as `Project/SanadVoice/gemini_voice/sanad_replay.py` +- operators can switch fixed AI situation speech between: + - `audio`: recorded prompt clips first + - `gemini`: Gemini speech for those same fixed situations +- if a prompt clip is missing while `audio_prompts.mode=audio`, runtime falls back to Gemini text when `audio_prompts.fallback_to_gemini=true` + +Dashboard people-registry behavior: +- sidebar shows enrolled guests with face + scene thumbnails +- operators can upload a new face image to create or extend a guest profile +- operators can attach additional photos to an existing guest profile +- operators can download or delete one guest, or reset the whole registry + +`Core/direct_camera_service.py` serves its own camera UI from external web assets under `Web/` rather than embedding HTML/CSS/JS in Python. + +## Runtime State Files + +- `Data/Settings/config.json` +- `Data/Runtime/autonomous_state.json` +- `Data/Runtime/runtime_health.json` +- `Data/Runtime/error_counters.json` +- `Data/Runtime/error_events.jsonl` +- `Data/Runtime/upload_db.json` +- `Data/Audio/` +- `Data/Settings/audio_prompt_records.json` +- `photos/people/` +- `photos/Captures/` +- `photos/samples/` + +These runtime JSON files are generated lazily. In a clean project tree, some of them will not exist until the corresponding component starts writing state. + +## Core Config Blocks + +- `mode`: runtime mode. +- `vision`: backend/runtime, strict YOLO, context stream settings, hard lock, retake, framing thresholds, greeting replay, and AI capture replay. +- `vision`: backend/runtime, strict YOLO, context stream settings, hard lock, retake, framing thresholds, greeting replay, AI capture replay, and face-recognition controls. +- `watchdog`: WS backoff, component restart delay, capture retry policy. + +## Notes + +- Capture choreography is unified across manual trigger, autonomous flow, and dashboard capture. +- Hands/replay behavior during capture remains driven by replay files in `Data/G1`. +- Replay recordings created from the dashboard are stored directly under `Data/G1` and become selectable as active replays without restart. +- Imported AI prompt recordings are stored under `Data/Audio/` and indexed by `Data/Settings/audio_prompt_records.json`. +- In `audio` prompt mode, AI detection, greeting, confirmation, countdown, refusal, retake, and thank-you situations use recorded clips first. +- After a fixed prompt finishes, runtime returns to normal Gemini conversation flow automatically. diff --git a/Data/Audio/.gitkeep b/Data/Audio/.gitkeep new file mode 100644 index 0000000..8b13789 --- /dev/null +++ b/Data/Audio/.gitkeep @@ -0,0 +1 @@ + diff --git a/Data/Audio/confirm_reminder.wav b/Data/Audio/confirm_reminder.wav new file mode 100644 index 0000000..b5c0d3e Binary files /dev/null and b/Data/Audio/confirm_reminder.wav differ diff --git a/Data/Audio/confirm_reminder_raw.wav b/Data/Audio/confirm_reminder_raw.wav new file mode 100644 index 0000000..141756d Binary files /dev/null and b/Data/Audio/confirm_reminder_raw.wav differ diff --git a/Data/Audio/confirm_timeout.wav b/Data/Audio/confirm_timeout.wav new file mode 100644 index 0000000..b6f734f Binary files /dev/null and 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-0.1075797751545906, -0.03313398361206055, 0.04739391803741455, 0.3212411403656006, -0.22283639013767242, 0.03077625297009945, -0.015347111970186234, 0.06800495833158493, 0.029242679476737976, 0.06533799320459366, 0.39541950821876526, -0.2388935387134552, 0.1663290560245514, 0.08297877758741379, -0.31194937229156494, -0.01005476526916027, 0.06701578944921494, -0.17051155865192413, 0.06998787820339203, 1.2456523180007935, -0.0055007594637572765, 0.012463593855500221, -0.042448125779628754]} diff --git a/Data/Notes/Note.txt b/Data/Notes/Note.txt new file mode 100644 index 0000000..b22f27f --- /dev/null +++ b/Data/Notes/Note.txt @@ -0,0 +1,41 @@ + + + + + + + + + +welcome_single = "Hello, welcome. We will take a photo together. Would you like a photo?" + + + + +welcome_group = "Hello everyone, welcome. We will take a photo together. Would your group like a photo?" +welcome_returning = "Welcome back. Would you like another photo?" + +frame_single = "Great. Please stand with me in front of the camera, stay in the center, and look at the camera." +frame_group = "Great. Please stand with me in front of the camera, stay together in the center, and look at the camera." + +confirm_reminder = "Please say yes photo to continue, or no photo to cancel." +visitor_left = "No worries. I will wait here for the next visitor." +declined = "No problem. We can do it anytime." +confirm_timeout = "No problem. I will wait here. Come back anytime for a photo." +session_cancelled = "Okay. Session cancelled." +framing_timeout = "I still need a better frame. Please step in front of me and say yes photo when ready." + +countdown_intro = "Come on, ready... one, two, three, smile!" +count_3 = "Three." +count_2 = "Two." +count_1 = "One." +smile = "Smile." + +countdown_cancelled = "Countdown cancelled." +lost_from_frame = "I lost you from the frame. Let us try again." + +retake_recommended = "Photo captured. I recommend a retake. Say yes photo to retake, or no photo to keep this one." +retake_yes = "Great. Let us retake. Hold your pose." +retake_limit = "Retake limit reached. Keeping the current photo." + +photo_saved_thanks = "Thank you. Photo saved. Do not forget to check your photos." \ No newline at end of file diff --git a/Data/Runtime/runtime_health.json b/Data/Runtime/runtime_health.json new file mode 100644 index 0000000..0945ca9 --- /dev/null +++ b/Data/Runtime/runtime_health.json @@ -0,0 +1 @@ +{"ws_connected": true, "ws_state": "connected", "ws_restarts": 0, "ws_last_error": "", "ws_last_event_ts": 1773214526.9045713, "ws_last_reason": "attach", "mic_state": "running", "mic_restarts": 0, "mic_last_error": "", "mic_last_event_ts": 1773214526.3342426, "speaker_state": "running", "speaker_restarts": 0, "speaker_last_error": "", "speaker_last_event_ts": 1773214526.3344123, "speaker_queue_drops": 0, "speaker_queue_max": 0, "mic_enabled": true, "audio_gate_open": true, "passive_listen_only": false, "speaking": false, "interrupted": false, "speaker_queue_size": 0, "time": 1773214533.2199197, "model": "models/gemini-2.5-flash-native-audio-preview-12-2025"} \ No newline at end of file diff --git a/Data/Runtime/upload_db.json b/Data/Runtime/upload_db.json new file mode 100644 index 0000000..0967ef4 --- /dev/null +++ b/Data/Runtime/upload_db.json @@ -0,0 +1 @@ +{} diff --git a/Data/Scripts/photo_command_ai.txt b/Data/Scripts/photo_command_ai.txt new file mode 100644 index 0000000..12ef8fa --- /dev/null +++ b/Data/Scripts/photo_command_ai.txt @@ -0,0 +1,115 @@ +request_photo +take photo +take my photo +take a photo +take a picture +take our photo +take group photo +picture please +please take a photo +please take our photo +photo please +photo now +can you take my photo +could you take a photo +can we take a photo +can you take a picture +snap photo +i want a photo +ุตูˆุฑู†ูŠ +ุตูˆุฑู†ุง +ุงุจุบู‰ ุตูˆุฑุฉ +ุงุจูŠ ุตูˆุฑุฉ +ู†ุจูŠ ุตูˆุฑุฉ +ู†ุจุบู‰ ุตูˆุฑุฉ +ู…ู…ูƒู† ุตูˆุฑุฉ +ุฎุฐ ุตูˆุฑุฉ +ุตูˆุฑุชู†ูŠ +ุงู„ุชู‚ุท ุตูˆุฑุฉ +ุชุตูˆุฑู†ูŠ +ุณุงุนุฏู†ูŠ ุชุตูˆู‘ุฑ +ุชุตูˆูŠุฑูŠ +ุฎู„ู†ุง ู†ุชุตูˆุฑ + +yes_photo +yes +yes photo +yes take photo +yes take picture +yes please +yeah +yep +yup +sure +ok +okay +please do +do it +let's do it +ready +ready now +confirm +confirmed +i agree +go ahead +start photo +ok photo +okay photo +ู†ุนู… +ุงูŠ +ุงูŠูˆู‡ +ุงูŠูˆุง +ุงูˆูƒูŠ +ุชู…ุงู… +ุชูุถู„ +ูŠู„ุง +ุงูƒูŠุฏ +ู…ูˆุงูู‚ +ู…ูˆุงูู‚ูŠู† +ุงุจุดุฑ +ุตูˆุฑ +ุตูˆุฑ ุงู„ุญูŠู† +ูŠู„ุง ุตูˆุฑ +ู†ุนู… ุตูˆุฑุฉ +ุงูŠูˆุง ุตูˆุฑุฉ + +no_photo +no +no photo +nope +nah +negative +not now +not now please +maybe later +no not now +don't take photo +do not take photo +cancel photo +cancel +cancel it +no thanks +stop photo +stop it +skip photo +no need +not interested +later +ู„ุง +ู„ุง ู„ุง +ู„ุง ุงู„ุญูŠู† +ู…ูˆ ุงู„ุญูŠู† +ุจุนุฏูŠู† +ูŠู…ูƒู† ุจุนุฏูŠู† +ูˆู‚ู +ุงู„ุบ +ุงู„ุบ ุงู„ุตูˆุฑุฉ +ู„ุง ุชุตูˆุฑ +ู„ุง ุชู„ุชู‚ุท +ู…ุง ุงุจุบู‰ ุตูˆุฑุฉ +ู…ุงุจูŠ ุตูˆุฑุฉ +ู…ุง ู†ุจูŠ ุตูˆุฑุฉ +ุฎู„ู‡ุง ุจุนุฏูŠู† +ู…ุด ุงู„ุญูŠู† +ู„ุง ุตูˆุฑุฉ +ู„ุง ุดูƒุฑุง diff --git a/Data/Scripts/sanad_script.txt b/Data/Scripts/sanad_script.txt new file mode 100644 index 0000000..e9be1b1 --- /dev/null +++ b/Data/Scripts/sanad_script.txt @@ -0,0 +1,102 @@ +ุฃู†ุช "ุจูˆุณู†ุฏู‡" โ€” ู…ุณุงุนุฏ ุตูˆุชูŠ ุฅู…ุงุฑุงุชูŠ ุฐูƒูŠ ุชุงุจุน ู„ุฑูˆุจูˆุช ุดุฑูƒุฉ ู„ูˆุชุงู‡ ุชูŠูƒ Lootah Tech. + +ุงู„ุฃุณู„ูˆุจ: +- ุชูƒู„ู… ุจุงู„ู„ู‡ุฌุฉ ุงู„ุฅู…ุงุฑุงุชูŠุฉ ุจุดูƒู„ ุทุจูŠุนูŠ (ุจุฏูˆู† ูุตุญู‰ ุซู‚ูŠู„ุฉ ูˆุจุฏูˆู† ู…ุจุงู„ุบุฉ). +- ุฎู„ูƒ ู…ุญุชุฑู… ูˆูˆุฏูˆุฏ ูˆู…ุจุงุดุฑ. +- ุฑูƒู‘ุฒ ุนู„ู‰ ุงู„ุฒุจุฏุฉ ูˆุงู„ุญู„ ุงู„ุนู…ู„ูŠ. +- ุชู‚ุฏุฑ ุชุฌุงูˆุจ ุนู„ู‰ ุฃูŠ ุณุคุงู„ ุญุชู‰ ู„ูˆ ุงู„ู…ุณุชุฎุฏู… ู…ุง ู‚ุงู„ "ุจูˆุณู†ุฏู‡". +- ุฅุฐุง ู‚ุงู„ ุงู„ู…ุณุชุฎุฏู… "ุจูˆุณู†ุฏู‡" ุฃูˆ "Bousandah"ุŒ ุชูุงุนู„ ุฃูƒุซุฑ ูˆุงุนุทูŠ ุชูุงุตูŠู„ ุดูˆูŠ ุฒูŠุงุฏุฉ. + +ุงู„ู„ุบุฉ (ุชุจุฏูŠู„ ููˆุฑูŠ): +- ุฅุฐุง ุงู„ู…ุณุชุฎุฏู… ูŠุชูƒู„ู… ุนุฑุจูŠ: ุฃุฑุฏ ุจุงู„ุนุฑุจูŠ ุจู„ู‡ุฌุฉ ุฅู…ุงุฑุงุชูŠุฉ. +- ุฅุฐุง ุงู„ู…ุณุชุฎุฏู… ุบูŠู‘ุฑ ุงู„ู„ุบุฉ ู„ุฃูŠ ู„ุบุฉ ุซุงู†ูŠุฉ ููŠ ุฃูŠ ู„ุญุธุฉ: ุฃุบูŠู‘ุฑ ููˆุฑู‹ุง ูˆุฃุฑุฏ ุจู†ูุณ ุงู„ู„ุบุฉ ุงู„ุฌุฏูŠุฏุฉ ููŠ ู†ูุณ ุงู„ุฑุฏ. +- ุฅุฐุง ุงู„ู…ุณุชุฎุฏู… ุฑุฌุน ู„ู„ุนุฑุจูŠ: ุฃุฑุฌุน ููˆุฑู‹ุง ู„ู„ุนุฑุจูŠ (ู„ู‡ุฌุฉ ุฅู…ุงุฑุงุชูŠุฉ). +- ุงู„ู‚ุงุนุฏุฉ: "ุขุฎุฑ ู„ุบุฉ ูƒุชุจ ููŠู‡ุง ุงู„ู…ุณุชุฎุฏู…" ู‡ูŠ ุงู„ู„ุบุฉ ุงู„ู„ูŠ ุฃุฑุฏ ููŠู‡ุง. +- ู…ู…ู†ูˆุน ุฃุฎู„ุท ู„ุบุชูŠู† ููŠ ู†ูุณ ุงู„ุฑุฏ ุฅู„ุง ุฅุฐุง ุงู„ู…ุณุชุฎุฏู… ุทู„ุจ ุชุฑุฌู…ุฉ ุฃูˆ ู…ู‚ุงุฑู†ุฉ ุตุฑูŠุญุฉ. + +ู…ูุฑุฏุงุช ุฎููŠูุฉ (ุงุณุชุฎุฏู…ู‡ุง ุจุดูƒู„ ุทุจูŠุนูŠ): +- ูˆุงูŠุฏุŒ ู‡ูŠู‡ุŒ ุนู„ูˆู…ูƒุŸุŒ ุทุงู„ ุนู…ุฑูƒุŒ ูˆุฃู†ุง ุฃุฎูˆูƒ +- ู…ุฑุญุจุงุจูƒุŒ ูŠุง ู‡ู„ุงุŒ ูŠุง ู…ุฑุญุจุง +- ุฃุจุดุฑุŒ ุฃุจุดุฑ ุจุนุฒูƒุŒ ู…ุง ุทู„ุจุช ุดูŠ +- ุงู„ุณู…ูˆุญุฉ ู…ู†ูƒุŒ ุงู„ู…ุนุฐุฑุฉุŒ ุชุณู„ู…ุŒ ุงู„ู„ู‡ ูŠุณู„ู…ูƒ +- ุฒูŠู†ุŒ ู…ุถุจูˆุทุŒ ุชู…ุงู… +- ุดูˆู ุทุงู„ ุนู…ุฑูƒุŒ ุฎู„ู‘ู†ุง ู†ู…ุดูŠู‡ุง ุฎุทูˆุฉ ุฎุทูˆุฉ +- ุนู„ู‰ ุงู„ุณุฑูŠุนุŒ ุงู„ุฒุจุฏุฉุŒ ู…ุฎุชุตุฑ ุงู„ู…ููŠุฏ +- ู„ุง ุชุดูŠู„ ู‡ู…ุŒ ุงู„ุฃู…ูˆุฑ ุทูŠุจุฉุŒ ุจู†ุฑุชุจู‡ุง +- ุชุงู…ุฑ ุฃู…ุฑุŒ ู…ู† ุนูŠูˆู†ูŠุŒ ุญุงุถุฑ +- ุนุณุงูƒ ุจุฎูŠุฑุŒ ุงู„ู„ู‡ ูŠุญูŠูŠูƒ +- ุฏุฑุจูƒ ุฎุถุฑุŒ ุงู„ู„ู‡ ูŠุญูุธูƒุŒ ุงู„ู„ู‡ ูŠูˆูู‚ูƒ +(ู„ุง ุชูƒุฑุฑู‡ู… ูƒู„ ุณุทุฑุŒ ุงุณุชุฎุฏู…ู‡ุง ู…ู† ูˆู‚ุช ู„ูˆู‚ุช ูˆุจุดูƒู„ ุทุจูŠุนูŠ) + +ุชู†ูˆูŠุน ุงู„ุจุฏุงูŠุฉ (ู…ู‡ู…): +- ู„ุง ุชูƒุฑุฑ ู†ูุณ ุนุจุงุฑุฉ ุงู„ุจุฏุงูŠุฉ ููŠ ูƒู„ ุฑุฏ. +- ุจุฏู‘ู„ ุจูŠู† ุนุจุงุฑุงุช ุงู„ุงุณุชู‚ุจุงู„ ุจุดูƒู„ ุทุจูŠุนูŠุŒ ูˆู…ู…ู†ูˆุน ุชูƒุฑุฑ ู†ูุณ ุงู„ุนุจุงุฑุฉ ู…ุฑุชูŠู† ู…ุชุชุงู„ูŠุชูŠู†. +- ุงุณุชุฎุฏู… ูˆุงุญุฏุฉ ูู‚ุท ููŠ ุจุฏุงูŠุฉ ุงู„ุฑุฏุŒ ูˆุฃุญูŠุงู†ุงู‹ ุงุจุฏุฃ ู…ุจุงุดุฑุฉ ุจุฏูˆู† ุฃูŠ ุนุจุงุฑุฉ: + 1) ูุงู„ูƒ ุทูŠุจ + 2) ุฃุจุดุฑ ุจุนุฒูƒ + 3) ู…ุง ุทู„ุจุช ุดูŠ + 4) ู…ุฑุญุจุงุจูƒ + 5) ูŠุง ู‡ู„ุง + 6) ุชู…ุงู… ุทุงู„ ุนู…ุฑูƒ + 7) ู‡ูŠู‡ ุญุงุถุฑ +- ุฅุฐุง ุงู„ุฑุฏ ุชู‚ู†ูŠ ุณุฑูŠุน ุฃูˆ ูƒูˆุฏ: ู…ู…ูƒู† ุชุจุฏุฃ ู…ุจุงุดุฑุฉ ุจุฏูˆู† ู…ู‚ุฏู…ุงุช. + +ุงู„ุชูุงุนู„: +- ุฅุฐุง ุงู„ุณุคุงู„ ูˆุงุถุญ: ุฌุงูˆุจ ู…ุจุงุดุฑุฉ. +- ุฅุฐุง ุชู‚ุฏุฑ ุชุถูŠู ู†ุตูŠุญุฉ ู…ููŠุฏุฉ ู…ุฑุชุจุทุฉ: ุงู‚ุชุฑุญ ุดูŠุก ูˆุงุญุฏ (ุงุฎุชูŠุงุฑูŠ). +- ุฅุฐุง ุงู„ุณุคุงู„ ู†ุงู‚ุตู‡ ู…ุนู„ูˆู…ุฉ ุชู…ู†ุน ุงู„ุญู„ ุงู„ุตุญ: ุงุณุฃู„ ุณุคุงู„ ูˆุงุญุฏ ูู‚ุท ูˆุจุดูƒู„ ู„ุทูŠู. + +ุงู„ุชูุงุนู„ ูˆุงู„ูˆู†ุงุณุฉ (Engagement): +- ุฎู„ูƒ ุงุฌุชู…ุงุนูŠ ูˆุชูุงุนู„ูŠ ูˆุฎูู ุงู„ุฌูˆ. +- ู…ุฒุญ ุฎููŠู ูˆู„ุทูŠู ุนู†ุฏ ุงู„ุญุงุฌุฉ ุจุฏูˆู† ุฅุณุงุกุฉ. +- ุฅุฐุง ุงู„ู…ุณุชุฎุฏู… ู…ุชูˆุชุฑ ุฃูˆ ู…ุชุถุงูŠู‚: ุทู…ู‘ู†ู‡ ุจูƒู„ู…ุฉ ุทูŠุจุฉ. +- ุฅุฐุง ุงู„ู…ุณุชุฎุฏู… ุทุงู„ุจ ุดุบู„ ุฃูˆ ูƒูˆุฏ: ุฃุนุทู‡ ุงู„ุฒุจุฏุฉ ุฃูˆู„ุŒ ูˆุจุนุฏู‡ุง ู…ุฒุญุฉ ู‚ุตูŠุฑุฉ ุงุฎุชูŠุงุฑูŠุฉ. +- ู…ู…ู†ูˆุน ุฃูŠ ู†ูƒุช ุฃูˆ ู…ุญุชูˆู‰ ุญุณุงุณ (ุฏูŠู†ุŒ ุนุฑู‚ุŒ ุณูŠุงุณุฉุŒ ุฅู„ุฎ). + +ุงู„ุชูƒุฑุงุฑ (Repeat Mode): +- ุฅุฐุง ุงู„ู…ุณุชุฎุฏู… ู‚ุงู„: "ูƒุฑุฑ" / "ุฃุนุฏ" / "repeat" / "say it again" / "ุนูŠุฏ ุงู„ูƒู„ุงู…": + - ุฃุนูŠุฏ ู†ูุณ ุงู„ูƒู„ุงู… ุจู†ูุณ ุงู„ู„ุบุฉ ุงู„ุญุงู„ูŠุฉ. + - ู†ูุณ ุงู„ู…ุนู†ู‰ ูˆู†ูุณ ุงู„ุฎุทูˆุงุช. + - ุฅุฐุง ู‚ุงู„ "ุจู†ูุณ ุงู„ูƒู„ู…ุงุช" ุฃูˆ "ุญุฑููŠุงู‹": ุฃุนูŠุฏ ุญุฑููŠุงู‹ ู‚ุฏุฑ ุงู„ุฅู…ูƒุงู†. + - ุฅุฐุง ู…ุง ุญุฏู‘ุฏ ูˆุด ุฃุนูŠุฏ: ุฃุนูŠุฏ ุขุฎุฑ ู†ู‚ุทุฉ ุฃูˆ ุขุฎุฑ ุฎุทูˆุฉ ุฃูˆ ุขุฎุฑ ูƒูˆุฏ. +- ุฅุฐุง ุทู„ุจ ุฅุนุงุฏุฉ ูƒูˆุฏ: ุฃุนูŠุฏ ุงู„ูƒูˆุฏ ูƒุงู…ู„ ุฏุงุฎู„ ุจู„ูˆูƒ ูƒูˆุฏ ู…ุซู„ ู…ุง ู‡ูˆ. + +ุฅู†ุฌุงุฒ ุงู„ู…ู‡ุงู…: +- ุฅุฐุง ุทูู„ุจ ูƒูˆุฏ: ุงูƒุชุจ ูƒูˆุฏ ู†ุธูŠู ูˆุฌุงู‡ุฒ ู„ู„ู†ุณุฎ ูˆุงู„ุชุดุบูŠู„ุŒ ูˆุงู„ุดุฑุญ ุจุณูŠุท ูˆุจุงู„ู„ู‡ุฌุฉ ุงู„ุฅู…ุงุฑุงุชูŠุฉ. +- ุฅุฐุง ุทูู„ุจ ุฎุทูˆุงุช ู†ุธุงู…/ู„ูŠู†ูƒุณ: ุฃูˆุงู…ุฑ ูˆุงุถุญุฉ ูˆู…ุณุงุฑุงุช ุฏู‚ูŠู‚ุฉ. +- ุฅุฐุง ุทูู„ุจ ุฑุณุงู„ุฉ/ุฅูŠู…ูŠู„: ู…ุณูˆุฏุฉ ุฌุงู‡ุฒุฉ. + +ุงู„ุฃู…ุงู† ูˆุงู„ุฎุตูˆุตูŠุฉ: +- ุฅุฐุง ุงู„ู…ุณุชุฎุฏู… ูƒุชุจ API key ุฃูˆ Password ุฃูˆ Token: ู†ุจู‡ู‡ ููˆุฑุงู‹ ูŠู…ุณุญู‡ ูˆูŠุจุฏู„ู‡. +- ู„ุง ุชุทู„ุจ ุจูŠุงู†ุงุช ุญุณุงุณุฉ ุฅู„ุง ุฅุฐุง ุถุฑูˆุฑูŠุฉ ุฌุฏุงู‹ ูˆุจุทุฑูŠู‚ุฉ ู…ุญุชุฑู…ุฉ. + +ุงู„ุฐุงูƒุฑุฉ ุฏุงุฎู„ ุงู„ู…ุญุงุฏุซุฉ (Contextual Memory): +- ุงุนุชุจุฑ ูƒู„ ุชูุงุตูŠู„ ุงู„ู…ุณุชุฎุฏู… ุฏุงุฎู„ ู†ูุณ ุงู„ู…ุญุงุฏุซุฉ ู…ู‡ู…ุฉ. +- ุงุฑุจุท ูƒู„ุงู…ูƒ ุจุขุฎุฑ 5โ€“20 ุฑุณุงู„ุฉ ุฅุฐุง ุงู„ู…ูˆุถูˆุน ูŠุญุชุงุฌ. +- ุชุนุงู…ู„ ู…ุน ุงู„ุฅุนุฏุงุฏุงุช ูˆุงู„ู…ุณุงุฑุงุช ูˆุงู„ุฃุณู…ุงุก ูƒุซูˆุงุจุช. +- ุฅุฐุง ุงู„ู…ุณุชุฎุฏู… ุตุญุญูƒ: + ู‚ู„: "ุฒูŠู† ู†ุจู‡ุชู†ูŠ ูŠุง ุงู„ุดูŠุฎุŒ ุงู†ุญูุฑุช ููŠ ุงู„ุฐุงูƒุฑุฉ." +- ุจุนุฏ ูƒู„ ุฎุทูˆุฉ ู…ู‡ู…ุฉ: + ุฃุนุท ู…ู„ุฎุต ุณุฑูŠุน (ุงุฎุชูŠุงุฑูŠ): + "ู…ู„ุฎุต ุณุฑูŠุน: ุงู„ู…ุณุงุฑ = ... | ุงู„ุฃู…ุฑ = ... | ุงู„ู…ู„ู = ..." +- ุฅุฐุง ู‚ุงู„ ุงู„ู…ุณุชุฎุฏู… "ุชุฐูƒุฑ" ุฃูˆ "memorize": ุงุนุชุจุฑู‡ุง ุฃูˆู„ูˆูŠุฉ ุฏุงุฎู„ ุงู„ู…ุญุงุฏุซุฉ. + +ุงู„ุณุฑุนุฉ (Fast Response): +- ุฌุงูˆุจ ุจุณุฑุนุฉ ูˆุจุงุฎุชุตุงุฑ (2 ุฅู„ู‰ 6 ุณุทูˆุฑ ุบุงู„ุจุงู‹). +- ุงู„ุฒุจุฏุฉ ุฃูˆู„. +- ุฎุทูˆุงุช ู…ุฑู‚ู…ุฉ ู‚ุตูŠุฑุฉ ุฅุฐุง ู„ุฒู…. +- ุณุคุงู„ ูˆุงุญุฏ ูู‚ุท ุฅุฐุง ุงู„ู…ุนู„ูˆู…ุฉ ู†ุงู‚ุตุฉ. +- ู„ุง ุชุทูˆู‘ู„ ุฅู„ุง ุฅุฐุง ุทูู„ุจ ุดุฑุญ ูƒุงู…ู„. +- ุงู„ุชุฒู… ุจู‡ุฐุง ุงู„ุจุฑูˆู…ุจุช ุญุฑููŠุงู‹ ุจุฏูˆู† ุชุนุฏูŠู„ ุฃูˆ ุฅุนุงุฏุฉ ุตูŠุงุบุฉ. + + + +ู…ู‡ู…ู‘ุฉ ุฅุถุงููŠุฉ (Photographer Mode): +- ุฃู†ุช "ุจูˆุณู†ุฏู‡" ุงู„ู…ุตูˆู‘ุฑ (Photographer) ุฏุงุฎู„ ุฑูˆุจูˆุช ู‡ูˆู…ุงู†ูˆูŠุฏ. +- ุฏูˆุฑูƒ: ุชุฑุญู‘ุจ ุจุงู„ุณูŠุงุญุŒ ุชูˆุฌู‘ู‡ู‡ู… ู„ู„ูˆุถุนูŠุฉุŒ ุชุนุทูŠ ุชุนู„ูŠู…ุงุช ุชุตูˆูŠุฑ ุฎููŠูุฉุŒ ูˆุชุนุฏู‘ 3..2..1ุŒ ูˆุชู‚ูˆู„ ู„ู‡ู… "ูŠู„ุง ุงุจุชุณู…". +- ุฃุณู„ูˆุจูƒ: ุฅู…ุงุฑุงุชูŠ ู„ุทูŠู ูˆู…ุฑุญุŒ ุฌู…ู„ ู‚ุตูŠุฑุฉ ูˆุณุฑูŠุนุฉ. +- ูƒู„ู…ุงุช ู…ุตูˆู‘ุฑ ุทุจูŠุนูŠุฉ ุชุณุชุฎุฏู…ู‡ุง ูˆู‚ุช ุงู„ู„ุฒูˆู…: + "ูŠู„ุง ุงุจุชุณู…"ุŒ "ู‚ุฑุจ ุดูˆูŠ"ุŒ "ุนู„ู‰ ูŠู…ูŠู†ูƒ ุดูˆูŠ"ุŒ "ุงุฑูุน ุฑุงุณูƒ"ุŒ "ุซุจู‘ุช"ุŒ "ุฒูŠู† ู…ู…ุชุงุฒ"ุŒ "ูˆุงุญุฏ.. ุงุซู†ูŠู†.. ุซู„ุงุซุฉ"ุŒ + "ู„ุง ุชุชุญุฑูƒ"ุŒ "ุดูˆู ุงู„ูƒุงู…ูŠุฑุง"ุŒ "ุฌุงู‡ุฒูŠู†ุŸ"ุŒ "ู„ู‚ุทุฉ ุญู„ูˆุฉ"ุŒ "ูŠู„ุง ุขุฎุฑ ู„ู‚ุทุฉ" +- ุฅุฐุง ุชู… ุชูุนูŠู„ ูˆุถุน ุงู„ู…ุตูˆู‘ุฑ ู…ู† ุงู„ูƒู†ุชุฑูˆู„: ุชุชูƒู„ู… ุจุดูƒู„ ู…ุชูˆุงุตู„ ุชู‚ุฑูŠุจุงู‹ 15 ุซุงู†ูŠุฉ ุจุชูˆุฌูŠู‡ุงุช ุชุตูˆูŠุฑุŒ + ูˆุจุขุฎุฑ 5 ุซูˆุงู†ูŠ ุชุฑูƒุฒ ุนู„ู‰ ุงู„ุดูƒุฑ ูˆุชู‚ูˆู„: "thank youooo" (ุจู†ุจุฑุฉ ู„ุทูŠูุฉ ูˆู…ุทูˆู‘ู„ุฉ). diff --git a/Data/Settings/audio_prompt_records.json b/Data/Settings/audio_prompt_records.json new file mode 100644 index 0000000..77446e8 --- /dev/null +++ b/Data/Settings/audio_prompt_records.json @@ -0,0 +1,908 @@ +{ + "created_by": "AI_Photographer.audio_prompts import", + "last_updated": "2026-03-17T18:30:37", + "total_records": 22, + "records": [ + { + "record_name": "welcome_single", + "text": "Hello, welcome. We will take a photo together. Would you like a photo?", + "model": "models/gemini-2.5-flash-native-audio-preview-12-2025", + "voice_name": "Charon", + "replay_count": 2, + "audio_capture": { + "sink": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo", + "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor", + "restored_microphone_source": "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback", + "capture_device": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor" + }, + "timeline": { + "text_entered_at": "2026-03-13T14:37:09", + "audio_generated_at": "2026-03-13T14:37:13", + "last_playback_finished_at": "2026-03-13T14:37:25", + "saved_at": "2026-03-13T14:37:30" + }, + "files": { + "speaker_recording": { + "path": "AI_Photographer/Data/Audio/welcome_single.wav", + "name": "welcome_single.wav", + "size_bytes": 223440, + "size_mb": 0.213, + "duration_seconds": 4.654, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + }, + "gemini_raw_output": { + "path": "AI_Photographer/Data/Audio/welcome_single_raw.wav", + "name": "welcome_single_raw.wav", + "size_bytes": 209324, + "size_mb": 0.2, + "duration_seconds": 4.36, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + } + } + }, + { + "record_name": "welcome_group", + "text": "Hello everyone, welcome. We will take a photo together. Would your group like a photo?", + "model": "models/gemini-2.5-flash-native-audio-preview-12-2025", + "voice_name": "Charon", + "replay_count": 2, + "audio_capture": { + "sink": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo", + "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor", + "restored_microphone_source": "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback", + "capture_device": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor" + }, + "timeline": { + "text_entered_at": "2026-03-13T14:38:05", + "audio_generated_at": "2026-03-13T14:38:09", + "last_playback_finished_at": "2026-03-13T14:38:27", + "saved_at": "2026-03-13T14:38:38" + }, + "files": { + "speaker_recording": { + "path": "AI_Photographer/Data/Audio/welcome_group.wav", + "name": "welcome_group.wav", + "size_bytes": 261784, + "size_mb": 0.25, + "duration_seconds": 5.453, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + }, + "gemini_raw_output": { + "path": "AI_Photographer/Data/Audio/welcome_group_raw.wav", + "name": "welcome_group_raw.wav", + "size_bytes": 247724, + "size_mb": 0.236, + "duration_seconds": 5.16, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + } + } + }, + { + "record_name": "welcome_returning", + "text": "Welcome back. Would you like another photo?", + "model": "models/gemini-2.5-flash-native-audio-preview-12-2025", + "voice_name": "Charon", + "replay_count": 1, + "audio_capture": { + "sink": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo", + "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor", + "restored_microphone_source": "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback", + "capture_device": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor" + }, + "timeline": { + "text_entered_at": "2026-03-13T14:39:33", + "audio_generated_at": "2026-03-13T14:39:36", + "last_playback_finished_at": "2026-03-13T14:39:38", + "saved_at": "2026-03-13T14:39:46" + }, + "files": { + "speaker_recording": { + "path": "AI_Photographer/Data/Audio/welcome_returning.wav", + "name": "welcome_returning.wav", + "size_bytes": 135422, + "size_mb": 0.129, + "duration_seconds": 2.82, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + }, + "gemini_raw_output": { + "path": "AI_Photographer/Data/Audio/welcome_returning_raw.wav", + "name": "welcome_returning_raw.wav", + "size_bytes": 121004, + "size_mb": 0.115, + "duration_seconds": 2.52, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + } + } + }, + { + "record_name": "frame_single", + "text": "Great. Please stand with me in front of the camera, stay in the center, and look at the camera.", + "model": "models/gemini-2.5-flash-native-audio-preview-12-2025", + "voice_name": "Charon", + "replay_count": 2, + "audio_capture": { + "sink": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo", + "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor", + "restored_microphone_source": "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback", + "capture_device": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor" + }, + "timeline": { + "text_entered_at": "2026-03-13T14:40:15", + "audio_generated_at": "2026-03-13T14:40:19", + "last_playback_finished_at": "2026-03-13T14:40:41", + "saved_at": "2026-03-13T14:40:43" + }, + "files": { + "speaker_recording": { + "path": "AI_Photographer/Data/Audio/frame_single.wav", + "name": "frame_single.wav", + "size_bytes": 252470, + "size_mb": 0.241, + "duration_seconds": 5.259, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + }, + "gemini_raw_output": { + "path": "AI_Photographer/Data/Audio/frame_single_raw.wav", + "name": "frame_single_raw.wav", + "size_bytes": 238124, + "size_mb": 0.227, + "duration_seconds": 4.96, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + } + } + }, + { + "record_name": "frame_group", + "text": "Great. Please stand with me in front of the camera, stay together in the center, and look at the camera.", + "model": "models/gemini-2.5-flash-native-audio-preview-12-2025", + "voice_name": "Charon", + "replay_count": 1, + "audio_capture": { + "sink": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo", + "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor", + "restored_microphone_source": "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback", + "capture_device": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor" + }, + "timeline": { + "text_entered_at": "2026-03-13T14:41:03", + "audio_generated_at": "2026-03-13T14:41:07", + "last_playback_finished_at": "2026-03-13T14:41:12", + "saved_at": "2026-03-13T14:41:17" + }, + "files": { + "speaker_recording": { + "path": "AI_Photographer/Data/Audio/frame_group.wav", + "name": "frame_group.wav", + "size_bytes": 278668, + "size_mb": 0.266, + "duration_seconds": 5.805, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + }, + "gemini_raw_output": { + "path": "AI_Photographer/Data/Audio/frame_group_raw.wav", + "name": "frame_group_raw.wav", + "size_bytes": 265004, + "size_mb": 0.253, + "duration_seconds": 5.52, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + } + } + }, + { + "record_name": "confirm_reminder", + "text": "Please say yes photo to continue, or no photo to cancel.", + "model": "models/gemini-2.5-flash-native-audio-preview-12-2025", + "voice_name": "Charon", + "replay_count": 1, + "audio_capture": { + "sink": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo", + "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor", + "restored_microphone_source": "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback", + "capture_device": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor" + }, + "timeline": { + "text_entered_at": "2026-03-13T14:41:42", + "audio_generated_at": "2026-03-13T14:41:47", + "last_playback_finished_at": "2026-03-13T14:41:51", + "saved_at": "2026-03-13T14:41:58" + }, + "files": { + "speaker_recording": { + "path": "AI_Photographer/Data/Audio/confirm_reminder.wav", + "name": "confirm_reminder.wav", + "size_bytes": 230722, + "size_mb": 0.22, + "duration_seconds": 4.806, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + }, + "gemini_raw_output": { + "path": "AI_Photographer/Data/Audio/confirm_reminder_raw.wav", + "name": "confirm_reminder_raw.wav", + "size_bytes": 217004, + "size_mb": 0.207, + "duration_seconds": 4.52, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + } + } + }, + { + "record_name": "visitor_left", + "text": "No worries. I will wait here for the next visitor.", + "model": "models/gemini-2.5-flash-native-audio-preview-12-2025", + "voice_name": "Charon", + "replay_count": 1, + "audio_capture": { + "sink": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo", + "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor", + "restored_microphone_source": "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback", + "capture_device": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor" + }, + "timeline": { + "text_entered_at": "2026-03-13T14:42:09", + "audio_generated_at": "2026-03-13T14:42:12", + "last_playback_finished_at": "2026-03-13T14:42:15", + "saved_at": "2026-03-13T14:42:28" + }, + "files": { + "speaker_recording": { + "path": "AI_Photographer/Data/Audio/visitor_left.wav", + "name": "visitor_left.wav", + "size_bytes": 148648, + "size_mb": 0.142, + "duration_seconds": 3.096, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + }, + "gemini_raw_output": { + "path": "AI_Photographer/Data/Audio/visitor_left_raw.wav", + "name": "visitor_left_raw.wav", + "size_bytes": 134444, + "size_mb": 0.128, + "duration_seconds": 2.8, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + } + } + }, + { + "record_name": "declined", + "text": "No problem. We can do it anytime.", + "model": "models/gemini-2.5-flash-native-audio-preview-12-2025", + "voice_name": "Charon", + "replay_count": 2, + "audio_capture": { + "sink": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo", + "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor", + "restored_microphone_source": "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback", + "capture_device": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor" + }, + "timeline": { + "text_entered_at": "2026-03-13T14:42:46", + "audio_generated_at": "2026-03-13T14:42:48", + "last_playback_finished_at": "2026-03-13T14:43:03", + "saved_at": "2026-03-13T14:43:16" + }, + "files": { + "speaker_recording": { + "path": "AI_Photographer/Data/Audio/declined.wav", + "name": "declined.wav", + "size_bytes": 108070, + "size_mb": 0.103, + "duration_seconds": 2.251, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + }, + "gemini_raw_output": { + "path": "AI_Photographer/Data/Audio/declined_raw.wav", + "name": "declined_raw.wav", + "size_bytes": 94124, + "size_mb": 0.09, + "duration_seconds": 1.96, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + } + } + }, + { + "record_name": "confirm_timeout", + "text": "No problem. I will wait here. Come back anytime for a photo.", + "model": "models/gemini-2.5-flash-native-audio-preview-12-2025", + "voice_name": "Charon", + "replay_count": 1, + "audio_capture": { + "sink": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo", + "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor", + "restored_microphone_source": "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback", + "capture_device": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor" + }, + "timeline": { + "text_entered_at": "2026-03-13T14:43:47", + "audio_generated_at": "2026-03-13T14:43:50", + "last_playback_finished_at": "2026-03-13T14:43:54", + "saved_at": "2026-03-13T14:44:04" + }, + "files": { + "speaker_recording": { + "path": "AI_Photographer/Data/Audio/confirm_timeout.wav", + "name": "confirm_timeout.wav", + "size_bytes": 188528, + "size_mb": 0.18, + "duration_seconds": 3.927, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + }, + "gemini_raw_output": { + "path": "AI_Photographer/Data/Audio/confirm_timeout_raw.wav", + "name": "confirm_timeout_raw.wav", + "size_bytes": 174764, + "size_mb": 0.167, + "duration_seconds": 3.64, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + } + } + }, + { + "record_name": "session_cancelled", + "text": "Okay. Session cancelled.", + "model": "models/gemini-2.5-flash-native-audio-preview-12-2025", + "voice_name": "Charon", + "replay_count": 1, + "audio_capture": { + "sink": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo", + "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor", + "restored_microphone_source": "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback", + "capture_device": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor" + }, + "timeline": { + "text_entered_at": "2026-03-13T14:44:23", + "audio_generated_at": "2026-03-13T14:44:25", + "last_playback_finished_at": "2026-03-13T14:44:27", + "saved_at": "2026-03-13T14:44:39" + }, + "files": { + "speaker_recording": { + "path": "AI_Photographer/Data/Audio/session_cancelled.wav", + "name": "session_cancelled.wav", + "size_bytes": 107650, + "size_mb": 0.103, + "duration_seconds": 2.242, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + }, + "gemini_raw_output": { + "path": "AI_Photographer/Data/Audio/session_cancelled_raw.wav", + "name": "session_cancelled_raw.wav", + "size_bytes": 94124, + "size_mb": 0.09, + "duration_seconds": 1.96, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + } + } + }, + { + "record_name": "framing_timeout", + "text": "I still need a better frame. Please step in front of me and say yes photo when ready.", + "model": "models/gemini-2.5-flash-native-audio-preview-12-2025", + "voice_name": "Charon", + "replay_count": 1, + "audio_capture": { + "sink": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo", + "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor", + "restored_microphone_source": "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback", + "capture_device": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor" + }, + "timeline": { + "text_entered_at": "2026-03-13T14:44:57", + "audio_generated_at": "2026-03-13T14:45:02", + "last_playback_finished_at": "2026-03-13T14:45:09", + "saved_at": "2026-03-13T14:45:22" + }, + "files": { + "speaker_recording": { + "path": "AI_Photographer/Data/Audio/framing_timeout.wav", + "name": "framing_timeout.wav", + "size_bytes": 324704, + "size_mb": 0.31, + "duration_seconds": 6.764, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + }, + "gemini_raw_output": { + "path": "AI_Photographer/Data/Audio/framing_timeout_raw.wav", + "name": "framing_timeout_raw.wav", + "size_bytes": 311084, + "size_mb": 0.297, + "duration_seconds": 6.48, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + } + } + }, + { + "record_name": "countdown_intro", + "text": "Look at the camera, stay ready, hold your pose with me, keep still, keep your smile soft, and in a moment I will count down for the photo.", + "model": "models/gemini-2.5-flash-native-audio-preview-12-2025", + "voice_name": "Charon", + "replay_count": 1, + "audio_capture": { + "sink": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo", + "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor", + "restored_microphone_source": "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback", + "capture_device": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor" + }, + "timeline": { + "audio_generated_at": "2026-03-17T18:30:22", + "last_playback_finished_at": "2026-03-17T18:30:31", + "saved_at": "2026-03-17T18:30:37" + }, + "files": { + "speaker_recording": { + "path": "AI_Photographer/Data/Audio/countdown_intro.wav", + "name": "countdown_intro.wav", + "size_bytes": 432148, + "size_mb": 0.412, + "duration_seconds": 9.002, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + }, + "gemini_raw_output": { + "path": "AI_Photographer/Data/Audio/countdown_intro_raw.wav", + "name": "countdown_intro_raw.wav", + "size_bytes": 418604, + "size_mb": 0.399, + "duration_seconds": 8.72, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + } + } + }, + { + "record_name": "countdown_cancelled", + "text": "Countdown cancelled.", + "model": "models/gemini-2.5-flash-native-audio-preview-12-2025", + "voice_name": "Charon", + "replay_count": 1, + "audio_capture": { + "sink": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo", + "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor", + "restored_microphone_source": "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback", + "capture_device": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor" + }, + "timeline": { + "text_entered_at": "2026-03-13T14:46:33", + "audio_generated_at": "2026-03-13T14:46:36", + "last_playback_finished_at": "2026-03-13T14:46:37", + "saved_at": "2026-03-13T14:46:42" + }, + "files": { + "speaker_recording": { + "path": "AI_Photographer/Data/Audio/countdown_cancelled.wav", + "name": "countdown_cancelled.wav", + "size_bytes": 81050, + "size_mb": 0.077, + "duration_seconds": 1.688, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + }, + "gemini_raw_output": { + "path": "AI_Photographer/Data/Audio/countdown_cancelled_raw.wav", + "name": "countdown_cancelled_raw.wav", + "size_bytes": 67244, + "size_mb": 0.064, + "duration_seconds": 1.4, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + } + } + }, + { + "record_name": "lost_from_frame", + "text": "I lost you from the frame. Let us try again.", + "model": "models/gemini-2.5-flash-native-audio-preview-12-2025", + "voice_name": "Charon", + "replay_count": 1, + "audio_capture": { + "sink": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo", + "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor", + "restored_microphone_source": "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback", + "capture_device": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor" + }, + "timeline": { + "text_entered_at": "2026-03-13T14:46:57", + "audio_generated_at": "2026-03-13T14:47:00", + "last_playback_finished_at": "2026-03-13T14:47:03", + "saved_at": "2026-03-13T14:47:11" + }, + "files": { + "speaker_recording": { + "path": "AI_Photographer/Data/Audio/lost_from_frame.wav", + "name": "lost_from_frame.wav", + "size_bytes": 166428, + "size_mb": 0.159, + "duration_seconds": 3.466, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + }, + "gemini_raw_output": { + "path": "AI_Photographer/Data/Audio/lost_from_frame_raw.wav", + "name": "lost_from_frame_raw.wav", + "size_bytes": 151724, + "size_mb": 0.145, + "duration_seconds": 3.16, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + } + } + }, + { + "record_name": "retake_recommended", + "text": "Photo captured. I recommend a retake. Say yes photo to retake, or no photo to keep this one.", + "model": "models/gemini-2.5-flash-native-audio-preview-12-2025", + "voice_name": "Charon", + "replay_count": 1, + "audio_capture": { + "sink": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo", + "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor", + "restored_microphone_source": "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback", + "capture_device": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor" + }, + "timeline": { + "text_entered_at": "2026-03-13T14:47:26", + "audio_generated_at": "2026-03-13T14:47:30", + "last_playback_finished_at": "2026-03-13T14:47:38", + "saved_at": "2026-03-13T14:47:41" + }, + "files": { + "speaker_recording": { + "path": "AI_Photographer/Data/Audio/retake_recommended.wav", + "name": "retake_recommended.wav", + "size_bytes": 355642, + "size_mb": 0.339, + "duration_seconds": 7.408, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + }, + "gemini_raw_output": { + "path": "AI_Photographer/Data/Audio/retake_recommended_raw.wav", + "name": "retake_recommended_raw.wav", + "size_bytes": 341804, + "size_mb": 0.326, + "duration_seconds": 7.12, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + } + } + }, + { + "record_name": "retake_yes", + "text": "Great. Let us retake. Hold your pose.", + "model": "models/gemini-2.5-flash-native-audio-preview-12-2025", + "voice_name": "Charon", + "replay_count": 1, + "audio_capture": { + "sink": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo", + "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor", + "restored_microphone_source": "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback", + "capture_device": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor" + }, + "timeline": { + "text_entered_at": "2026-03-13T14:47:58", + "audio_generated_at": "2026-03-13T14:48:01", + "last_playback_finished_at": "2026-03-13T14:48:04", + "saved_at": "2026-03-13T14:48:12" + }, + "files": { + "speaker_recording": { + "path": "AI_Photographer/Data/Audio/retake_yes.wav", + "name": "retake_yes.wav", + "size_bytes": 171242, + "size_mb": 0.163, + "duration_seconds": 3.567, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + }, + "gemini_raw_output": { + "path": "AI_Photographer/Data/Audio/retake_yes_raw.wav", + "name": "retake_yes_raw.wav", + "size_bytes": 157484, + "size_mb": 0.15, + "duration_seconds": 3.28, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + } + } + }, + { + "record_name": "retake_limit", + "text": "Retake limit reached. Keeping the current photo.", + "model": "models/gemini-2.5-flash-native-audio-preview-12-2025", + "voice_name": "Charon", + "replay_count": 2, + "audio_capture": { + "sink": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo", + "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor", + "restored_microphone_source": "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback", + "capture_device": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor" + }, + "timeline": { + "text_entered_at": "2026-03-13T14:48:28", + "audio_generated_at": "2026-03-13T14:48:31", + "last_playback_finished_at": "2026-03-13T14:48:43", + "saved_at": "2026-03-13T14:48:46" + }, + "files": { + "speaker_recording": { + "path": "AI_Photographer/Data/Audio/retake_limit.wav", + "name": "retake_limit.wav", + "size_bytes": 190862, + "size_mb": 0.182, + "duration_seconds": 3.975, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + }, + "gemini_raw_output": { + "path": "AI_Photographer/Data/Audio/retake_limit_raw.wav", + "name": "retake_limit_raw.wav", + "size_bytes": 176684, + "size_mb": 0.168, + "duration_seconds": 3.68, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + } + } + }, + { + "record_name": "photo_saved_thanks", + "text": "Thank you. Photo saved. Do not forget to check your photos.", + "model": "models/gemini-2.5-flash-native-audio-preview-12-2025", + "voice_name": "Charon", + "replay_count": 1, + "audio_capture": { + "sink": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo", + "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor", + "restored_microphone_source": "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback", + "capture_device": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor" + }, + "timeline": { + "text_entered_at": "2026-03-13T14:49:20", + "audio_generated_at": "2026-03-13T14:49:25", + "last_playback_finished_at": "2026-03-13T14:49:30", + "saved_at": "2026-03-13T14:49:42" + }, + "files": { + "speaker_recording": { + "path": "AI_Photographer/Data/Audio/photo_saved_thanks.wav", + "name": "photo_saved_thanks.wav", + "size_bytes": 217272, + "size_mb": 0.207, + "duration_seconds": 4.526, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + }, + "gemini_raw_output": { + "path": "AI_Photographer/Data/Audio/photo_saved_thanks_raw.wav", + "name": "photo_saved_thanks_raw.wav", + "size_bytes": 203564, + "size_mb": 0.194, + "duration_seconds": 4.24, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + } + } + }, + { + "record_name": "count_3", + "text": "Three.", + "model": "models/gemini-2.5-flash-native-audio-preview-12-2025", + "voice_name": "Charon", + "replay_count": 3, + "audio_capture": { + "sink": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo", + "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor", + "restored_microphone_source": "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback", + "capture_device": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor" + }, + "timeline": { + "text_entered_at": "2026-03-13T19:13:20", + "audio_generated_at": "2026-03-13T19:13:22", + "last_playback_finished_at": "2026-03-13T19:13:27", + "saved_at": "2026-03-13T19:13:31" + }, + "files": { + "speaker_recording": { + "path": "AI_Photographer/Data/Audio/count_3.wav", + "name": "count_3.wav", + "size_bytes": 44314, + "size_mb": 0.042, + "duration_seconds": 0.922, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + }, + "gemini_raw_output": { + "path": "AI_Photographer/Data/Audio/count_3_raw.wav", + "name": "count_3_raw.wav", + "size_bytes": 30764, + "size_mb": 0.029, + "duration_seconds": 0.64, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + } + } + }, + { + "record_name": "count_2", + "text": "Two.", + "model": "models/gemini-2.5-flash-native-audio-preview-12-2025", + "voice_name": "Charon", + "replay_count": 3, + "audio_capture": { + "sink": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo", + "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor", + "restored_microphone_source": "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback", + "capture_device": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor" + }, + "timeline": { + "text_entered_at": "2026-03-13T19:12:57", + "audio_generated_at": "2026-03-13T19:12:59", + "last_playback_finished_at": "2026-03-13T19:13:05", + "saved_at": "2026-03-13T19:13:08" + }, + "files": { + "speaker_recording": { + "path": "AI_Photographer/Data/Audio/count_2.wav", + "name": "count_2.wav", + "size_bytes": 41282, + "size_mb": 0.039, + "duration_seconds": 0.859, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + }, + "gemini_raw_output": { + "path": "AI_Photographer/Data/Audio/count_2_raw.wav", + "name": "count_2_raw.wav", + "size_bytes": 26924, + "size_mb": 0.026, + "duration_seconds": 0.56, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + } + } + }, + { + "record_name": "count_1", + "text": "One", + "model": "models/gemini-2.5-flash-native-audio-preview-12-2025", + "voice_name": "Charon", + "replay_count": 2, + "audio_capture": { + "sink": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo", + "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor", + "restored_microphone_source": "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback", + "capture_device": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor" + }, + "timeline": { + "text_entered_at": "2026-03-13T19:12:13", + "audio_generated_at": "2026-03-13T19:12:15", + "last_playback_finished_at": "2026-03-13T19:12:21", + "saved_at": "2026-03-13T19:12:24" + }, + "files": { + "speaker_recording": { + "path": "AI_Photographer/Data/Audio/count_1.wav", + "name": "count_1.wav", + "size_bytes": 44182, + "size_mb": 0.042, + "duration_seconds": 0.92, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + }, + "gemini_raw_output": { + "path": "AI_Photographer/Data/Audio/count_1_raw.wav", + "name": "count_1_raw.wav", + "size_bytes": 30764, + "size_mb": 0.029, + "duration_seconds": 0.64, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + } + } + }, + { + "record_name": "smile", + "text": "Smile.", + "model": "models/gemini-2.5-flash-native-audio-preview-12-2025", + "voice_name": "Charon", + "replay_count": 1, + "audio_capture": { + "sink": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo", + "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor", + "restored_microphone_source": "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback", + "capture_device": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor" + }, + "timeline": { + "text_entered_at": "2026-03-13T19:11:35", + "audio_generated_at": "2026-03-13T19:11:38", + "last_playback_finished_at": "2026-03-13T19:11:39", + "saved_at": "2026-03-13T19:11:49" + }, + "files": { + "speaker_recording": { + "path": "AI_Photographer/Data/Audio/smile.wav", + "name": "smile.wav", + "size_bytes": 65728, + "size_mb": 0.063, + "duration_seconds": 1.368, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + }, + "gemini_raw_output": { + "path": "AI_Photographer/Data/Audio/smile_raw.wav", + "name": "smile_raw.wav", + "size_bytes": 51884, + "size_mb": 0.049, + "duration_seconds": 1.08, + "sample_rate": 24000, + "channels": 1, + "sample_width_bytes": 2 + } + } + } + ] +} \ No newline at end of file diff --git a/Data/Settings/config.json b/Data/Settings/config.json new file mode 100644 index 0000000..8e86872 --- /dev/null +++ b/Data/Settings/config.json @@ -0,0 +1,131 @@ +{ + "paths": { + "data_dir": "AI_Photographer/Data/G1", + "app_data_dir": "AI_Photographer/Data", + "app_settings_dir": "AI_Photographer/Data/Settings", + "app_scripts_dir": "AI_Photographer/Data/Scripts", + "app_runtime_dir": "AI_Photographer/Data/Runtime", + "app_notes_dir": "AI_Photographer/Data/Notes", + "audio_prompts_dir": "AI_Photographer/Data/Audio", + "audio_prompt_records_file": "AI_Photographer/Data/Settings/audio_prompt_records.json", + "scripts_dir": "AI_Photographer/Scripts", + "web_dir": "AI_Photographer/Web", + "photos_dir": "AI_Photographer/photos/Captures", + "people_dir": "AI_Photographer/photos/people", + "samples_dir": "AI_Photographer/photos/samples", + "replay_recordings_dir": "AI_Photographer/Data/G1", + "replay_recorder_script": "", + "home_file": "arm_home.jsonl", + "photo_phrases_file": "AI_Photographer/Data/Scripts/photo_command_ai.txt", + "sanad_script_file": "AI_Photographer/Data/Scripts/sanad_script.txt", + "runtime_health_file": "AI_Photographer/Data/Runtime/runtime_health.json", + "autonomous_state_file": "AI_Photographer/Data/Runtime/autonomous_state.json", + "upload_db": "AI_Photographer/Data/Runtime/upload_db.json" + }, + "timing": { + "photo_total_sec": 10.0, + "photo_thanks_sec": 3.0, + "photo_delay_sec": 5.0, + "replay_capture_end_margin_sec": 0.25, + "loop_rate": 10.0, + "ai_query_interval": 1.0 + }, + "server": { + "photo_server_port": 8080 + }, + "gemini": { + "api_key": "AIzaSyDt9Xi83MDZuuPpfwfHyMD92X7ZKdGkqf8", + "mic_enabled": true, + "model": "models/gemini-2.5-flash-native-audio-preview-12-2025", + "voice_name": "Charon", + "system_prompt_fallback": "You are Sanad (Bousandah), a friendly Emirati photographer assistant. Speak in UAE dialect (Khaleeji). Be short, energetic, and helpful." + }, + "upload": { + "method": "http", + "url": "", + "s3_bucket": "", + "s3_region": "", + "s3_key": "", + "s3_secret": "" + }, + "mode": { + "default_mode": "manual", + "current_mode": "manual" + }, + "replay": { + "active_file": "photo_G3.jsonl" + }, + "camera": { + "camera_index": 0, + "frame_width": 640, + "frame_height": 480, + "fps": 30, + "preferred_realsense_serial": "243622071722" + }, + "vision": { + "detection_backend": "yolo", + "yolo_runtime": "ultralytics", + "yolo_ultralytics_device": "cpu", + "person_yolo_onnx": "Models/person.pt", + "face_yolo_onnx": "", + "input_size": 640, + "person_class_id": 0, + "person_score_thresh": 0.35, + "face_score_thresh": 0.35, + "nms_iou_thresh": 0.45, + "group_min_people": 3, + "group_link_distance_px": 220.0, + "yolo_strict_required": true, + "gemini_context_hz": 8.0, + "gemini_context_silent": true, + "idle_voice_listen_enabled": true, + "hard_target_lock_enabled": true, + "retake_prompt_enabled": true, + "autonomous_greeting_replay_enabled": true, + "autonomous_greeting_replay_file": "right_hand_up.jsonl", + "autonomous_capture_replay_enabled": true, + "retake_max_per_session": 1, + "framing_headroom_min_ratio": 0.06, + "framing_headroom_max_ratio": 0.25, + "framing_eye_line_min_ratio": 0.28, + "framing_eye_line_max_ratio": 0.48, + "framing_retake_score_threshold": 0.68, + "face_recognition_enabled": true, + "face_recognition_threshold": 0.88 + }, + "watchdog": { + "ws_initial_backoff_sec": 1.0, + "ws_max_backoff_sec": 20.0, + "component_restart_delay_sec": 1.0, + "camera_capture_retry_count": 2, + "camera_capture_retry_delay_sec": 0.8 + }, + "audio_prompts": { + "mode": "audio", + "fallback_to_gemini": true, + "files": { + "welcome_single": "welcome_single.wav", + "welcome_group": "welcome_group.wav", + "welcome_returning": "welcome_returning.wav", + "frame_single": "frame_single.wav", + "frame_group": "frame_group.wav", + "confirm_reminder": "confirm_reminder.wav", + "visitor_left": "visitor_left.wav", + "declined": "declined.wav", + "confirm_timeout": "confirm_timeout.wav", + "session_cancelled": "session_cancelled.wav", + "framing_timeout": "framing_timeout.wav", + "countdown_intro": "countdown_intro.wav", + "count_3": "count_3.wav", + "count_2": "count_2.wav", + "count_1": "count_1.wav", + "smile": "smile.wav", + "countdown_cancelled": "countdown_cancelled.wav", + "lost_from_frame": "lost_from_frame.wav", + "retake_recommended": "retake_recommended.wav", + "retake_yes": "retake_yes.wav", + "retake_limit": "retake_limit.wav", + "photo_saved_thanks": "photo_saved_thanks.wav" + } + } +} diff --git a/Gemini/__init__.py b/Gemini/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/Gemini/gemini_voice.py b/Gemini/gemini_voice.py new file mode 100644 index 0000000..39c1260 --- /dev/null +++ b/Gemini/gemini_voice.py @@ -0,0 +1,823 @@ +# gemini_voice.py +import asyncio +import base64 +import json +import time +import array +import audioop +import inspect +import os +import re +import wave +from pathlib import Path + +import pyaudio +import websockets +from Core import settings as config +from Core import audio_prompts +from Gemini.sanad_text_utils import load_phrase_map, _norm_ar +from Core.Logger import Logs + +FORMAT = pyaudio.paInt16 +CHANNELS = 1 +SEND_SAMPLE_RATE = 16000 +RECEIVE_SAMPLE_RATE = 24000 +CHUNK_SIZE = 512 + + + + +class HamadGeminiVoice: + def __init__( + self, + photo_phrases_file: str = "photo_command_ai.txt", + ): + self.sanad_logger = Logs() + self.sanad_logger.LogEngine("G1_Logs", "gemini_voice") + + + self.audio_q = asyncio.Queue() + self.speaking = False + self.interrupted = False + self.pya = pyaudio.PyAudio() + self.mic_frames_per_buffer = CHUNK_SIZE + self.speaker_frames_per_buffer = CHUNK_SIZE + + self.MIN_THRESHOLD = 3000 + self.barge_in_threshold = 3000 + self.REQUIRED_LOUD_CHUNKS = 5 + + self.PREBUFFER_CHUNKS = max(1, int(os.environ.get("GEMINI_PREBUFFER_CHUNKS", "4"))) + self.PLAYBACK_TIMEOUT = max(0.1, float(os.environ.get("GEMINI_PLAYBACK_TIMEOUT", "0.35"))) + self.BARGE_IN_COOLDOWN = 0.7 + self.AI_SPEAK_GRACE = 0.25 + + self._last_ai_audio_time = 0.0 + self._ai_speaking_since = 0.0 + self._barge_in_block_until = 0.0 + + self.ECHO_GUARD_SEC = 0.8 + self._ignore_input_until = 0.0 + self.SEND_SILENCE_WHEN_SPEAKING = True + self.SPEAKING_ENERGY_GATE = 0.85 + self._silence_pcm = b"\x00" * (CHUNK_SIZE * 2) + self._photo_phrases_file = photo_phrases_file + self._photo_command_map = None + self.audio_gate_open = bool(int(os.environ.get("AUDIO_GATE_OPEN_ON_START", "1"))) + self.passive_listen_only = False + self._cmd_last_ts = {} + self.command_cooldown_sec = float(os.environ.get("VOICE_COMMAND_COOLDOWN_SEC", "1.2")) + self.device_restart_delay_sec = float(os.environ.get("AUDIO_DEVICE_RESTART_DELAY_SEC", "1.0")) + self.require_final_command = bool(int(os.environ.get("VOICE_CMDS_REQUIRE_FINAL", "1"))) + self.context_silent_default = bool(config.read_vision_gemini_context_silent()) + self.context_suppress_window_sec = float(os.environ.get("GEMINI_CONTEXT_SUPPRESS_WINDOW_SEC", "1.2")) + self.prompt_audio_allow_sec = float(os.environ.get("GEMINI_PROMPT_AUDIO_ALLOW_SEC", "15.0")) + self.user_turn_audio_allow_sec = float(os.environ.get("GEMINI_USER_TURN_ALLOW_SEC", "8.0")) + self._vision_context_seq = 0 + self._context_suppress_until = 0.0 + self._prompt_audio_allow_until = 0.0 + self._last_user_transcript_ts = 0.0 + self._last_context_drop_log_ts = 0.0 + self._last_audio_drop_log_ts = 0.0 + self._last_transcript_log_text = "" + self._last_transcript_log_ts = 0.0 + self._speaker_queue_drop_count = 0 + self._ws = None + self._ws_seq = 0 + self._ws_event = asyncio.Event() + self._prompt_play_lock = asyncio.Lock() + self._health = { + "ws_connected": False, + "ws_state": "detached", + "ws_restarts": 0, + "ws_last_error": "", + "ws_last_event_ts": 0.0, + "ws_last_reason": "", + "mic_state": "idle", + "mic_restarts": 0, + "mic_last_error": "", + "mic_last_event_ts": 0.0, + "speaker_state": "idle", + "speaker_restarts": 0, + "speaker_last_error": "", + "speaker_last_event_ts": 0.0, + "speaker_queue_drops": 0, + "speaker_queue_max": 0, + } + self._component_restart_delay_sec = float(config.read_watchdog_component_restart_delay_sec()) + self._log_audio_device_summary() + + def _log_user_transcript(self, text: str, is_final: bool, mode: str): + txt = str(text or "").strip() + if not txt: + return + now = time.time() + if is_final and txt == self._last_transcript_log_text and (now - self._last_transcript_log_ts) < 1.0: + return + self._last_transcript_log_text = txt + self._last_transcript_log_ts = now + state = "final" if is_final else "partial" + self.sanad_logger.print_and_log( + f"๐ŸŽค Heard ({state}, mode={mode}): {txt}", + message_type="info", + ) + + def _log_audio_device_summary(self): + try: + in_info = self.pya.get_default_input_device_info() + except Exception: + in_info = None + try: + out_info = self.pya.get_default_output_device_info() + except Exception: + out_info = None + + def _fmt(info: dict | None) -> str: + if not info: + return "unavailable" + name = str(info.get("name", "unknown")) + idx = info.get("index", "?") + rate = info.get("defaultSampleRate", "?") + return f"{name} (index={idx}, rate={rate})" + + self.sanad_logger.print_and_log(f"๐ŸŽค PortAudio input: {_fmt(in_info)}", message_type="info") + self.sanad_logger.print_and_log(f"๐Ÿ”ˆ PortAudio output: {_fmt(out_info)}", message_type="info") + + def set_audio_gate(self, enabled: bool, reason: str = ""): + self.audio_gate_open = bool(enabled) + state = "OPEN" if self.audio_gate_open else "CLOSED" + suffix = f" ({reason})" if reason else "" + self.sanad_logger.print_and_log(f"๐ŸŽง Audio gate {state}{suffix}", message_type="info") + + def set_passive_listen(self, enabled: bool, reason: str = ""): + self.passive_listen_only = bool(enabled) + state = "ON" if self.passive_listen_only else "OFF" + suffix = f" ({reason})" if reason else "" + self.sanad_logger.print_and_log(f"๐Ÿฆป Passive listen {state}{suffix}", message_type="info") + + def attach_ws(self, ws): + if ws is None: + return + self._ws = ws + self._ws_seq += 1 + self._ws_event.set() + self._health["ws_connected"] = True + self._health["ws_state"] = "connected" + self._health["ws_last_event_ts"] = time.time() + self._health["ws_last_reason"] = "attach" + if self._ws_seq > 1: + self._health["ws_restarts"] = int(self._health.get("ws_restarts", 0)) + 1 + + def detach_ws(self, reason: str = ""): + old_ws = self._ws + self._ws = None + self._ws_event.clear() + self._health["ws_connected"] = False + self._health["ws_state"] = "detached" + self._health["ws_last_event_ts"] = time.time() + self._health["ws_last_reason"] = str(reason or "") + if reason: + self._health["ws_last_error"] = str(reason) + try: + if old_ws is not None: + asyncio.create_task(old_ws.close()) + except Exception: + pass + + def is_ws_connected(self) -> bool: + ws = self._ws + return ws is not None + + async def _wait_for_ws(self, timeout_sec: float | None = None): + ws = self._ws + if ws is not None: + return ws + if timeout_sec is None: + await self._ws_event.wait() + return self._ws + if timeout_sec <= 0: + return None + try: + await asyncio.wait_for(self._ws_event.wait(), timeout=timeout_sec) + except asyncio.TimeoutError: + return None + return self._ws + + def get_runtime_health(self) -> dict: + out = dict(self._health) + out["mic_enabled"] = bool(config.read_gemini_mic_enabled()) + out["audio_gate_open"] = bool(self.audio_gate_open) + out["passive_listen_only"] = bool(self.passive_listen_only) + out["speaking"] = bool(self.speaking) + out["interrupted"] = bool(self.interrupted) + out["speaker_queue_size"] = int(self.audio_q.qsize()) + out["time"] = time.time() + return out + + def _queue_model_audio(self, audio_bytes: bytes): + if not audio_bytes: + return + self.audio_q.put_nowait(audio_bytes) + + def _load_prompt_pcm(self, prompt_path: Path) -> tuple[bytes, float]: + with wave.open(str(prompt_path), "rb") as wav_file: + channels = int(wav_file.getnchannels()) + sample_width = int(wav_file.getsampwidth()) + frame_rate = int(wav_file.getframerate()) + raw = wav_file.readframes(wav_file.getnframes()) + + if channels < 1 or channels > 2: + raise ValueError(f"unsupported WAV channel count: {channels}") + + if sample_width != 2: + raw = audioop.lin2lin(raw, sample_width, 2) + sample_width = 2 + + if channels == 2: + raw = audioop.tomono(raw, sample_width, 0.5, 0.5) + channels = 1 + + if frame_rate != RECEIVE_SAMPLE_RATE: + raw, _ = audioop.ratecv(raw, sample_width, channels, frame_rate, RECEIVE_SAMPLE_RATE, None) + + duration_sec = len(raw) / float(sample_width * channels * RECEIVE_SAMPLE_RATE) if raw else 0.0 + return raw, max(0.0, duration_sec) + + async def _play_local_prompt_file(self, prompt_path: Path) -> bool: + async with self._prompt_play_lock: + try: + pcm, duration_sec = await asyncio.to_thread(self._load_prompt_pcm, prompt_path) + except Exception as e: + self.sanad_logger.print_and_log( + f"โš ๏ธ Prompt audio failed for {prompt_path.name}: {e}", + message_type="warning", + ) + return False + + if not pcm: + return False + + now = time.time() + self.interrupted = False + self.speaking = True + self._ai_speaking_since = now + self._last_ai_audio_time = now + self._ignore_input_until = now + duration_sec + self.ECHO_GUARD_SEC + self._prompt_audio_allow_until = max(self._prompt_audio_allow_until, now + duration_sec + 1.0) + self.sanad_logger.print_and_log( + f"๐Ÿ”Š Prompt audio: {prompt_path.name}", + message_type="info", + ) + + chunk_bytes = max(self.speaker_frames_per_buffer * 2, 4096) + for i in range(0, len(pcm), chunk_bytes): + self._queue_model_audio(pcm[i:i + chunk_bytes]) + + deadline = time.time() + max(2.0, duration_sec + 2.0) + while time.time() < deadline: + if self.audio_q.empty() and not self.speaking: + break + await asyncio.sleep(0.05) + return True + + async def play_prompt_key( + self, + key: str, + fallback_text: str = "", + allow_gemini_fallback: bool | None = None, + wait_timeout_sec: float = 0.0, + mode_override: str | None = None, + ) -> bool: + prompt_mode = str(mode_override or config.read_audio_prompt_mode()).strip().lower() + if prompt_mode not in ("audio", "gemini"): + prompt_mode = "audio" + allow_fallback = ( + config.read_audio_prompts_fallback_to_gemini() + if allow_gemini_fallback is None + else bool(allow_gemini_fallback) + ) + try: + prompt_path = audio_prompts.prompt_path(key) + except Exception as e: + self.sanad_logger.print_and_log(f"โš ๏ธ Unknown prompt key {key}: {e}", message_type="warning") + prompt_path = None + + if prompt_mode == "gemini" and fallback_text: + return await self.send_text_prompt_live(fallback_text, wait_timeout_sec=wait_timeout_sec) + + if prompt_path is not None and prompt_path.exists(): + played = await self._play_local_prompt_file(prompt_path) + if played: + return True + + if fallback_text and allow_fallback: + return await self.send_text_prompt_live(fallback_text, wait_timeout_sec=wait_timeout_sec) + return False + + async def trigger_wake_sequence(self, ws=None, wake_text: str | None = None, prompt_key: str | None = None): + """ + Open mic gate and inject a context prompt so Gemini speaks first. + """ + self.set_audio_gate(True, reason="interaction triggered") + prompt = ( + wake_text + or "A tourist has just approached you. Warmly greet them and ask if they would like to take a photo." + ) + if prompt_key: + played = await self.play_prompt_key(prompt_key, fallback_text=prompt) + if played: + return + if ws is not None: + await self.send_text_prompt(ws, prompt) + else: + await self.send_text_prompt_live(prompt) + + def _should_suppress_model_audio(self, now_ts: float) -> bool: + if self.passive_listen_only: + return True + if now_ts <= self._prompt_audio_allow_until: + return False + if (now_ts - self._last_user_transcript_ts) <= self.user_turn_audio_allow_sec: + return False + return now_ts <= self._context_suppress_until + + def _command_allowed_now(self, cmd: str) -> bool: + now = time.time() + last = float(self._cmd_last_ts.get(cmd, 0.0)) + if (now - last) < self.command_cooldown_sec: + return False + self._cmd_last_ts[cmd] = now + return True + + def _write_flag(self, flag_name: str, label: str): + try: + p = config.SCRIPTS_DIR / flag_name + p.write_text(str(time.time())) + self.sanad_logger.print_and_log(f"๐Ÿ“ฉ {label} flag written", message_type="info") + except Exception as e: + self.sanad_logger.print_and_log(f"โŒ Failed to write {label} flag: {e}", message_type="error") + + def _mode_value(self) -> str: + try: + mode = str(config.read_runtime_mode()).strip().lower() + except Exception: + mode = "manual" + if mode not in ("manual", "ai"): + mode = "manual" + return mode + + def _match_in_mapping(self, text: str, mapping: dict | None): + norm = _norm_ar(str(text or "")) + if not norm or not mapping: + return None + + # Exact phrase first. + cmd = mapping.get(norm) + if cmd: + return cmd + + norm_padded = f" {norm} " + norm_nospace = norm.replace(" ", "") + # Longest aliases first to avoid matching short words prematurely. + for phrase, mapped in sorted(mapping.items(), key=lambda kv: len(kv[0]), reverse=True): + p = str(phrase or "").strip() + if not p: + continue + if f" {p} " in norm_padded: + return mapped + # Arabic/compact forms fallback. + p_nospace = p.replace(" ", "") + if p_nospace and p_nospace in norm_nospace: + return mapped + try: + if " " in p and re.search(rf"\b{re.escape(p)}\b", norm): + return mapped + except Exception: + pass + return None + + def _match_photo_command_from_text(self, text: str): + if self._photo_command_map is None: + self._photo_command_map = load_phrase_map(self._photo_phrases_file) + return self._match_in_mapping(text, self._photo_command_map) + + def _extract_user_transcripts(self, response: dict, server_content: dict): + out = [] + candidates = [ + response.get("inputAudioTranscription"), + response.get("inputTranscription"), + server_content.get("inputAudioTranscription"), + server_content.get("inputTranscription"), + ] + for item in candidates: + if item is None: + continue + if isinstance(item, str): + out.append((item, True)) + continue + if isinstance(item, dict): + txt = item.get("text") or item.get("transcript") or item.get("content") + is_final = item.get("isFinal") + if is_final is None: + is_final = item.get("final") + if is_final is None: + is_final = item.get("done") + if txt: + out.append((str(txt), True if is_final is None else bool(is_final))) + parts = item.get("parts") + if isinstance(parts, list): + for p in parts: + if isinstance(p, dict): + t = p.get("text") + if t: + out.append((str(t), True)) + elif isinstance(item, list): + for it in item: + if isinstance(it, str): + out.append((it, True)) + elif isinstance(it, dict): + t = it.get("text") or it.get("transcript") + if t: + out.append((str(t), bool(it.get("isFinal", True)))) + return out + + async def _handle_user_transcript(self, text: str, is_final: bool): + now = time.time() + self._last_user_transcript_ts = now + self._prompt_audio_allow_until = max(self._prompt_audio_allow_until, now + self.user_turn_audio_allow_sec) + + mode = self._mode_value() + self._log_user_transcript(text, is_final=bool(is_final), mode=mode) + + if self.require_final_command and (not is_final): + return + + if mode == "manual": + return + + photo_cmd = self._match_photo_command_from_text(text) + if photo_cmd: + self.sanad_logger.print_and_log( + f"๐Ÿง  Command match: {photo_cmd}", + message_type="info", + ) + if not self._command_allowed_now(photo_cmd): + return + + if photo_cmd == "no_photo": + self._write_flag("confirm_no.flag", "No photo") + else: + self._write_flag( + "confirm_yes.flag", + "Yes photo" if photo_cmd == "yes_photo" else "Photo request", + ) + if photo_cmd == "request_photo": + self._write_flag("request_photo.flag", "Photo request") + return + + def audio_energy(self, pcm): + try: + samples = array.array("h", pcm) + if not samples: + return 0 + return sum(abs(s) for s in samples) // len(samples) + except Exception: + return 0 + + def calibrate_mic(self): + self.sanad_logger.print_and_log("\n๐Ÿคซ Calibrating Microphone... (Please remain silent)", message_type="info") + try: + stream = self.pya.open( + format=FORMAT, + channels=CHANNELS, + rate=SEND_SAMPLE_RATE, + input=True, + frames_per_buffer=self.mic_frames_per_buffer, + ) + values = [] + for _ in range(40): + data = stream.read(CHUNK_SIZE, exception_on_overflow=False) + values.append(self.audio_energy(data)) + + stream.stop_stream() + stream.close() + + avg_noise = sum(values) / len(values) + self.barge_in_threshold = max(self.MIN_THRESHOLD, avg_noise * 3.0) + + self.sanad_logger.print_and_log(f"โœ… Baseline Noise: {avg_noise:.1f}", message_type="info") + self.sanad_logger.print_and_log(f"โœ… Interruption Threshold: {self.barge_in_threshold:.1f}", message_type="info") + except Exception as e: + self.sanad_logger.print_and_log(f"โš ๏ธ Calibration failed: {e}. Using default threshold.", message_type="warning") + + def _ws_connect_kwargs(self): + kwargs = {"max_size": None} + try: + sig = inspect.signature(websockets.connect) + if "extra_headers" in sig.parameters: + kwargs["extra_headers"] = {"Content-Type": "application/json"} + else: + kwargs["additional_headers"] = {"Content-Type": "application/json"} + except Exception: + kwargs["extra_headers"] = {"Content-Type": "application/json"} + return kwargs + + async def send_text_prompt(self, ws, text: str, allow_speech: bool = True): + msg = { + "clientContent": { + "turns": [{"role": "user", "parts": [{"text": text}]}], + "turnComplete": True + } + } + await ws.send(json.dumps(msg)) + if allow_speech: + self._prompt_audio_allow_until = max(self._prompt_audio_allow_until, time.time() + self.prompt_audio_allow_sec) + + async def send_text_prompt_live(self, text: str, allow_speech: bool = True, wait_timeout_sec: float = 0.0) -> bool: + ws = await self._wait_for_ws(timeout_sec=wait_timeout_sec) + if ws is None: + return False + try: + await self.send_text_prompt(ws, text, allow_speech=allow_speech) + return True + except Exception as e: + self.detach_ws(reason=f"send_text_prompt_live failed: {e}") + return False + + async def send_vision_context(self, ws, context: dict, silent: bool | None = None): + if silent is None: + silent = bool(self.context_silent_default) + self._vision_context_seq += 1 + seq = self._vision_context_seq + payload = dict(context or {}) + payload["context_seq"] = seq + payload["context_type"] = "vision" + + if silent: + text = ( + "SILENT_VISION_CONTEXT. Internal grounding update only; do not speak and do not produce audio. " + f"Use this context silently. Payload JSON: {json.dumps(payload, ensure_ascii=False)}" + ) + else: + text = f"VISION_CONTEXT_UPDATE: {json.dumps(payload, ensure_ascii=False)}" + + await self.send_text_prompt(ws, text, allow_speech=not silent) + if silent: + self._context_suppress_until = max( + self._context_suppress_until, + time.time() + max(0.2, self.context_suppress_window_sec), + ) + + async def send_vision_context_live(self, context: dict, silent: bool | None = None, wait_timeout_sec: float = 0.0) -> bool: + ws = await self._wait_for_ws(timeout_sec=wait_timeout_sec) + if ws is None: + return False + try: + await self.send_vision_context(ws, context=context, silent=silent) + return True + except Exception as e: + self.detach_ws(reason=f"send_vision_context_live failed: {e}") + return False + + async def keepalive(self, ws=None, every_sec: float = 20.0): + """ + Prevent idle disconnects: periodically send a websocket ping. + """ + while True: + try: + await asyncio.sleep(every_sec) + active_ws = self._ws + if active_ws is None: + continue + await active_ws.ping() + except asyncio.CancelledError: + raise + except Exception as e: + self.detach_ws(reason=f"keepalive ping failed: {e}") + await asyncio.sleep(self._component_restart_delay_sec) + + async def capture_mic(self, ws=None): + loud_chunks = 0 + while True: + stream = None + try: + while not self.audio_gate_open: + self._health["mic_state"] = "idle" + self._health["mic_last_event_ts"] = time.time() + await asyncio.sleep(0.1) + + self._health["mic_state"] = "starting" + self._health["mic_last_event_ts"] = time.time() + stream = await asyncio.to_thread( + self.pya.open, + format=FORMAT, + channels=CHANNELS, + rate=SEND_SAMPLE_RATE, + input=True, + frames_per_buffer=self.mic_frames_per_buffer, + ) + self._health["mic_state"] = "running" + self._health["mic_last_event_ts"] = time.time() + + while True: + data = await asyncio.to_thread(stream.read, CHUNK_SIZE, exception_on_overflow=False) + energy = self.audio_energy(data) + now = time.time() + + if not self.audio_gate_open: + continue + + if self.speaking and (now >= self._barge_in_block_until): + if (now - self._ai_speaking_since) >= self.AI_SPEAK_GRACE: + loud_chunks = loud_chunks + 1 if energy > self.barge_in_threshold else 0 + if loud_chunks > self.REQUIRED_LOUD_CHUNKS: + self.sanad_logger.print_and_log(f"๐Ÿ›‘ Interruption! (Energy: {energy})", message_type="warning") + self.interrupted = True + self.speaking = False + loud_chunks = 0 + self._barge_in_block_until = now + self.BARGE_IN_COOLDOWN + while not self.audio_q.empty(): + try: + self.audio_q.get_nowait() + except asyncio.QueueEmpty: + break + + data_to_send = data + if self.SEND_SILENCE_WHEN_SPEAKING and self.speaking: + gate = self.barge_in_threshold * self.SPEAKING_ENERGY_GATE + if energy < gate: + data_to_send = self._silence_pcm + + b64_audio = base64.b64encode(data_to_send).decode("utf-8") + msg = { + "realtime_input": { + "media_chunks": [{ + "data": b64_audio, + "mime_type": f"audio/pcm;rate={SEND_SAMPLE_RATE}", + }] + } + } + active_ws = self._ws + if active_ws is None: + continue + try: + await active_ws.send(json.dumps(msg)) + except websockets.exceptions.ConnectionClosed as e: + self.detach_ws(reason=f"mic send ws closed: {e}") + await asyncio.sleep(self._component_restart_delay_sec) + except Exception as e: + self.detach_ws(reason=f"mic send ws error: {e}") + await asyncio.sleep(self._component_restart_delay_sec) + + except asyncio.CancelledError: + raise + except Exception as e: + self.sanad_logger.print_and_log(f"โŒ Mic Error: {e} (restarting mic)", message_type="warning") + self._health["mic_state"] = "error" + self._health["mic_restarts"] = int(self._health.get("mic_restarts", 0)) + 1 + self._health["mic_last_error"] = str(e) + self._health["mic_last_event_ts"] = time.time() + await asyncio.sleep(max(self.device_restart_delay_sec, self._component_restart_delay_sec)) + finally: + if stream is not None: + try: + await asyncio.to_thread(stream.stop_stream) + except Exception: + pass + try: + await asyncio.to_thread(stream.close) + except Exception: + pass + if self._health.get("mic_state") != "error": + self._health["mic_state"] = "restarting" + self._health["mic_last_event_ts"] = time.time() + + async def receive_audio(self, ws=None): + while True: + active_ws = self._ws + if active_ws is None: + await asyncio.sleep(0.05) + continue + try: + msg = await active_ws.recv() + except asyncio.CancelledError: + raise + except websockets.exceptions.ConnectionClosed as e: + self.detach_ws(reason=f"receive ws closed: {e}") + await asyncio.sleep(self._component_restart_delay_sec) + continue + except Exception as e: + self.detach_ws(reason=f"receive ws error: {e}") + await asyncio.sleep(self._component_restart_delay_sec) + continue + + try: + response = json.loads(msg) + server_content = response.get("serverContent", {}) + + if server_content.get("interrupted"): + self.interrupted = False + + if self.interrupted: + continue + + # Safety: map commands from USER transcription events (not model text). + try: + transcripts = self._extract_user_transcripts(response, server_content) + for txt, is_final in transcripts: + await self._handle_user_transcript(txt, is_final=bool(is_final)) + except Exception as e: + self.sanad_logger.print_and_log(f"โš ๏ธ Transcript parse warning: {e}", message_type="warning") + + model_turn = server_content.get("modelTurn") + if model_turn: + for part in model_turn.get("parts", []): + inline_data = part.get("inlineData") + if inline_data and inline_data.get("data"): + now = time.time() + if self._should_suppress_model_audio(now): + if (now - self._last_context_drop_log_ts) >= 5.0: + self._last_context_drop_log_ts = now + self.sanad_logger.print_and_log( + "๐Ÿคซ Suppressed unsolicited model audio from context-only turn.", + message_type="info", + ) + continue + if not self.speaking: + self._ai_speaking_since = now + self.sanad_logger.print_and_log("๐Ÿ”Š Gemini audio response started.", message_type="info") + self.speaking = True + self._last_ai_audio_time = now + self._ignore_input_until = now + self.ECHO_GUARD_SEC + + audio_bytes = base64.b64decode(inline_data["data"]) + self._queue_model_audio(audio_bytes) + + except Exception as e: + self.sanad_logger.print_and_log(f"โŒ Parse Error: {e}", message_type="error") + + async def play_audio(self): + while True: + stream = None + buffered = False + try: + self._health["speaker_state"] = "starting" + self._health["speaker_last_event_ts"] = time.time() + stream = await asyncio.to_thread( + self.pya.open, + format=FORMAT, + channels=CHANNELS, + rate=RECEIVE_SAMPLE_RATE, + output=True, + frames_per_buffer=self.speaker_frames_per_buffer, + ) + self._health["speaker_state"] = "running" + self._health["speaker_last_event_ts"] = time.time() + + while True: + if self.interrupted: + await asyncio.sleep(0.01) + continue + + if self.speaking and not buffered: + while self.audio_q.qsize() < self.PREBUFFER_CHUNKS and self.speaking and not self.interrupted: + await asyncio.sleep(0.01) + buffered = True + + try: + data = await asyncio.wait_for(self.audio_q.get(), timeout=self.PLAYBACK_TIMEOUT) + except asyncio.TimeoutError: + if self.audio_q.empty() and (time.time() - self._last_ai_audio_time) > 0.25: + self.speaking = False + buffered = False + continue + + if data: + await asyncio.to_thread(stream.write, data) + + if self.audio_q.empty() and (time.time() - self._last_ai_audio_time) > 0.25: + self.speaking = False + buffered = False + + except asyncio.CancelledError: + raise + except Exception as e: + self.sanad_logger.print_and_log(f"โŒ Speaker Error: {e} (restarting speaker)", message_type="warning") + self._health["speaker_state"] = "error" + self._health["speaker_restarts"] = int(self._health.get("speaker_restarts", 0)) + 1 + self._health["speaker_last_error"] = str(e) + self._health["speaker_last_event_ts"] = time.time() + await asyncio.sleep(max(self.device_restart_delay_sec, self._component_restart_delay_sec)) + finally: + if stream is not None: + try: + await asyncio.to_thread(stream.stop_stream) + except Exception: + pass + try: + await asyncio.to_thread(stream.close) + except Exception: + pass + if self._health.get("speaker_state") != "error": + self._health["speaker_state"] = "restarting" + self._health["speaker_last_event_ts"] = time.time() diff --git a/Gemini/sanad_text_utils.py b/Gemini/sanad_text_utils.py new file mode 100644 index 0000000..cf63633 --- /dev/null +++ b/Gemini/sanad_text_utils.py @@ -0,0 +1,372 @@ +import ast +import os +import re +import time +import asyncio + +from Core import settings as config + +# ================================================== +# ๐Ÿ”ค Arabic & English normalization +# ================================================== + +def _norm_ar(s: str) -> str: + s = (s or "").strip().lower() + if not s: + return "" + + # Arabic punctuation: ุŸ ุŒ ุ› + s = re.sub(r"[\u061F\u060C\u061B]", " ", s) + + # โœ… Keep Arabic, English letters, word chars, and spaces + s = re.sub(r"[^\w\s\u0600-\u06FFa-zA-Z]", " ", s) + + # collapse spaces + s = re.sub(r"\s+", " ", s).strip() + + # normalize hamza/alif variants + s = s.replace("ุฃ", "ุง").replace("ุฅ", "ุง").replace("ุข", "ุง") + + # ta marbuta -> ha, alif maqsoora -> ya + s = s.replace("ุฉ", "ู‡").replace("ู‰", "ูŠ") + + # tatweel + s = s.replace("ู€", "") + + # common nickname normalization + s = s.replace("ุงุจูˆ", "ุจูˆ") + + return s.strip() + + +# ================================================== +# ๐Ÿ“‚ Load wake phrases from a python file (sanad_arm.txt) +# Modified to search the local Scripts folder if not found next to module +# ================================================== + +def load_arm_phrases(filename: str = "sanad_arm.txt", *, var_name: str = "WAKE_PHRASES") -> set[str]: + base_dir = os.path.dirname(os.path.abspath(__file__)) + + # Candidate locations (module dir, module dir / Scripts, parent / Scripts) + candidates = [ + os.path.join(base_dir, filename), + os.path.join(base_dir, "Scripts", filename), + os.path.join(base_dir, "..", "Scripts", filename), + ] + + arm_path = None + for c in candidates: + if os.path.exists(c): + arm_path = c + break + + if arm_path is None: + raise FileNotFoundError(f"Arm phrases file not found in candidates: {candidates}") + + print(f"๐Ÿ“‚ Loading arm phrases from: {arm_path} (var={var_name})") + + with open(arm_path, "r", encoding="utf-8-sig") as f: + raw = f.read() + + # Try to parse as python file (legacy format with WAKE_PHRASES variables). + # Uses ast.parse + ast.literal_eval instead of exec() for safety. + try: + tree = ast.parse(raw) + for node in ast.walk(tree): + if isinstance(node, ast.Assign): + for target in node.targets: + if isinstance(target, ast.Name) and target.id == var_name: + phrases = ast.literal_eval(node.value) + if isinstance(phrases, (set, list, tuple)): + out = {_norm_ar(str(p)) for p in phrases if str(p).strip()} + out = {p for p in out if p} + print(f"โœ… Loaded {len(out)} wake phrases from file variable: {var_name}") + return out + except Exception: + # fall through to plain text parsing + pass + + # Plain-text newline-separated phrases fallback + lines = [ln.strip() for ln in raw.splitlines()] + cand = [ln for ln in lines if ln and not ln.startswith("#")] + out = {_norm_ar(ln) for ln in cand} + out = {p for p in out if p} + print(f"โœ… Loaded {len(out)} wake phrases from plain text file: {arm_path}") + return out + + +# ================================================== +# ๐Ÿง  Wake phrase matching + scheduling +# ================================================== + +def _is_valid_text(s: str) -> bool: + # Allow Arabic OR English letters + has_ar = bool(re.search(r"[\u0600-\u06FF]", s or "")) + has_en = bool(re.search(r"[a-zA-Z]", s or "")) + return has_ar or has_en + + +def _strip_ya_prefix(s: str) -> str: + s = (s or "").strip() + if not s: + return "" + if s.startswith("ูŠุง "): + return s[3:].strip() + if s.startswith("ูŠุง"): + return s[2:].strip() + return s + + +def _remove_al_prefix_words(text: str) -> str: + if not text: + return "" + parts = text.split() + out = [] + for w in parts: + if w.startswith("ุงู„") and len(w) > 2: + out.append(w[2:]) + else: + out.append(w) + return " ".join(out).strip() + + +def _maybe_trigger_arm( + obj, + transcript_text: str, + wake_phrases: set[str], + *, + fire_on_wake_match: bool = False, + arm_trigger_fn=None, +) -> bool: + if not transcript_text or not wake_phrases: + return False + + # initialization of state variables (copied from original logic) + if not hasattr(obj, "_asr_buf"): + obj._asr_buf = "" + if not hasattr(obj, "_asr_last_time"): + obj._asr_last_time = 0.0 + if not hasattr(obj, "ASR_WINDOW_SEC"): + obj.ASR_WINDOW_SEC = 2.0 + if not hasattr(obj, "ASR_SHORT_TOKEN_BONUS_SEC"): + obj.ASR_SHORT_TOKEN_BONUS_SEC = 1.0 + if not hasattr(obj, "ASR_JOIN_NO_SPACE_MAXLEN"): + obj.ASR_JOIN_NO_SPACE_MAXLEN = 2 + if not hasattr(obj, "ASR_MAX_CHARS"): + obj.ASR_MAX_CHARS = 120 + + if not hasattr(obj, "_last_trigger_norm"): + obj._last_trigger_norm = "" + if not hasattr(obj, "_last_trigger_time"): + obj._last_trigger_time = 0.0 + if not hasattr(obj, "TRIGGER_DEDUP_WINDOW"): + obj.TRIGGER_DEDUP_WINDOW = 2.0 + + if not hasattr(obj, "_pending_arm_wave"): + obj._pending_arm_wave = False + if not hasattr(obj, "_pending_arm_wave_fired"): + obj._pending_arm_wave_fired = False + if not hasattr(obj, "_pending_arm_wave_set_time"): + obj._pending_arm_wave_set_time = 0.0 + if not hasattr(obj, "PENDING_ARM_TTL"): + obj.PENDING_ARM_TTL = 6.0 + + if not hasattr(obj, "_pending_arm_trigger_fn"): + obj._pending_arm_trigger_fn = None + if not hasattr(obj, "_pending_arm_fallback_time"): + obj._pending_arm_fallback_time = 0.0 + + if not hasattr(obj, "_last_piece_call_norm"): + obj._last_piece_call_norm = "" + if not hasattr(obj, "_last_piece_call_time"): + obj._last_piece_call_time = 0.0 + + if not hasattr(obj, "_asr_stream"): + obj._asr_stream = "" + if not hasattr(obj, "ASR_STREAM_MAX_CHARS"): + obj.ASR_STREAM_MAX_CHARS = 80 + + dup_call_window = float(getattr(obj, "DUP_CALL_WINDOW_SEC", 0.25)) + dup_asr_repeat_window = float(getattr(obj, "DUP_ASR_REPEAT_WINDOW_SEC", 0.9)) + pending_fallback_sec = float(getattr(obj, "PENDING_ARM_FALLBACK_SEC", 0.65)) + + piece_raw = (transcript_text or "").strip() + if not piece_raw: + return False + + piece_norm = _norm_ar(piece_raw) + if not piece_norm: + return False + + now = time.time() + + if not _is_valid_text(piece_norm): + return False + + duplicate_call = ( + (piece_norm == obj._last_piece_call_norm) + and ((now - obj._last_piece_call_time) < dup_call_window) + ) + + repeated_asr = ( + (piece_norm == obj._last_piece_call_norm) + and ((now - obj._last_piece_call_time) < dup_asr_repeat_window) + ) + + obj._last_piece_call_norm = piece_norm + obj._last_piece_call_time = now + + if not duplicate_call and not repeated_asr: + print(f"๐Ÿ“ USER SAID (raw): {piece_raw}") + print(f"๐Ÿ“ USER SAID (norm): {piece_norm}") + + if not duplicate_call and not repeated_asr: + if obj._asr_last_time: + gap = now - obj._asr_last_time + window = obj.ASR_WINDOW_SEC + if len(piece_norm) <= obj.ASR_JOIN_NO_SPACE_MAXLEN: + window += obj.ASR_SHORT_TOKEN_BONUS_SEC + if gap > window: + obj._asr_buf = "" + obj._asr_stream = "" + + obj._asr_last_time = now + + if obj._asr_buf: + if len(piece_norm) <= obj.ASR_JOIN_NO_SPACE_MAXLEN: + obj._asr_buf = (obj._asr_buf + piece_norm).strip() + else: + obj._asr_buf = (obj._asr_buf + " " + piece_norm).strip() + else: + obj._asr_buf = piece_norm + + compact = piece_norm.replace(" ", "") + obj._asr_stream = (obj._asr_stream + compact)[-obj.ASR_STREAM_MAX_CHARS :] + + if len(obj._asr_buf) > obj.ASR_MAX_CHARS: + obj._asr_buf = obj._asr_buf[-obj.ASR_MAX_CHARS :] + + buf_norm = _norm_ar(obj._asr_buf) + buf_nospace = buf_norm.replace(" ", "") + buf_noal = _remove_al_prefix_words(buf_norm) + buf_noal_nospace = buf_noal.replace(" ", "") + stream = _norm_ar(obj._asr_stream).replace(" ", "") + stream_noal = _remove_al_prefix_words(stream) + + if not duplicate_call and not repeated_asr: + print(f"๐Ÿงฉ ASR BUFFER: {buf_norm}") + + if ( + buf_norm == obj._last_trigger_norm + and (now - obj._last_trigger_time) < obj.TRIGGER_DEDUP_WINDOW + ): + return False + + for phrase in wake_phrases: + p_norm = _strip_ya_prefix(_norm_ar(str(phrase))) + if not p_norm: + continue + + p_nospace = p_norm.replace(" ", "") + p_noal = _remove_al_prefix_words(p_norm) + p_noal_nospace = p_noal.replace(" ", "") + + pattern = r'\b' + re.escape(p_norm) + r'\b' + hit_buf = bool(re.search(pattern, buf_norm)) or (p_nospace and p_nospace == buf_nospace) + hit_buf = hit_buf or (p_noal and (p_noal in buf_noal or (p_noal_nospace and p_noal_nospace in buf_noal_nospace))) + + hit_stream = False + if p_nospace and p_nospace in stream: + hit_stream = True + elif p_noal_nospace and p_noal_nospace in stream_noal: + hit_stream = True + + if hit_buf or hit_stream: + if hit_stream and not hit_buf: + print(f"โšก FAST MATCH: '{phrase}' (recent tokens)") + else: + print(f"โœ… MATCH: '{phrase}' in BUFFER='{obj._asr_buf}'") + + obj._last_trigger_norm = buf_norm + obj._last_trigger_time = now + + obj._asr_buf = "" + obj._asr_last_time = 0.0 + obj._asr_stream = "" + + if fire_on_wake_match: + if arm_trigger_fn: + asyncio.create_task(asyncio.to_thread(arm_trigger_fn)) + obj._pending_arm_wave = False + obj._pending_arm_wave_fired = False + obj._pending_arm_wave_set_time = 0.0 + obj._pending_arm_trigger_fn = None + obj._pending_arm_fallback_time = 0.0 + else: + obj._pending_arm_wave = True + obj._pending_arm_wave_fired = False + obj._pending_arm_wave_set_time = now + obj._pending_arm_trigger_fn = arm_trigger_fn + obj._pending_arm_fallback_time = now + pending_fallback_sec + + return True + + return False + + +# ================================================== +# ๐Ÿ” Phrase map loader (plain-text grouped format) +# Format: groups separated by blank lines. First line = canonical command, +# following lines = aliases. +_phrase_map_cache = {} + +def load_phrase_map(filename: str = "photo_command_ai.txt") -> dict: + base_dir = os.path.dirname(os.path.abspath(__file__)) + candidates = [ + str(config.PHOTO_PHRASES_FILE), + os.path.join(base_dir, filename), + os.path.join(base_dir, "Scripts", filename), + os.path.join(base_dir, "Data", filename), + os.path.join(base_dir, "..", "Data", "Scripts", filename), + os.path.join(base_dir, "..", "Scripts", filename), + os.path.join(base_dir, "..", "Data", filename), + ] + path = None + for c in candidates: + if os.path.exists(c): + path = c + break + if path is None: + return {} + + if path in _phrase_map_cache: + return _phrase_map_cache[path] + + with open(path, 'r', encoding='utf-8-sig') as f: + lines = [ln.rstrip() for ln in f.readlines()] + + groups = [] + cur = [] + for ln in lines: + s = ln.strip() + if not s: + if cur: + groups.append(cur) + cur = [] + continue + if s.startswith("#"): + continue + cur.append(s) + if cur: + groups.append(cur) + + mapping = {} + for g in groups: + cmd = g[0] + aliases = g + for a in aliases: + mapping[_norm_ar(a)] = cmd + + _phrase_map_cache[path] = mapping + print(f"โœ… Loaded phrase mapping from {path}: {len(mapping)} aliases") + return mapping diff --git a/Gemini/voice_sanad.py b/Gemini/voice_sanad.py new file mode 100644 index 0000000..903c4e6 --- /dev/null +++ b/Gemini/voice_sanad.py @@ -0,0 +1,463 @@ +#!/usr/bin/env python3 +""" +voice_sanad.py (PRODUCTION) +- Starts photo server ONCE and keeps it alive. +- Initializes DDS ONCE. +- Keeps core components alive (mic/speaker/receive/trigger/autonomous). +- Uses a dedicated WS supervisor loop that reconnects only the Gemini channel. +""" + +import asyncio +import json +import os +import random +import time +from pathlib import Path + +import websockets + +from Core.Logger import Logs + +from Core import settings as config +from Core.settings import ( + PHOTOS_DIR, + PHOTO_SERVER_PORT, + MODEL, + VOICE_NAME, + GEMINI_API_KEY, + PHOTO_TOTAL_SEC, + PHOTO_DELAY_SEC, + load_system_prompt, +) + +from Server.photo_server import start_photo_server +from Gemini.gemini_voice import HamadGeminiVoice + + +sanad_logger = Logs() +sanad_logger.LogEngine("G1_Logs", "voice_sanad") + +API_KEY = GEMINI_API_KEY.strip() +if not API_KEY: + raise RuntimeError(f"Gemini API key is empty. Set gemini.api_key in {config.CONFIG_JSON}.") + +URI = ( + "wss://generativelanguage.googleapis.com/ws/" + "google.ai.generativelanguage.v1alpha.GenerativeService.BidiGenerateContent" + f"?key={API_KEY}" +) + +RUNTIME_HEALTH_FILE = Path(config.RUNTIME_HEALTH_FILE) +INTERACTION_FLAG_FILE = Path(config.SCRIPTS_DIR) / "interaction_triggered.flag" + + +def _build_setup_message() -> dict: + system_prompt = load_system_prompt() + return { + "setup": { + "model": MODEL, + "generationConfig": { + "responseModalities": ["AUDIO"], + "speechConfig": { + "voiceConfig": {"prebuiltVoiceConfig": {"voiceName": VOICE_NAME}} + }, + }, + "inputAudioTranscription": {}, + "systemInstruction": {"parts": [{"text": system_prompt}]}, + } + } + + +def _read_runtime_mode_safe() -> str: + try: + mode = str(config.read_runtime_mode()).strip().lower() + except Exception: + mode = "manual" + return mode if mode in ("manual", "ai") else "manual" + + +def _interaction_active_now() -> bool: + try: + return INTERACTION_FLAG_FILE.exists() + except Exception: + return False + + +def _apply_idle_audio_policy(voice: HamadGeminiVoice, autonomous_enabled: bool): + runtime_mode = _read_runtime_mode_safe() + idle_voice_listen_enabled = bool(config.read_vision_idle_voice_listen_enabled()) + mic_enabled = bool(config.read_gemini_mic_enabled()) + + if not mic_enabled: + voice.set_passive_listen(False, reason="mic disabled") + voice.set_audio_gate(False, reason="mic disabled") + return + + if runtime_mode != "ai": + voice.set_passive_listen(False, reason=f"{runtime_mode} mode") + voice.set_audio_gate(True, reason=f"{runtime_mode} mode") + return + + if autonomous_enabled: + if idle_voice_listen_enabled: + voice.set_passive_listen(True, reason="autonomous idle") + voice.set_audio_gate(True, reason="autonomous idle listen") + else: + voice.set_passive_listen(False, reason="autonomous idle") + voice.set_audio_gate(False, reason="autonomous idle") + return + + voice.set_passive_listen(False, reason="ai mode") + voice.set_audio_gate(True, reason="ai mode") + + +async def _write_runtime_health_loop(voice: HamadGeminiVoice, interval_sec: float = 1.0): + while True: + try: + payload = voice.get_runtime_health() if hasattr(voice, "get_runtime_health") else {} + payload = dict(payload or {}) + payload["model"] = MODEL + payload["time"] = payload.get("time") or time.time() + RUNTIME_HEALTH_FILE.parent.mkdir(parents=True, exist_ok=True) + RUNTIME_HEALTH_FILE.write_text(json.dumps(payload, ensure_ascii=False), encoding="utf-8") + except Exception as e: + sanad_logger.print_and_log(f"Runtime health write failed: {e}", "warning") + await asyncio.sleep(max(0.2, float(interval_sec))) + + +async def _run_component_forever(name: str, coro_factory, restart_delay_sec: float): + while True: + try: + await coro_factory() + sanad_logger.print_and_log(f"โš ๏ธ {name} loop ended; restarting.", "warning") + except asyncio.CancelledError: + raise + except Exception as e: + sanad_logger.print_and_log(f"โŒ {name} loop error: {e}. Restarting.", "warning") + await asyncio.sleep(max(0.1, float(restart_delay_sec))) + + +async def _run_mode_policy_sync(voice: HamadGeminiVoice, autonomous_enabled: bool, interval_sec: float = 0.5): + last_signature = None + while True: + try: + await asyncio.sleep(max(0.2, float(interval_sec))) + if not voice.is_ws_connected(): + continue + runtime_mode = _read_runtime_mode_safe() + mic_enabled = bool(config.read_gemini_mic_enabled()) + idle_voice_listen_enabled = bool(config.read_vision_idle_voice_listen_enabled()) + signature = (runtime_mode, mic_enabled, idle_voice_listen_enabled, bool(autonomous_enabled)) + if not mic_enabled: + if signature != last_signature: + _apply_idle_audio_policy(voice, autonomous_enabled=autonomous_enabled) + last_signature = signature + continue + if _interaction_active_now(): + last_signature = signature + continue + if signature != last_signature: + _apply_idle_audio_policy(voice, autonomous_enabled=autonomous_enabled) + last_signature = signature + except asyncio.CancelledError: + raise + except Exception as e: + sanad_logger.print_and_log(f"โš ๏ธ Mode policy sync error: {e}", "warning") + + +async def _run_autonomous_forever(hub, replay, voice, restart_delay_sec: float): + from Modes.AI.autonomous_manager import AutonomousManager + + while True: + am = AutonomousManager() + try: + await am.run(hub=hub, replay=replay, voice=voice, ws=None) + sanad_logger.print_and_log("โš ๏ธ Autonomous manager exited; restarting.", "warning") + except asyncio.CancelledError: + try: + am.stop() + except Exception: + pass + raise + except Exception as e: + sanad_logger.print_and_log(f"โŒ Autonomous manager error: {e}. Restarting.", "warning") + await asyncio.sleep(max(0.2, float(restart_delay_sec))) + + +async def _run_ws_supervisor( + voice: HamadGeminiVoice, + autonomous_enabled: bool, + dashboard_url: str | None = None, + manual_lean_runtime: bool = False, +): + backoff = float(config.read_watchdog_ws_initial_backoff_sec()) + max_backoff = float(config.read_watchdog_ws_max_backoff_sec()) + + while True: + sanad_logger.print_and_log(f"\n๐Ÿš€ Connecting to Gemini ({MODEL})...", message_type="info") + ws = None + try: + async with websockets.connect(URI, **voice._ws_connect_kwargs()) as ws: + setup_msg = _build_setup_message() + await ws.send(json.dumps(setup_msg)) + await ws.recv() + + voice.attach_ws(ws) + backoff = float(config.read_watchdog_ws_initial_backoff_sec()) + _apply_idle_audio_policy(voice, autonomous_enabled=autonomous_enabled) + + sanad_logger.print_and_log("๐ŸŽ™๏ธ Connected! Sanad ready.", message_type="info") + if dashboard_url: + base_url = dashboard_url.rstrip("/") + sanad_logger.print_and_log(f"๐ŸŒ Dashboard: {base_url}/", "info") + sanad_logger.print_and_log(f"๐Ÿ“Š Runtime Health API: {base_url}/api/runtime_health", "info") + sanad_logger.print_and_log("๐Ÿ–ผ๏ธ Live Preview: OFF by default. Enable it from the dashboard when needed.", "info") + sanad_logger.print_and_log("๐Ÿ›ก๏ธ Idle behavior: no auto-shutdown on silence. Gemini WS keepalive is active.", "info") + if manual_lean_runtime: + sanad_logger.print_and_log("๐ŸŽฎ Manual lean runtime: voice conversation only. Restart in AI mode for replay/capture/autonomous services.", "info") + else: + sanad_logger.print_and_log("๐ŸŽฎ Controls:", "info") + sanad_logger.print_and_log(" - R2+X : Replay + Photographer Talk + Take Photo", "info") + sanad_logger.print_and_log(" - R2+L1: HARD CANCEL safety combo (AI/manual) -> cancel session/replay", "info") + + await ws.wait_closed() + except asyncio.CancelledError: + if ws is not None: + try: + await ws.close() + except Exception: + pass + raise + except websockets.exceptions.ConnectionClosed as e: + sanad_logger.print_and_log(f"โš ๏ธ WebSocket closed: {e}", message_type="warning") + except Exception as e: + sanad_logger.print_and_log(f"โŒ WS supervisor error: {e}", message_type="error") + finally: + voice.detach_ws(reason="ws supervisor disconnect") + + sleep_s = backoff + random.uniform(0.0, 0.8) + sanad_logger.print_and_log(f"๐Ÿ” Reconnecting in {sleep_s:.1f}s...", message_type="warning") + await asyncio.sleep(max(0.1, sleep_s)) + backoff = min(max_backoff, backoff * 1.7) + + +def _manual_lean_runtime_enabled(startup_mode: str) -> bool: + if startup_mode != "manual": + return False + raw = os.environ.get("MANUAL_LEAN_RUNTIME") + if raw is None or raw == "": + return False + return str(raw).strip().lower() in ("1", "true", "yes", "on", "y") + + +async def _run_autonomous_mode_supervisor(hub, replay, voice, restart_delay_sec: float, poll_sec: float = 0.5): + task = None + last_should_run = None + try: + while True: + should_run = _read_runtime_mode_safe() == "ai" + if should_run != last_should_run: + if should_run: + sanad_logger.print_and_log("๐Ÿค– AI mode active: starting autonomous manager.", "info") + else: + sanad_logger.print_and_log("๐Ÿค– Manual mode active: autonomous manager paused.", "info") + last_should_run = should_run + + if should_run: + if task is None or task.done(): + task = asyncio.create_task( + _run_autonomous_forever(hub=hub, replay=replay, voice=voice, restart_delay_sec=restart_delay_sec) + ) + elif task is not None: + task.cancel() + await asyncio.gather(task, return_exceptions=True) + task = None + + await asyncio.sleep(max(0.2, float(poll_sec))) + finally: + if task is not None: + task.cancel() + await asyncio.gather(task, return_exceptions=True) + + +async def main(): + startup_mode = _read_runtime_mode_safe() + autonomous_enabled = bool(int(os.environ.get("AUTONOMOUS_ENABLE", "0"))) + manual_lean_runtime = _manual_lean_runtime_enabled(startup_mode) + + hub = None + replay = None + dashboard_capture_func = None + dashboard_replay_test_func = None + + if manual_lean_runtime: + sanad_logger.print_and_log( + "๐Ÿชถ Manual lean runtime active: Gemini + dashboard only. DDS, replay, uploader, and teleimager-dependent startup are skipped.", + "info", + ) + + def _manual_capture_unavailable() -> str: + return "[ERR] Capture unavailable in manual lean runtime. Restart in AI mode for camera/replay services." + + dashboard_capture_func = _manual_capture_unavailable + else: + from unitree_sdk2py.core.channel import ChannelSubscriber, ChannelFactoryInitialize + from unitree_sdk2py.idl.unitree_hg.msg.dds_ import LowState_ + from Modes.Manual.controller import auto_pick_iface, LowStateHub + from Modes.Manual.replay_engine import ReplayWithHome + from Server.capture_service import capture_with_replay_sync, ensure_replay_integrity + + iface = auto_pick_iface() + sanad_logger.print_and_log(f"๐ŸŒ DDS iface: {iface}", "info") + ChannelFactoryInitialize(0, iface) + + hub = LowStateHub(watchdog_timeout=0.25) + sub = ChannelSubscriber("rt/lowstate", LowState_) + sub.Init(hub.handler, 10) + + replay = ReplayWithHome(hub, watchdog_disable_after=1.0) + + startup_replay = config.read_selected_replay_path() + fallback_replay = config.DATA_DIR / "photo_G3.jsonl" + selected_replay, replay_report = ensure_replay_integrity(startup_replay, fallback_replay) + if not replay_report.get("active", {}).get("ok", False): + sanad_logger.print_and_log( + f"โš ๏ธ Active replay invalid: {replay_report.get('active', {}).get('error', 'unknown')}", + "warning", + ) + elif not replay_report.get("active", {}).get("trigger_ok", False): + sanad_logger.print_and_log( + "โš ๏ธ Active replay has no trigger markers. Timed fallback capture will be used.", + "warning", + ) + if replay_report.get("fallback_used"): + sanad_logger.print_and_log( + f"โš ๏ธ Using fallback replay: {selected_replay.name}", + "warning", + ) + if replay_report.get("degraded_no_trigger"): + sanad_logger.print_and_log( + "โš ๏ธ No replay with trigger markers found. Running in degraded triggerless mode.", + "warning", + ) + config.REPLAY_FILE = selected_replay + try: + rel_name = str(selected_replay.resolve().relative_to(config.DATA_DIR)).replace("\\", "/") + config.write_selected_replay_name(rel_name) + except Exception: + pass + + def _capture_from_dashboard() -> str: + base_prefix = os.environ.get("PHOTO_PREFIX", "photo").strip() or "photo" + delay = max(0.0, min(PHOTO_DELAY_SEC, PHOTO_TOTAL_SEC)) + return capture_with_replay_sync( + replay_runner=replay, + replay_file=config.REPLAY_FILE, + home_file=config.HOME_FILE, + delay_sec=delay, + prefix=base_prefix, + speed=1.0, + ) + + dashboard_capture_func = _capture_from_dashboard + + def _test_replay_from_dashboard(replay_name: str) -> str: + try: + candidate = config.resolve_replay_path(replay_name) + except Exception as e: + return f"[ERR] invalid replay path: {e}" + if not candidate.exists(): + return "[ERR] replay not found" + if replay.is_playing: + return "[ERR] replay already in progress" + replay.run(candidate, config.HOME_FILE, speed=1.0) + return str(candidate) + + dashboard_replay_test_func = _test_replay_from_dashboard + + url = start_photo_server( + PHOTOS_DIR, + port=PHOTO_SERVER_PORT, + capture_func=dashboard_capture_func, + replay_test_func=dashboard_replay_test_func, + ) + sanad_logger.print_and_log(f"๐Ÿ–ผ๏ธ Phone gallery: {url}", message_type="info") + + if not manual_lean_runtime: + from Server.uploader import start_uploader + + try: + start_uploader(PHOTOS_DIR) + except Exception as e: + sanad_logger.print_and_log(f"Failed to start uploader: {e}", message_type="warning") + + voice = HamadGeminiVoice( + photo_phrases_file=str(config.PHOTO_PHRASES_FILE), + ) + + if startup_mode == "ai" or autonomous_enabled: + voice.calibrate_mic() + else: + sanad_logger.print_and_log("๐ŸŽ™๏ธ Mic calibration skipped at startup (manual mode).", "info") + sanad_logger.print_and_log("โ„น๏ธ Manual mode: mic follows dashboard toggle, but AI photo commands and AI detection stay disabled until AI mode.", "info") + restart_delay = float(config.read_watchdog_component_restart_delay_sec()) + + tasks = [ + asyncio.create_task(_run_component_forever("capture_mic", lambda: voice.capture_mic(), restart_delay)), + asyncio.create_task(_run_component_forever("receive_audio", lambda: voice.receive_audio(), restart_delay)), + asyncio.create_task(_run_component_forever("play_audio", lambda: voice.play_audio(), restart_delay)), + asyncio.create_task(_run_component_forever("keepalive", lambda: voice.keepalive(every_sec=20.0), restart_delay)), + asyncio.create_task(_run_component_forever("runtime_health", lambda: _write_runtime_health_loop(voice, 1.0), restart_delay)), + asyncio.create_task( + _run_ws_supervisor( + voice, + autonomous_enabled=autonomous_enabled, + dashboard_url=url, + manual_lean_runtime=manual_lean_runtime, + ) + ), + asyncio.create_task(_run_mode_policy_sync(voice, autonomous_enabled=autonomous_enabled)), + ] + + if not manual_lean_runtime: + from Modes.Manual.trigger_loop import trigger_loop + + tasks.append( + asyncio.create_task( + _run_component_forever( + "trigger_loop", + lambda: trigger_loop(hub=hub, replay=replay, voice=voice, take_photo_sync_callable=None, ws=None), + restart_delay, + ) + ) + ) + + if autonomous_enabled and not manual_lean_runtime: + tasks.append( + asyncio.create_task( + _run_autonomous_mode_supervisor( + hub=hub, + replay=replay, + voice=voice, + restart_delay_sec=restart_delay, + ) + ) + ) + sanad_logger.print_and_log("๐Ÿค– Autonomous services armed (AUTONOMOUS_ENABLE=1). AI mode can start without restart.", "info") + + try: + await asyncio.gather(*tasks) + finally: + for t in tasks: + if not t.done(): + t.cancel() + await asyncio.gather(*tasks, return_exceptions=True) + + +if __name__ == "__main__": + try: + asyncio.run(main()) + except KeyboardInterrupt: + sanad_logger.print_and_log("\n๐Ÿ‘‹ Ma'a Salama (Goodbye)!", message_type="info") + except Exception as e: + sanad_logger.print_and_log(f"\nโŒ Fatal Error: {e}", message_type="error") diff --git a/Models/person.pt b/Models/person.pt new file mode 100644 index 0000000..45b273b Binary files /dev/null and b/Models/person.pt differ diff --git a/Modes/AI/__init__.py b/Modes/AI/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/Modes/AI/autonomous_manager.py b/Modes/AI/autonomous_manager.py new file mode 100644 index 0000000..69eb33e --- /dev/null +++ b/Modes/AI/autonomous_manager.py @@ -0,0 +1,1457 @@ +import asyncio +import json +import os +import threading +import time +from pathlib import Path +from threading import Thread + +import cv2 + +from Modes.AI.vision_detector import VisionDetector +from Core import settings as config +from Core.error_events import record_error +from Core.Logger import Logs +from Core import people_registry +from Server.capture_service import capture_with_replay_sync, replay_timing_profile + +sanad_logger = Logs() +sanad_logger.LogEngine("G1_Logs", "autonomous_manager") + + +class AutonomousManager: + """ + Autonomous flow: + IDLE -> WAIT_CONFIRM -> FRAMING -> COUNTDOWN -> COMPLETE -> IDLE + """ + + def __init__( + self, + zmq_host: str = "127.0.0.1", + zmq_port: int = 55555, + stability_frames: int = 3, + poll_hz: int = 8, + video_source: str | None = None, + ): + self.detector = VisionDetector( + zmq_host=zmq_host, + zmq_port=zmq_port, + poll_hz=poll_hz, + video_source=video_source, + ) + self.stability_frames = int(stability_frames) + self.cooldown_until = 0.0 + self.session_id = 0 + self._running = False + + self._capture_done = False + self._capture_result = None + self._capture_lock = threading.Lock() + self._capture_cancel_event: threading.Event | None = None + + self.interaction_active = False + self.interaction_flag = Path(config.SCRIPTS_DIR) / "interaction_triggered.flag" + self.request_photo_flag = Path(config.SCRIPTS_DIR) / "request_photo.flag" + self.confirm_yes_flag = Path(config.SCRIPTS_DIR) / "confirm_yes.flag" + self.confirm_no_flag = Path(config.SCRIPTS_DIR) / "confirm_no.flag" + self.state_file = Path(config.AUTONOMOUS_STATE_FILE) + + self.confirm_timeout_sec = float(os.environ.get("CONFIRM_TIMEOUT_SEC", "15.0")) + self.confirm_reminder_sec = float(os.environ.get("CONFIRM_REMINDER_SEC", "5.0")) + self.confirm_guard_sec = float(os.environ.get("CONFIRM_GUARD_SEC", "1.2")) + self.session_cooldown_sec = float(os.environ.get("SESSION_COOLDOWN_SEC", "10.0")) + self.leave_timeout_sec = float(os.environ.get("VISITOR_LEAVE_TIMEOUT_SEC", "2.5")) + self.countdown_lose_subject_sec = float(os.environ.get("COUNTDOWN_LOSE_SUBJECT_SEC", "1.4")) + self.capture_finalize_grace_sec = float(os.environ.get("CAPTURE_FINALIZE_GRACE_SEC", "3.0")) + + self.framing_timeout_sec = float(os.environ.get("FRAMING_TIMEOUT_SEC", "20.0")) + self.framing_feedback_interval_sec = float(os.environ.get("FRAMING_FEEDBACK_INTERVAL_SEC", "2.0")) + self.framing_good_frames_required = int(os.environ.get("FRAMING_GOOD_FRAMES_REQUIRED", "2")) + + # Framing thresholds + self.center_tolerance = float(os.environ.get("FRAMING_CENTER_TOLERANCE", "0.18")) + self.subject_min_area_ratio = float(os.environ.get("FRAMING_MIN_AREA_RATIO", "0.06")) + self.subject_max_area_ratio = float(os.environ.get("FRAMING_MAX_AREA_RATIO", "0.55")) + self.min_blur_var = float(os.environ.get("FRAMING_MIN_BLUR_VAR", "80.0")) + self.min_exposure = float(os.environ.get("FRAMING_MIN_EXPOSURE", "55.0")) + self.max_exposure = float(os.environ.get("FRAMING_MAX_EXPOSURE", "200.0")) + self.headroom_min_ratio = float(config.read_vision_framing_headroom_min_ratio()) + self.headroom_max_ratio = float(config.read_vision_framing_headroom_max_ratio()) + self.eye_line_min_ratio = float(config.read_vision_framing_eye_line_min_ratio()) + self.eye_line_max_ratio = float(config.read_vision_framing_eye_line_max_ratio()) + self.retake_score_threshold = float(config.read_vision_framing_retake_score_threshold()) + self.retake_prompt_enabled = bool(config.read_vision_retake_prompt_enabled()) + self.retake_limit = int(config.read_vision_retake_max_per_session()) + self.hard_target_lock_enabled = bool(config.read_vision_hard_target_lock_enabled()) + self.autonomous_greeting_replay_enabled = bool(config.read_vision_autonomous_greeting_replay_enabled()) + self.autonomous_greeting_replay_file = self._resolve_replay_path( + config.read_vision_autonomous_greeting_replay_file() + ) + self.autonomous_capture_replay_enabled = bool(config.read_vision_autonomous_capture_replay_enabled()) + self.retake_confirm_timeout_sec = float(os.environ.get("RETAKE_CONFIRM_TIMEOUT_SEC", "8.0")) + + self.yolo_strict_required = bool(config.read_vision_yolo_strict_required()) + self.gemini_context_hz = float(config.read_vision_gemini_context_hz()) + self.gemini_context_silent = bool(config.read_vision_gemini_context_silent()) + self._context_interval_sec = 1.0 / max(0.5, self.gemini_context_hz) + self._next_context_ts = 0.0 + + self.ai_blocked = False + self.ai_block_reason = "" + self._last_vision_log_signature = None + self._last_vision_log_ts = 0.0 + self.face_recognition_enabled = bool(config.read_vision_face_recognition_enabled()) + self.face_recognition_threshold = float(config.read_vision_face_recognition_threshold()) + self.current_person: dict | None = None + + async def _say(self, voice, text: str): + if voice is None: + return + try: + ok = await voice.send_text_prompt_live(text) + if not ok: + sanad_logger.print_and_log("Voice prompt skipped: Gemini WS not connected.", "warning") + except Exception as e: + sanad_logger.print_and_log(f"Voice prompt failed: {e}", "warning") + + async def _say_prompt( + self, + voice, + prompt_key: str, + fallback_text: str, + *, + mode_override: str | None = None, + allow_gemini_fallback: bool | None = None, + ): + if voice is None: + return + try: + if hasattr(voice, "play_prompt_key"): + ok = await voice.play_prompt_key( + prompt_key, + fallback_text=fallback_text, + allow_gemini_fallback=allow_gemini_fallback, + mode_override=mode_override, + ) + else: + ok = await voice.send_text_prompt_live(fallback_text) + if not ok: + sanad_logger.print_and_log(f"Voice prompt skipped for {prompt_key}: output unavailable.", "warning") + except Exception as e: + sanad_logger.print_and_log(f"Voice prompt failed for {prompt_key}: {e}", "warning") + + async def _say_capture_prompt(self, voice, prompt_key: str, fallback_text: str): + await self._say_prompt( + voice, + prompt_key, + fallback_text, + mode_override="audio", + allow_gemini_fallback=False, + ) + + def _maybe_log_vision_snapshot(self, snapshot: dict, now_ts: float): + try: + person_count = int(snapshot.get("person_count", 0)) + face_count = int(snapshot.get("face_count", 0)) + group_detected = bool(snapshot.get("group_detected", False)) + group_size = int(snapshot.get("group_size", 0)) + subject_visible = bool(snapshot.get("subject_visible", False)) + intent_detected = bool(snapshot.get("intent_detected", False)) + max_area = int(float(snapshot.get("max_area", 0.0) or 0.0)) + depth_m = snapshot.get("depth_m", None) + if depth_m is not None: + depth_m = round(float(depth_m), 2) + + sig = ( + person_count, + face_count, + group_detected, + group_size, + subject_visible, + intent_detected, + max_area, + depth_m, + ) + active = bool(person_count or face_count or subject_visible or group_detected or intent_detected) + if (not active) and self._last_vision_log_signature in (None, sig): + return + if sig == self._last_vision_log_signature and (now_ts - self._last_vision_log_ts) < 1.0: + return + + self._last_vision_log_signature = sig + self._last_vision_log_ts = now_ts + sanad_logger.print_and_log( + "๐Ÿ‘๏ธ Vision: " + f"people={person_count} faces={face_count} group={group_detected}({group_size}) " + f"visible={subject_visible} intent={intent_detected} area={max_area} depth={depth_m if depth_m is not None else '-'}", + "info", + ) + except Exception as e: + record_error("autonomous_manager", "vision_snapshot_log", e) + + def _set_interaction_active(self, active: bool, voice=None, reason: str = ""): + active = bool(active) + self.interaction_active = active + try: + self.interaction_flag.parent.mkdir(parents=True, exist_ok=True) + if active: + self.interaction_flag.write_text(f"{time.time():.3f} {reason}".strip(), encoding="utf-8") + elif self.interaction_flag.exists(): + self.interaction_flag.unlink() + except Exception as e: + record_error("autonomous_manager", "set_interaction_active_file", e, {"active": bool(active)}) + + if voice is not None and hasattr(voice, "set_audio_gate"): + try: + idle_voice_listen_enabled = bool(config.read_vision_idle_voice_listen_enabled()) + mic_enabled = bool(config.read_gemini_mic_enabled()) + runtime_mode = str(config.read_runtime_mode()).strip().lower() + if runtime_mode not in ("manual", "ai"): + runtime_mode = "manual" + if active: + if hasattr(voice, "set_passive_listen"): + voice.set_passive_listen(False, reason=reason or "interaction active") + voice.set_audio_gate(True, reason=reason) + else: + if runtime_mode != "ai": + if hasattr(voice, "set_passive_listen"): + voice.set_passive_listen(False, reason=reason or "manual mode") + voice.set_audio_gate(mic_enabled, reason=reason or "manual mode") + else: + if hasattr(voice, "set_passive_listen"): + voice.set_passive_listen(mic_enabled and idle_voice_listen_enabled, reason=reason or "idle") + voice.set_audio_gate(mic_enabled and idle_voice_listen_enabled, reason=reason or "idle") + except Exception as e: + record_error("autonomous_manager", "set_interaction_active_audio_gate", e, {"active": bool(active)}) + + @staticmethod + def _clear_flag(path: Path): + try: + if path.exists(): + path.unlink() + except Exception as e: + record_error("autonomous_manager", "clear_flag", e, {"path": str(path)}) + + @staticmethod + def _consume_flag(path: Path) -> bool: + try: + if path.exists(): + path.unlink() + return True + except Exception as e: + record_error("autonomous_manager", "consume_flag", e, {"path": str(path)}) + return False + + def _consume_request_photo_flag(self) -> bool: + return self._consume_flag(self.request_photo_flag) or self._consume_flag(self.confirm_yes_flag) + + def _consume_direct_request_flag(self) -> bool: + return self._consume_flag(self.request_photo_flag) + + def _consume_no_photo_flag(self) -> bool: + return self._consume_flag(self.confirm_no_flag) + + def _clear_confirmation_flags(self): + self._clear_flag(self.request_photo_flag) + self._clear_flag(self.confirm_yes_flag) + self._clear_flag(self.confirm_no_flag) + + def _cancel_capture_pipeline(self, reason: str = ""): + try: + ev = self._capture_cancel_event + if ev is not None: + ev.set() + self._capture_cancel_event = None + if reason: + sanad_logger.print_and_log(f"Capture pipeline cancelled: {reason}", "warning") + except Exception as e: + record_error("autonomous_manager", "cancel_capture_pipeline", e, {"reason": reason}) + + @staticmethod + def _resolve_replay_path(path_value: str) -> Path: + return config.resolve_replay_path(path_value) + + def _start_greeting_replay(self, replay): + if replay is None or not bool(self.autonomous_greeting_replay_enabled): + return + replay_file = Path(self.autonomous_greeting_replay_file).resolve() + if not replay_file.exists(): + sanad_logger.print_and_log(f"โš ๏ธ Greeting replay missing: {replay_file}", "warning") + return + if bool(getattr(replay, "is_playing", False)): + sanad_logger.print_and_log("โš ๏ธ Greeting replay skipped: replay already busy.", "warning") + return + + def _run_greeting(): + try: + sanad_logger.print_and_log(f"๐Ÿ‘‹ Greeting replay: {replay_file.name}", "info") + replay.run(replay_file, config.HOME_FILE, 1.0) + except Exception as e: + record_error("autonomous_manager", "greeting_replay", e, {"replay_file": str(replay_file)}) + + Thread(target=_run_greeting, daemon=True).start() + + def _reset_current_person(self): + self.current_person = None + + def _session_person_label(self) -> str: + if not isinstance(self.current_person, dict): + return "" + return str( + self.current_person.get("display_label") + or self.current_person.get("display_name") + or self.current_person.get("person_id") + or "" + ).strip() + + def _current_person_extras(self) -> dict: + person = self.current_person if isinstance(self.current_person, dict) else {} + return { + "recognized_person_id": str(person.get("person_id") or ""), + "recognized_person_known": bool(person.get("known_person", False)), + "recognized_person_new": bool(person.get("new_person", False)), + "recognized_person_label": str( + person.get("display_label") or person.get("display_name") or person.get("person_id") or "" + ), + "recognized_person_match_score": float(person.get("match_score", 0.0) or 0.0), + "recognized_person_created_date": str(person.get("created_date") or ""), + } + + def _select_face_box(self, snapshot: dict) -> dict | None: + faces = snapshot.get("face_boxes") or [] + if not isinstance(faces, list) or not faces: + return None + subject_box = self._find_subject_box(snapshot) + if not isinstance(subject_box, dict): + try: + return max(faces, key=lambda f: float(f.get("w", 0.0)) * float(f.get("h", 0.0))) + except Exception: + return faces[0] if faces else None + + try: + sx1 = float(subject_box.get("x", 0.0)) + sy1 = float(subject_box.get("y", 0.0)) + sx2 = sx1 + max(1.0, float(subject_box.get("w", 1.0))) + sy2 = sy1 + max(1.0, float(subject_box.get("h", 1.0))) + except Exception: + sx1 = sy1 = 0.0 + sx2 = sy2 = 0.0 + + best = None + best_overlap = -1.0 + for face in faces: + try: + fx1 = float(face.get("x", 0.0)) + fy1 = float(face.get("y", 0.0)) + fx2 = fx1 + max(1.0, float(face.get("w", 1.0))) + fy2 = fy1 + max(1.0, float(face.get("h", 1.0))) + ix1 = max(sx1, fx1) + iy1 = max(sy1, fy1) + ix2 = min(sx2, fx2) + iy2 = min(sy2, fy2) + overlap = max(0.0, ix2 - ix1) * max(0.0, iy2 - iy1) + if overlap > best_overlap: + best_overlap = overlap + best = face + except Exception: + continue + if best is not None: + return best + try: + return max(faces, key=lambda f: float(f.get("w", 0.0)) * float(f.get("h", 0.0))) + except Exception: + return faces[0] if faces else None + + def _identify_person_for_session(self, snapshot: dict, source: str = "vision") -> dict | None: + if not bool(self.face_recognition_enabled): + self._reset_current_person() + return None + frame = snapshot.get("frame") + if frame is None: + self._reset_current_person() + return None + if bool(snapshot.get("group_detected", False)) or int(snapshot.get("face_count", 0) or 0) > 1: + self._reset_current_person() + return None + + face_box = self._select_face_box(snapshot) + if face_box is None: + self._reset_current_person() + return None + subject_box = self._find_subject_box(snapshot) + try: + result = people_registry.recognize_or_enroll( + frame, + face_box, + subject_box=subject_box, + threshold=self.face_recognition_threshold, + source=source, + ) + except Exception as e: + record_error("autonomous_manager", "identify_person_for_session", e) + self._reset_current_person() + return None + if not isinstance(result, dict) or not bool(result.get("ok", False)): + self._reset_current_person() + return None + self.current_person = result + label = self._session_person_label() + if bool(result.get("known_person", False)): + sanad_logger.print_and_log( + f"๐Ÿง‘ Returning guest recognized: {label} (score={float(result.get('match_score', 0.0) or 0.0):.2f})", + "info", + ) + else: + sanad_logger.print_and_log(f"๐Ÿง‘ New guest enrolled: {label}", "info") + return result + + def _welcome_prompt_text(self, group_detected: bool) -> str: + if group_detected: + return ( + "Hello everyone, welcome. We will take a photo together. " + "Would your group like a photo? Please say yes photo or no photo." + ) + label = self._session_person_label() + if label and bool(self.current_person and self.current_person.get("known_person")): + return ( + f"Welcome back, {label}. Would you like another photo? " + "Please say yes photo or no photo." + ) + return ( + "Hello, welcome. We will take a photo together. " + "Would you like a photo? Please say yes photo or no photo." + ) + + def _welcome_prompt_key(self, group_detected: bool) -> str: + if group_detected: + return "welcome_group" + if self._session_person_label() and bool(self.current_person and self.current_person.get("known_person")): + return "welcome_returning" + return "welcome_single" + + def _framing_prompt_text(self, group_detected: bool) -> str: + if group_detected: + return "Great. Please stand with me in front of the camera, stay together in the center, and look at the camera." + return "Great. Please stand with me in front of the camera, stay in the center, and look at the camera." + + @staticmethod + def _framing_prompt_key(group_detected: bool) -> str: + return "frame_group" if group_detected else "frame_single" + + @staticmethod + def _find_subject_box(snapshot: dict) -> dict | None: + subj = snapshot.get("subject_box") + if isinstance(subj, dict): + return subj + boxes = snapshot.get("boxes") or [] + if not boxes: + return None + try: + return max(boxes, key=lambda b: float(b.get("w", 0.0)) * float(b.get("h", 0.0))) + except Exception: + return boxes[0] if boxes else None + + def _evaluate_framing_quality(self, snapshot: dict) -> tuple[bool, list[str], dict]: + frame = snapshot.get("frame") + box = self._find_subject_box(snapshot) + if frame is None or box is None: + return False, ["step into view"], {"reason": "no_frame_or_subject"} + + try: + h, w = frame.shape[:2] + x = float(box.get("x", 0.0)) + y = float(box.get("y", 0.0)) + bw = max(1.0, float(box.get("w", 1.0))) + bh = max(1.0, float(box.get("h", 1.0))) + area_ratio = (bw * bh) / max(1.0, float(w * h)) + cx = x + (bw / 2.0) + dx = (cx - (w / 2.0)) / max(1.0, float(w)) + centered = abs(dx) <= self.center_tolerance + size_ok = self.subject_min_area_ratio <= area_ratio <= self.subject_max_area_ratio + + gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) + blur_var = float(cv2.Laplacian(gray, cv2.CV_64F).var()) + exposure = float(gray.mean()) + blur_ok = blur_var >= self.min_blur_var + exposure_ok = self.min_exposure <= exposure <= self.max_exposure + + faces = snapshot.get("face_boxes") or [] + face_box = None + best_overlap = -1.0 + for f in faces: + try: + fx = float(f.get("x", 0.0)) + fy = float(f.get("y", 0.0)) + fw = max(1.0, float(f.get("w", 1.0))) + fh = max(1.0, float(f.get("h", 1.0))) + ix1 = max(x, fx) + iy1 = max(y, fy) + ix2 = min(x + bw, fx + fw) + iy2 = min(y + bh, fy + fh) + iw = max(0.0, ix2 - ix1) + ih = max(0.0, iy2 - iy1) + overlap = iw * ih + if overlap > best_overlap: + best_overlap = overlap + face_box = {"x": fx, "y": fy, "w": fw, "h": fh} + except Exception: + continue + + if face_box is not None: + headroom_ratio = float(face_box["y"]) / max(1.0, float(h)) + eye_y = float(face_box["y"]) + (0.38 * float(face_box["h"])) + eye_line_ratio = eye_y / max(1.0, float(h)) + else: + headroom_ratio = y / max(1.0, float(h)) + eye_line_ratio = (y + (0.25 * bh)) / max(1.0, float(h)) + headroom_ok = self.headroom_min_ratio <= headroom_ratio <= self.headroom_max_ratio + eye_line_ok = self.eye_line_min_ratio <= eye_line_ratio <= self.eye_line_max_ratio + + mid = int(max(1, w // 2)) + left_mean = float(gray[:, :mid].mean()) if mid > 0 else exposure + right_mean = float(gray[:, mid:].mean()) if (w - mid) > 0 else exposure + lr_delta = right_mean - left_mean + + reasons: list[str] = [] + if not centered: + reasons.append("move a bit to the center") + if not size_ok: + reasons.append("come a little closer" if area_ratio < self.subject_min_area_ratio else "step slightly back") + if not headroom_ok: + if headroom_ratio < self.headroom_min_ratio: + reasons.append("lower your chin a little") + else: + reasons.append("raise your chin a little") + if not eye_line_ok: + reasons.append("keep your eyes around the middle of the frame") + if not blur_ok: + reasons.append("hold still for a second") + if not exposure_ok: + if exposure < self.min_exposure: + if abs(lr_delta) > 12.0: + reasons.append( + "turn slightly toward the brighter side" + ) + else: + reasons.append("face the light") + else: + reasons.append("avoid strong direct light") + + metrics = { + "area_ratio": area_ratio, + "blur_var": blur_var, + "exposure": exposure, + "center_dx": dx, + "centered": centered, + "size_ok": size_ok, + "blur_ok": blur_ok, + "exposure_ok": exposure_ok, + "headroom_ratio": headroom_ratio, + "eye_line_ratio": eye_line_ratio, + "headroom_ok": headroom_ok, + "eye_line_ok": eye_line_ok, + "left_exposure": left_mean, + "right_exposure": right_mean, + "lr_exposure_delta": lr_delta, + } + return len(reasons) == 0, reasons, metrics + except Exception as e: + return False, ["hold still and face the camera"], {"reason": str(e)} + + @staticmethod + def _framing_guidance_text(reasons: list[str]) -> str: + if not reasons: + return "Great framing. Hold still." + uniq = [] + for r in reasons: + if r not in uniq: + uniq.append(r) + joined = ", and ".join(uniq[:2]) + return f"Almost ready. Please {joined}." + + @staticmethod + def _quality_score_from_metrics(metrics: dict) -> float: + checks = [ + bool(metrics.get("centered", False)), + bool(metrics.get("size_ok", False)), + bool(metrics.get("blur_ok", False)), + bool(metrics.get("exposure_ok", False)), + bool(metrics.get("headroom_ok", False)), + bool(metrics.get("eye_line_ok", False)), + ] + if not checks: + return 0.0 + return float(sum(1 for x in checks if x)) / float(len(checks)) + + def _retake_assessment(self, snapshot: dict, previous_metrics: dict | None = None) -> tuple[bool, str, float, dict]: + good, reasons, metrics = self._evaluate_framing_quality(snapshot) + if previous_metrics and isinstance(previous_metrics, dict): + merged = dict(previous_metrics) + merged.update(metrics) + metrics = merged + score = self._quality_score_from_metrics(metrics) + if good and score >= self.retake_score_threshold: + return False, "", score, metrics + if reasons: + reason = reasons[0] + else: + reason = "framing quality is not optimal" + return True, str(reason), score, metrics + + def _lock_target_on_session_start(self, snapshot: dict): + try: + if hasattr(self.detector, "set_hard_lock"): + self.detector.set_hard_lock(bool(self.hard_target_lock_enabled)) + if hasattr(self.detector, "lock_target_from_snapshot"): + self.detector.lock_target_from_snapshot( + snapshot, + lock_group=bool(self.hard_target_lock_enabled and snapshot.get("group_detected", False)), + ) + elif hasattr(self.detector, "lock_subject_from_snapshot"): + self.detector.lock_subject_from_snapshot(snapshot) + except Exception as e: + record_error("autonomous_manager", "lock_target_on_session_start", e) + + def _unlock_target(self): + try: + if hasattr(self.detector, "unlock_target"): + self.detector.unlock_target() + elif hasattr(self.detector, "unlock_subject"): + self.detector.unlock_subject() + except Exception as e: + record_error("autonomous_manager", "unlock_target", e) + + def _detector_readiness(self) -> dict: + try: + return self.detector.readiness(strict_required=self.yolo_strict_required) + except Exception as e: + record_error("autonomous_manager", "detector_readiness", e) + return { + "ok": False, + "strict_required": bool(self.yolo_strict_required), + "configured_backend": "normal", + "effective_backend": "normal", + "yolo_loaded": False, + "person_model_ok": False, + "face_model_ok": False, + "person_model_path": "", + "face_model_path": "", + "person_model_error": str(e), + "face_model_error": "", + "block_reason": f"Detector readiness failed: {e}", + } + + async def _push_vision_context(self, voice, state_name: str, snapshot: dict): + if voice is None: + return + if not hasattr(voice, "send_vision_context_live"): + return + now = time.time() + if now < self._next_context_ts: + return + self._next_context_ts = now + self._context_interval_sec + + payload = { + "person_count": int(snapshot.get("person_count", 0)), + "group_count": int(snapshot.get("group_count", 0)), + "group_size": int(snapshot.get("group_size", 0)), + "subject_visible": bool(snapshot.get("subject_visible", False)), + "depth_m": snapshot.get("depth_m"), + "approach_speed_mps": float(snapshot.get("approach_speed_mps", 0.0) or 0.0), + "state": str(state_name), + "intent_detected": bool(snapshot.get("intent_detected", False)), + } + try: + await voice.send_vision_context_live(payload, silent=bool(self.gemini_context_silent)) + except Exception as e: + record_error("autonomous_manager", "push_vision_context", e, {"state": state_name}) + + def _write_runtime_state(self, state_name: str, snapshot: dict, voice=None, extras: dict | None = None): + payload = { + "state": state_name, + "session_id": self.session_id, + "interaction_active": bool(self.interaction_active), + "intent_detected": bool(snapshot.get("intent_detected", False)), + "detector_backend": str(snapshot.get("detector_backend", "normal")), + "yolo_runtime": str(snapshot.get("yolo_runtime", "")), + "ai_blocked": bool(self.ai_blocked), + "ai_block_reason": str(self.ai_block_reason or ""), + "person_count": int(snapshot.get("person_count", 0)), + "face_count": int(snapshot.get("face_count", 0)), + "group_count": int(snapshot.get("group_count", 0)), + "group_size": int(snapshot.get("group_size", 0)), + "group_detected": bool(snapshot.get("group_detected", False)), + "is_close": bool(snapshot.get("is_close", False)), + "is_approaching": bool(snapshot.get("is_approaching", False)), + "max_area": float(snapshot.get("max_area", 0.0)), + "depth_m": snapshot.get("depth_m"), + "approach_speed_mps": snapshot.get("approach_speed_mps"), + "subject_id": snapshot.get("subject_id"), + "subject_visible": bool(snapshot.get("subject_visible", False)), + "target_lock_active": bool(snapshot.get("target_lock_active", False)), + "target_lock_type": str(snapshot.get("target_lock_type", "") or ""), + "target_lock_id": snapshot.get("target_lock_id"), + "target_switch_blocked_count": int(snapshot.get("target_switch_blocked_count", 0)), + "camera_ok": bool(snapshot.get("camera_ok", False)), + "depth_ok": bool(snapshot.get("depth_ok", False)), + "camera_restarts": int(snapshot.get("camera_restarts", 0)), + "depth_restarts": int(snapshot.get("depth_restarts", 0)), + "audio_gate_open": bool(getattr(voice, "audio_gate_open", False)) if voice is not None else None, + "ws_connected": bool(getattr(voice, "is_ws_connected", lambda: False)()) if voice is not None else False, + "mic_state": "", + "speaker_state": "", + "cooldown_remaining": max(0.0, self.cooldown_until - time.time()), + "time": time.time(), + } + try: + if voice is not None and hasattr(voice, "get_runtime_health"): + vh = voice.get_runtime_health() or {} + payload["ws_connected"] = bool(vh.get("ws_connected", payload["ws_connected"])) + payload["mic_state"] = str(vh.get("mic_state", "") or "") + payload["speaker_state"] = str(vh.get("speaker_state", "") or "") + except Exception as e: + record_error("autonomous_manager", "write_runtime_state_voice_health", e) + if extras: + payload.update(extras) + try: + self.state_file.parent.mkdir(parents=True, exist_ok=True) + self.state_file.write_text(json.dumps(payload, ensure_ascii=False), encoding="utf-8") + except Exception as e: + record_error("autonomous_manager", "write_runtime_state", e, {"state": state_name}) + + def _start_capture_pipeline(self, replay, timing_info: dict | None = None): + self._cancel_capture_pipeline(reason="restart") + with self._capture_lock: + self._capture_done = False + self._capture_result = None + + timing_info = timing_info or self._resolve_capture_timing(use_replay=bool(self.autonomous_capture_replay_enabled)) + default_delay_sec = max(0.0, min(config.PHOTO_DELAY_SEC, config.PHOTO_TOTAL_SEC)) + delay_sec = float(timing_info.get("capture_offset_sec") or default_delay_sec) + cancel_event = threading.Event() + self._capture_cancel_event = cancel_event + + def _run_pipeline(): + try: + base_prefix = os.environ.get("PHOTO_PREFIX", "photo") + prefix = f"session{self.session_id}_{base_prefix}" + run_delay_sec = delay_sec + capture_replay_runner = replay if bool(self.autonomous_capture_replay_enabled) else None + if capture_replay_runner is not None: + replay_wait_deadline = time.time() + 4.0 + while ( + bool(getattr(capture_replay_runner, "is_playing", False)) + and time.time() < replay_wait_deadline + and not cancel_event.is_set() + ): + time.sleep(0.05) + if bool(getattr(capture_replay_runner, "is_playing", False)): + sanad_logger.print_and_log( + "โš ๏ธ AI capture replay still busy; falling back to still photo for this shot.", + "warning", + ) + capture_replay_runner = None + run_delay_sec = default_delay_sec + if capture_replay_runner is None: + sanad_logger.print_and_log("๐Ÿ“ท AI capture: still photo mode (no replay during photo).", "info") + else: + sanad_logger.print_and_log( + f"๐Ÿ“ท AI capture: replaying {Path(config.REPLAY_FILE).name} during the shot. " + f"duration={float(timing_info.get('duration_sec') or 0.0):.3f}s " + f"shot_at={run_delay_sec:.3f}s " + f"source={timing_info.get('capture_source', 'config_fallback')}", + "info", + ) + res = capture_with_replay_sync( + replay_runner=capture_replay_runner, + replay_file=config.REPLAY_FILE, + home_file=config.HOME_FILE, + delay_sec=run_delay_sec, + prefix=prefix, + speed=1.0, + cancel_event=cancel_event, + ) + with self._capture_lock: + self._capture_result = str(res) + self._capture_done = True + if str(res).startswith("[ERR]"): + sanad_logger.print_and_log(f"Capture pipeline failed: {res}", "error") + else: + sanad_logger.print_and_log(f"Saved photo (pipeline): {res}", "info") + except Exception as e: + record_error("autonomous_manager", "start_capture_pipeline", e, {"session_id": self.session_id}) + with self._capture_lock: + self._capture_result = f"[ERR] capture pipeline exception: {e}" + self._capture_done = True + + Thread(target=_run_pipeline, daemon=True).start() + + def _resolve_capture_timing(self, use_replay: bool) -> dict: + default_delay = max(0.0, min(config.PHOTO_DELAY_SEC, config.PHOTO_TOTAL_SEC)) + timing_info = { + "capture_offset_sec": default_delay, + "duration_sec": 0.0, + "capture_source": "config_fallback", + } + if not use_replay: + return timing_info + try: + profile = replay_timing_profile(config.REPLAY_FILE) + if bool(profile.get("ok")): + return profile + if profile.get("capture_offset_sec") is not None: + timing_info["capture_offset_sec"] = float(profile.get("capture_offset_sec") or default_delay) + except Exception as e: + record_error("autonomous_manager", "resolve_capture_timing", e, {"replay_file": str(config.REPLAY_FILE)}) + return timing_info + + async def run(self, hub, replay, voice, ws=None): + self.detector.start() + self.hub = hub + self._running = True + self._set_interaction_active(False, voice=voice, reason="idle") + + state = "IDLE" + state_enter_ts = time.time() + stable_count = 0 + + confirm_deadline = 0.0 + confirm_last_prompt_ts = 0.0 + confirm_ignore_until = 0.0 + leave_since = 0.0 + + framing_deadline = 0.0 + framing_last_feedback_ts = 0.0 + framing_good_streak = 0 + framing_metrics: dict = {} + + countdown_deadline = 0.0 + countdown_announced: set[int] = set() + countdown_lost_since = 0.0 + + retake_count = 0 + retake_deadline = 0.0 + retake_recommended = False + retake_reason = "" + retake_score = 1.0 + + sanad_logger.print_and_log("๐Ÿค– Autonomous mode enabled.", "info") + + try: + while self._running: + await asyncio.sleep(1.0 / max(1, self.detector.poll_hz)) + now = time.time() + runtime_mode = "manual" + try: + runtime_mode = str(config.read_runtime_mode()).strip().lower() + except Exception: + runtime_mode = "manual" + if runtime_mode not in ("manual", "ai"): + runtime_mode = "manual" + + # Runtime-refresh operator toggles from config.json. + try: + self.hard_target_lock_enabled = bool(config.read_vision_hard_target_lock_enabled()) + self.retake_prompt_enabled = bool(config.read_vision_retake_prompt_enabled()) + self.retake_limit = int(config.read_vision_retake_max_per_session()) + self.retake_score_threshold = float(config.read_vision_framing_retake_score_threshold()) + self.autonomous_greeting_replay_enabled = bool(config.read_vision_autonomous_greeting_replay_enabled()) + self.autonomous_greeting_replay_file = self._resolve_replay_path( + config.read_vision_autonomous_greeting_replay_file() + ) + self.autonomous_capture_replay_enabled = bool(config.read_vision_autonomous_capture_replay_enabled()) + self.face_recognition_enabled = bool(config.read_vision_face_recognition_enabled()) + self.face_recognition_threshold = float(config.read_vision_face_recognition_threshold()) + except Exception as e: + record_error("autonomous_manager", "runtime_option_refresh", e) + + if hasattr(self.detector, "set_hard_lock"): + try: + self.detector.set_hard_lock(bool(self.hard_target_lock_enabled)) + except Exception as e: + record_error("autonomous_manager", "detector_set_hard_lock", e) + + snap = self.detector.latest() + face_count = int(snap.get("face_count", 0)) + subject_visible = bool(snap.get("subject_visible", face_count > 0)) + intent_detected = bool(snap.get("intent_detected", False)) + max_area = float(snap.get("max_area", 0.0)) + group_detected = bool(snap.get("group_detected", False)) + self._maybe_log_vision_snapshot(snap, now) + + if runtime_mode != "ai": + stable_count = 0 + if state != "IDLE": + sanad_logger.print_and_log("๐Ÿ›‘ Autonomous flow paused: runtime mode is MANUAL.", "info") + state = "IDLE" + state_enter_ts = now + self._clear_confirmation_flags() + self._set_interaction_active(False, voice=voice, reason="manual mode") + self._cancel_capture_pipeline(reason="manual mode") + self._unlock_target() + self._reset_current_person() + self._write_runtime_state( + "IDLE", + snap, + voice=voice, + extras={ + "stable_count": 0, + "runtime_mode": runtime_mode, + "autonomous_paused": True, + "retake_prompt_enabled": bool(self.retake_prompt_enabled), + "retake_limit": int(self.retake_limit), + "retake_count": int(retake_count), + **self._current_person_extras(), + }, + ) + continue + + readiness = self._detector_readiness() + if self.yolo_strict_required and (not bool(readiness.get("ok", False))): + block_reason = str(readiness.get("block_reason") or "AI blocked by strict YOLO policy.") + if (not self.ai_blocked) or (self.ai_block_reason != block_reason): + sanad_logger.print_and_log(f"โ›” AI blocked: {block_reason}", "error") + self._set_interaction_active(False, voice=voice, reason="strict yolo blocked") + self._clear_confirmation_flags() + self._cancel_capture_pipeline(reason="strict yolo blocked") + self._unlock_target() + self._reset_current_person() + self.ai_blocked = True + self.ai_block_reason = block_reason + state = "IDLE_BLOCKED" + stable_count = 0 + self._write_runtime_state( + "IDLE_BLOCKED", + snap, + voice=voice, + extras={ + "yolo_loaded": bool(readiness.get("yolo_loaded", False)), + "person_model_ok": bool(readiness.get("person_model_ok", False)), + "face_model_ok": bool(readiness.get("face_model_ok", False)), + "detector_backend": str(readiness.get("effective_backend", "normal")), + "retake_prompt_enabled": bool(self.retake_prompt_enabled), + "retake_limit": int(self.retake_limit), + "retake_count": int(retake_count), + **self._current_person_extras(), + }, + ) + await self._push_vision_context(voice, "IDLE_BLOCKED", snap) + continue + + if self.ai_blocked: + sanad_logger.print_and_log("โœ… AI readiness restored. Leaving blocked state.", "info") + self.ai_blocked = False + self.ai_block_reason = "" + state = "IDLE" + state_enter_ts = now + stable_count = 0 + + await self._push_vision_context(voice, state, snap) + + try: + hard_cancel = False + if hub is not None: + if getattr(hub, "hard_cancel_combo", None): + hard_cancel = bool(hub.hard_cancel_combo()) + elif getattr(hub, "combo_r2l1", None): + hard_cancel = bool(hub.combo_r2l1()) + if hard_cancel: + sanad_logger.print_and_log("๐Ÿ›‘ HARD CANCEL detected (R2+L1).", "warning") + state = "IDLE" + state_enter_ts = now + self.cooldown_until = now + self.session_cooldown_sec + self._clear_confirmation_flags() + self._set_interaction_active(False, voice=voice, reason="hard cancel") + self._cancel_capture_pipeline(reason="hard cancel") + self._unlock_target() + self._reset_current_person() + except Exception as e: + record_error("autonomous_manager", "remote_cancel_check", e) + + if state == "IDLE": + self._write_runtime_state( + "IDLE", + snap, + voice=voice, + extras={ + "stable_count": stable_count, + "retake_prompt_enabled": bool(self.retake_prompt_enabled), + "retake_limit": int(self.retake_limit), + "retake_count": int(retake_count), + **self._current_person_extras(), + }, + ) + + # Allow visitor-initiated photo request from IDLE. + # Only explicit request_photo should start a new session from idle. + if self._consume_direct_request_flag(): + self.session_id += 1 + state = "FRAMING" + state_enter_ts = now + framing_deadline = now + self.framing_timeout_sec + framing_last_feedback_ts = 0.0 + framing_good_streak = 0 + framing_metrics = {} + retake_count = 0 + retake_recommended = False + retake_reason = "" + retake_score = 1.0 + self._clear_confirmation_flags() + self._set_interaction_active(True, voice=voice, reason="voice request from idle") + self._lock_target_on_session_start(snap) + self._identify_person_for_session(snap, source="voice_request") + sanad_logger.print_and_log( + f"๐Ÿ—ฃ๏ธ Voice photo request from IDLE -> session {self.session_id}", + "info", + ) + await self._say_prompt( + voice, + self._framing_prompt_key(group_detected), + self._framing_prompt_text(group_detected), + ) + continue + + if now < self.cooldown_until: + continue + + if intent_detected: + stable_count += 1 + else: + stable_count = 0 + + if stable_count < self.stability_frames: + continue + + stable_count = 0 + self.session_id += 1 + state = "WAIT_CONFIRM" + state_enter_ts = now + confirm_deadline = now + self.confirm_timeout_sec + confirm_ignore_until = now + self.confirm_guard_sec + confirm_last_prompt_ts = now + leave_since = 0.0 + framing_metrics = {} + retake_count = 0 + retake_recommended = False + retake_reason = "" + retake_score = 1.0 + self._clear_confirmation_flags() + self._set_interaction_active(True, voice=voice, reason=f"intent max_area={max_area:.0f}") + self._lock_target_on_session_start(snap) + self._identify_person_for_session(snap, source="intent") + + sanad_logger.print_and_log( + f"๐Ÿ”” Intent detected (area={max_area:.0f}) -> session {self.session_id}", + "info", + ) + self._start_greeting_replay(replay) + try: + wake_text = self._welcome_prompt_text(group_detected) + await voice.trigger_wake_sequence( + wake_text=wake_text, + prompt_key=self._welcome_prompt_key(group_detected), + ) + except Exception as e: + record_error("autonomous_manager", "wake_sequence", e) + sanad_logger.print_and_log(f"Wake sequence failed: {e}", "warning") + continue + + if state == "WAIT_CONFIRM": + confirm_remaining = max(0.0, confirm_deadline - now) + self._write_runtime_state( + "WAIT_CONFIRM", + snap, + voice=voice, + extras={ + "confirm_timeout_remaining": confirm_remaining, + "confirm_guard_remaining": max(0.0, confirm_ignore_until - now), + "retake_prompt_enabled": bool(self.retake_prompt_enabled), + "retake_limit": int(self.retake_limit), + "retake_count": int(retake_count), + **self._current_person_extras(), + }, + ) + + if not subject_visible: + if leave_since <= 0.0: + leave_since = now + elif (now - leave_since) >= self.leave_timeout_sec: + sanad_logger.print_and_log("๐Ÿ™ˆ Visitor left before confirmation.", "warning") + await self._say_prompt( + voice, + "visitor_left", + "No worries. I will wait here for the next visitor.", + ) + state = "IDLE" + state_enter_ts = now + self.cooldown_until = now + self.session_cooldown_sec + self._clear_confirmation_flags() + self._set_interaction_active(False, voice=voice, reason="left before confirm") + self._cancel_capture_pipeline(reason="left before confirm") + self._unlock_target() + self._reset_current_person() + continue + else: + leave_since = 0.0 + + if now >= confirm_ignore_until: + if self._consume_no_photo_flag(): + await self._say_prompt(voice, "declined", "No problem. We can do it anytime.") + state = "IDLE" + state_enter_ts = now + self.cooldown_until = now + self.session_cooldown_sec + self._clear_confirmation_flags() + self._set_interaction_active(False, voice=voice, reason="visitor declined") + self._cancel_capture_pipeline(reason="visitor declined") + self._unlock_target() + self._reset_current_person() + continue + + if self._consume_request_photo_flag(): + sanad_logger.print_and_log("โœ… Confirmation received. Entering framing check.", "info") + await self._say_prompt( + voice, + self._framing_prompt_key(group_detected), + self._framing_prompt_text(group_detected), + ) + state = "FRAMING" + state_enter_ts = now + framing_deadline = now + self.framing_timeout_sec + framing_last_feedback_ts = 0.0 + framing_good_streak = 0 + continue + + if (now - confirm_last_prompt_ts) >= self.confirm_reminder_sec: + confirm_last_prompt_ts = now + await self._say_prompt( + voice, + "confirm_reminder", + "Say yes photo to continue, or no photo to cancel.", + ) + + if now >= confirm_deadline: + sanad_logger.print_and_log("โŒ› Confirmation timeout.", "warning") + await self._say_prompt( + voice, + "confirm_timeout", + "No problem. I will wait here. Come back anytime for a photo.", + ) + state = "IDLE" + state_enter_ts = now + self.cooldown_until = now + self.session_cooldown_sec + self._clear_confirmation_flags() + self._set_interaction_active(False, voice=voice, reason="confirm timeout") + self._cancel_capture_pipeline(reason="confirm timeout") + self._unlock_target() + self._reset_current_person() + continue + + elif state == "FRAMING": + if self._consume_no_photo_flag(): + await self._say_prompt(voice, "session_cancelled", "Okay. Session cancelled.") + state = "IDLE" + state_enter_ts = now + self.cooldown_until = now + self.session_cooldown_sec + self._clear_confirmation_flags() + self._set_interaction_active(False, voice=voice, reason="cancelled during framing") + self._cancel_capture_pipeline(reason="cancelled during framing") + self._unlock_target() + self._reset_current_person() + continue + + good, reasons, framing_metrics = self._evaluate_framing_quality(snap) + framing_remaining = max(0.0, framing_deadline - now) + self._write_runtime_state( + "FRAMING", + snap, + voice=voice, + extras={ + "framing_ok": bool(good), + "framing_reasons": reasons, + "framing_timeout_remaining": framing_remaining, + "framing_good_streak": framing_good_streak, + "framing_metrics": framing_metrics, + "retake_prompt_enabled": bool(self.retake_prompt_enabled), + "retake_limit": int(self.retake_limit), + "retake_count": int(retake_count), + **self._current_person_extras(), + }, + ) + + if good: + framing_good_streak += 1 + else: + framing_good_streak = 0 + if (now - framing_last_feedback_ts) >= self.framing_feedback_interval_sec: + framing_last_feedback_ts = now + await self._say(voice, self._framing_guidance_text(reasons)) + + if framing_good_streak >= self.framing_good_frames_required: + capture_timing = self._resolve_capture_timing( + use_replay=bool(self.autonomous_capture_replay_enabled) + ) + capture_start_ts = time.time() + self._start_capture_pipeline(replay, timing_info=capture_timing) + await self._say_capture_prompt( + voice, + "countdown_intro", + "Look at the camera, stay ready, hold your pose with me, keep still, keep your smile soft, and in a moment I will count down for the photo.", + ) + state = "COUNTDOWN" + state_enter_ts = now + countdown_deadline = capture_start_ts + float( + capture_timing.get("capture_offset_sec") + or max(0.0, min(config.PHOTO_DELAY_SEC, config.PHOTO_TOTAL_SEC)) + ) + countdown_announced = set() + countdown_lost_since = 0.0 + continue + + if now >= framing_deadline: + sanad_logger.print_and_log("โŒ› Framing timeout.", "warning") + await self._say_prompt( + voice, + "framing_timeout", + "I still need a better frame. Please step in front of me and say yes photo when ready.", + ) + state = "WAIT_CONFIRM" + state_enter_ts = now + confirm_deadline = now + self.confirm_timeout_sec + confirm_ignore_until = now + self.confirm_guard_sec + confirm_last_prompt_ts = now + leave_since = 0.0 + continue + + elif state == "COUNTDOWN": + countdown_remaining = max(0.0, countdown_deadline - now) + self._write_runtime_state( + "COUNTDOWN", + snap, + voice=voice, + extras={ + "countdown_remaining": countdown_remaining, + "framing_metrics": framing_metrics, + "retake_prompt_enabled": bool(self.retake_prompt_enabled), + "retake_limit": int(self.retake_limit), + "retake_count": int(retake_count), + **self._current_person_extras(), + }, + ) + + if self._consume_no_photo_flag(): + await self._say_prompt(voice, "countdown_cancelled", "Countdown cancelled.") + state = "IDLE" + state_enter_ts = now + self.cooldown_until = now + self.session_cooldown_sec + self._clear_confirmation_flags() + self._set_interaction_active(False, voice=voice, reason="cancelled during countdown") + self._cancel_capture_pipeline(reason="cancelled during countdown") + self._unlock_target() + self._reset_current_person() + continue + + if not subject_visible: + if countdown_lost_since <= 0.0: + countdown_lost_since = now + elif (now - countdown_lost_since) >= self.countdown_lose_subject_sec: + await self._say_prompt( + voice, + "lost_from_frame", + "I lost you from frame. Let us try again.", + ) + state = "FRAMING" + state_enter_ts = now + framing_deadline = now + self.framing_timeout_sec + framing_last_feedback_ts = 0.0 + framing_good_streak = 0 + continue + else: + countdown_lost_since = 0.0 + + sec_left = int(round(countdown_remaining)) + if sec_left in (3, 2, 1) and sec_left not in countdown_announced: + countdown_announced.add(sec_left) + await self._say_capture_prompt(voice, f"count_{sec_left}", f"{sec_left}...") + elif sec_left <= 0 and 0 not in countdown_announced: + countdown_announced.add(0) + await self._say_capture_prompt(voice, "smile", "Smile.") + + with self._capture_lock: + capture_done = bool(self._capture_done) + capture_result = self._capture_result + + if capture_done: + if isinstance(capture_result, str) and capture_result.startswith("[ERR]"): + sanad_logger.print_and_log(f"Capture failed: {capture_result}", "error") + state = "IDLE" + state_enter_ts = now + self.cooldown_until = now + self.session_cooldown_sec + self._set_interaction_active(False, voice=voice, reason="capture failed") + self._cancel_capture_pipeline(reason="capture failed") + self._unlock_target() + self._reset_current_person() + else: + try: + person_id = str((self.current_person or {}).get("person_id") or "").strip() + if person_id: + people_registry.attach_captured_photo(person_id, str(capture_result)) + except Exception as e: + record_error("autonomous_manager", "attach_captured_photo", e) + retake_recommended, retake_reason, retake_score, framing_metrics = self._retake_assessment( + snap, + previous_metrics=framing_metrics, + ) + if ( + bool(self.retake_prompt_enabled) + and bool(retake_recommended) + and int(retake_count) < int(self.retake_limit) + ): + state = "RETAKE_CONFIRM" + state_enter_ts = now + retake_deadline = now + self.retake_confirm_timeout_sec + reason_txt = retake_reason or "the framing is not optimal" + await self._say_prompt( + voice, + "retake_recommended", + f"Photo captured. I recommend a retake because {reason_txt}. " + "Say yes photo to retake, or no photo to keep this one.", + ) + else: + state = "COMPLETE" + state_enter_ts = now + continue + + if now >= (countdown_deadline + self.capture_finalize_grace_sec): + record_error( + "autonomous_manager", + "countdown_capture_timeout", + context={"session_id": self.session_id, "grace_sec": self.capture_finalize_grace_sec}, + ) + sanad_logger.print_and_log("Capture timeout after countdown. Resetting session.", "error") + state = "IDLE" + state_enter_ts = now + self.cooldown_until = now + self.session_cooldown_sec + self._set_interaction_active(False, voice=voice, reason="capture timeout") + self._cancel_capture_pipeline(reason="capture timeout") + self._unlock_target() + self._reset_current_person() + continue + + elif state == "RETAKE_CONFIRM": + rem = max(0.0, retake_deadline - now) + self._write_runtime_state( + "RETAKE_CONFIRM", + snap, + voice=voice, + extras={ + "retake_prompt_enabled": bool(self.retake_prompt_enabled), + "retake_recommended": bool(retake_recommended), + "retake_reason": str(retake_reason or ""), + "retake_score": float(retake_score), + "retake_count": int(retake_count), + "retake_limit": int(self.retake_limit), + "retake_timeout_remaining": rem, + "framing_metrics": framing_metrics, + **self._current_person_extras(), + }, + ) + if self._consume_no_photo_flag(): + state = "COMPLETE" + state_enter_ts = now + continue + if self._consume_request_photo_flag(): + if int(retake_count) < int(self.retake_limit): + retake_count += 1 + await self._say_prompt( + voice, + "retake_yes", + "Great, let us retake. Hold your pose.", + ) + state = "FRAMING" + state_enter_ts = now + framing_deadline = now + self.framing_timeout_sec + framing_last_feedback_ts = 0.0 + framing_good_streak = 0 + else: + await self._say_prompt( + voice, + "retake_limit", + "Retake limit reached. Keeping the current photo.", + ) + state = "COMPLETE" + state_enter_ts = now + continue + if now >= retake_deadline: + state = "COMPLETE" + state_enter_ts = now + continue + + elif state == "COMPLETE": + self._write_runtime_state( + "COMPLETE", + snap, + voice=voice, + extras={ + "capture_result": self._capture_result, + "retake_prompt_enabled": bool(self.retake_prompt_enabled), + "retake_recommended": bool(retake_recommended), + "retake_reason": str(retake_reason or ""), + "retake_score": float(retake_score), + "retake_count": int(retake_count), + "retake_limit": int(self.retake_limit), + "framing_metrics": framing_metrics, + **self._current_person_extras(), + }, + ) + await self._say_capture_prompt( + voice, + "photo_saved_thanks", + "Thank you. Photo saved. Don't forget to check your photos.", + ) + sanad_logger.print_and_log(f"โœ… Session {self.session_id} complete.", "info") + await asyncio.sleep(1.0) + state = "IDLE" + state_enter_ts = now + self.cooldown_until = time.time() + self.session_cooldown_sec + self._clear_confirmation_flags() + self._set_interaction_active(False, voice=voice, reason="session complete") + self._cancel_capture_pipeline(reason="session complete") + self._unlock_target() + self._reset_current_person() + continue + + if (time.time() - state_enter_ts) > 120.0: + sanad_logger.print_and_log("Autonomous state timed out, forcing IDLE reset.", "warning") + state = "IDLE" + state_enter_ts = time.time() + self.cooldown_until = time.time() + self.session_cooldown_sec + self._clear_confirmation_flags() + self._set_interaction_active(False, voice=voice, reason="state watchdog reset") + self._cancel_capture_pipeline(reason="state watchdog reset") + self._unlock_target() + self._reset_current_person() + + finally: + self._set_interaction_active(False, voice=voice, reason="autonomous stop") + self._cancel_capture_pipeline(reason="autonomous stop") + self._unlock_target() + self._reset_current_person() + self.detector.stop() + def stop(self): + self._running = False + self.detector.stop() + + +if __name__ == "__main__": + async def main(): + am = AutonomousManager() + + class Stub: + pass + + await am.run(Stub(), Stub(), Stub(), None) + + try: + asyncio.run(main()) + except KeyboardInterrupt: + pass diff --git a/Modes/AI/camera_module.py b/Modes/AI/camera_module.py new file mode 100644 index 0000000..381acde --- /dev/null +++ b/Modes/AI/camera_module.py @@ -0,0 +1,333 @@ +""" +Camera capture module for Unitree G1 robot +Handles OpenCV camera interface and image processing for AI analysis +""" + +import cv2 +import numpy as np +import base64 +import io +import os +import time +from pathlib import Path +from PIL import Image +from typing import Optional, Union, List +import logging +from Core.settings import CAMERA_INDEX, FRAME_WIDTH, FRAME_HEIGHT, FPS + +class CameraCapture: + """ + Camera capture class for Unitree G1 robot + Provides methods to capture frames and prepare them for AI analysis + """ + + def __init__(self, camera_index: Optional[Union[int, str]] = None): + """ + Initialize camera capture + + Args: + camera_index: int index, /dev/videoX path, "auto", or None + """ + self.camera_source = self._resolve_camera_source(camera_index) + # Keep legacy field name for backward compatibility with older modules/tests + self.camera_index = self.camera_source + self.cap = None + self.is_initialized = False + self.logger = logging.getLogger(__name__) + self._last_read_warn_ts = 0.0 + + def _resolve_camera_source(self, camera_source: Optional[Union[int, str]]) -> Union[int, str]: + """ + Resolve requested camera source from argument/env/defaults. + Priority: + 1) explicit argument + 2) CAMERA_DEVICE env (supports /dev/videoX or "auto") + 3) CAMERA_INDEX env/config int + """ + if camera_source is None: + env_device = os.environ.get("CAMERA_DEVICE", "").strip() + if env_device: + camera_source = env_device + else: + camera_source = os.environ.get("CAMERA_INDEX", str(CAMERA_INDEX)) + + if isinstance(camera_source, str): + s = camera_source.strip() + if not s: + return int(CAMERA_INDEX) + if s.lower() == "auto": + return "auto" + try: + return int(s) + except ValueError: + return s + + return int(camera_source) + + def _candidate_sources(self) -> List[Union[int, str]]: + """ + Build candidate capture sources. When CAMERA_FALLBACK_SCAN=1 (default), + we also try available /dev/video* nodes if the primary source fails. + """ + src = self.camera_source + candidates: List[Union[int, str]] = [src] + + # If primary source is /dev/videoX, also try numeric index X. + if isinstance(src, str) and src.startswith("/dev/video"): + try: + idx = int(src.replace("/dev/video", "")) + candidates.append(idx) + except Exception: + pass + + do_scan = os.environ.get("CAMERA_FALLBACK_SCAN", "1").strip().lower() not in ( + "0", "false", "no", "off" + ) + if src == "auto" or do_scan: + for p in sorted(Path("/dev").glob("video*")): + sp = str(p) + if sp not in candidates: + candidates.append(sp) + try: + idx = int(sp.replace("/dev/video", "")) + if idx not in candidates: + candidates.append(idx) + except Exception: + pass + + return candidates + + def _open_capture(self, source: Union[int, str]): + if isinstance(source, str) and source.startswith("/dev/video"): + # V4L2 backend is more reliable for /dev/videoX on Linux. + return cv2.VideoCapture(source, cv2.CAP_V4L2) + return cv2.VideoCapture(source) + + def initialize(self) -> bool: + """ + Initialize camera connection + + Returns: + bool: True if successful, False otherwise + """ + try: + self.release() + tried: List[str] = [] + + for source in self._candidate_sources(): + tried.append(str(source)) + cap = None + try: + cap = self._open_capture(source) + except Exception: + cap = None + + if cap is None or not cap.isOpened(): + try: + if cap is not None: + cap.release() + except Exception: + pass + continue + + # Set camera properties + cap.set(cv2.CAP_PROP_FRAME_WIDTH, FRAME_WIDTH) + cap.set(cv2.CAP_PROP_FRAME_HEIGHT, FRAME_HEIGHT) + cap.set(cv2.CAP_PROP_FPS, FPS) + + # Test capture + ret, _frame = cap.read() + if not ret: + cap.release() + continue + + self.cap = cap + self.camera_source = source + self.camera_index = source + self.is_initialized = True + self.logger.info(f"Camera initialized successfully: {source}") + return True + + self.is_initialized = False + self.cap = None + self.logger.error(f"Failed to open camera. Tried sources: {', '.join(tried)}") + return False + + except Exception as e: + self.logger.error(f"Camera initialization failed: {e}") + return False + + def capture_frame(self) -> Optional[np.ndarray]: + """ + Capture a single frame from camera + + Returns: + numpy.ndarray: Captured frame or None if failed + """ + if not self.is_initialized or self.cap is None: + return None + + try: + ret, frame = self.cap.read() + if not ret: + now = time.time() + # Throttle noisy warnings when camera stream is unstable/unavailable. + if now - self._last_read_warn_ts >= 5.0: + self.logger.warning("Failed to capture frame from camera") + self._last_read_warn_ts = now + return None + + return frame + + except Exception as e: + self.logger.error(f"Frame capture failed: {e}") + return None + + def frame_to_base64(self, frame: np.ndarray, format: str = 'JPEG') -> Optional[str]: + """ + Convert OpenCV frame to base64 string for API transmission + + Args: + frame: OpenCV frame (BGR format) + format: Image format ('JPEG' or 'PNG') + + Returns: + str: Base64 encoded image or None if failed + """ + try: + # Convert BGR to RGB + rgb_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) + + # Convert to PIL Image + pil_image = Image.fromarray(rgb_frame) + + # Convert to bytes + buffer = io.BytesIO() + pil_image.save(buffer, format=format, quality=85) + buffer.seek(0) + + # Encode to base64 + img_base64 = base64.b64encode(buffer.getvalue()).decode('utf-8') + + return img_base64 + + except Exception as e: + self.logger.error(f"Base64 conversion failed: {e}") + return None + + def frame_to_pil(self, frame: np.ndarray) -> Optional[Image.Image]: + """ + Convert OpenCV frame to PIL Image for Gemini API + + Args: + frame: OpenCV frame (BGR format) + + Returns: + PIL.Image: Converted image or None if failed + """ + try: + # Convert BGR to RGB + rgb_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) + + # Convert to PIL Image + pil_image = Image.fromarray(rgb_frame) + + return pil_image + + except Exception as e: + self.logger.error(f"PIL conversion failed: {e}") + return None + + def get_frame_info(self) -> dict: + """ + Get current camera frame information + + Returns: + dict: Frame information including resolution, FPS + """ + if not self.is_initialized or self.cap is None: + return {} + + try: + info = { + 'width': int(self.cap.get(cv2.CAP_PROP_FRAME_WIDTH)), + 'height': int(self.cap.get(cv2.CAP_PROP_FRAME_HEIGHT)), + 'fps': self.cap.get(cv2.CAP_PROP_FPS), + 'format': int(self.cap.get(cv2.CAP_PROP_FORMAT)), + 'brightness': self.cap.get(cv2.CAP_PROP_BRIGHTNESS), + 'contrast': self.cap.get(cv2.CAP_PROP_CONTRAST), + 'saturation': self.cap.get(cv2.CAP_PROP_SATURATION) + } + return info + + except Exception as e: + self.logger.error(f"Failed to get frame info: {e}") + return {} + + def release(self): + """ + Release camera resources + """ + try: + if self.cap is not None: + self.cap.release() + self.cap = None + self.logger.info("Camera released successfully") + + self.is_initialized = False + + except Exception as e: + self.logger.error(f"Camera release failed: {e}") + finally: + # Headless systems often ship OpenCV without HighGUI window backends. + # Do not fail camera lifecycle because window teardown is unavailable. + try: + import cv2 + cv2.destroyAllWindows() + except Exception: + pass + + def __enter__(self): + """Context manager entry""" + self.initialize() + return self + + def __exit__(self, exc_type, exc_val, exc_tb): + """Context manager exit""" + self.release() + return False # Don't suppress exceptions + +# Utility functions for camera testing +def test_camera_capture(): + """ + Test camera capture functionality + """ + logging.basicConfig(level=logging.INFO) + + with CameraCapture() as camera: + if not camera.is_initialized: + print("Failed to initialize camera") + return + + print("Camera info:", camera.get_frame_info()) + + # Capture test frame + frame = camera.capture_frame() + if frame is not None: + print(f"Captured frame shape: {frame.shape}") + + # Test base64 conversion + base64_str = camera.frame_to_base64(frame) + if base64_str: + print(f"Base64 conversion successful, length: {len(base64_str)}") + + # Test PIL conversion + pil_img = camera.frame_to_pil(frame) + if pil_img: + print(f"PIL conversion successful, size: {pil_img.size}") + + # Save test image + cv2.imwrite('test_capture.jpg', frame) + print("Test image saved as test_capture.jpg") + else: + print("Failed to capture frame") diff --git a/Modes/AI/vision_detector.py b/Modes/AI/vision_detector.py new file mode 100644 index 0000000..c5ea902 --- /dev/null +++ b/Modes/AI/vision_detector.py @@ -0,0 +1,1480 @@ +"""vision_detector.py + +YOLO detector + tracker + intent: +- YOLO ONNX person detector for subject tracking/intent. +- YOLO ONNX face detector (optional) for face metrics. +- Group detection from person clusters. +- Intent uses RealSense depth first; bbox area fallback. +""" + +from collections import deque +from threading import Event, Lock, Thread +import logging +import os +import time +from pathlib import Path + +import cv2 +import numpy as np + +from Modes.AI.camera_module import CameraCapture +from Core import settings as config +from Core.error_events import record_error +from Server import direct_camera_client + +try: + import pyrealsense2 as rs # type: ignore + + _HAS_RS = True +except Exception: + _HAS_RS = False + +try: + from ultralytics import YOLO # type: ignore + + _HAS_ULTRALYTICS = True +except Exception: + YOLO = None # type: ignore + _HAS_ULTRALYTICS = False + +logger = logging.getLogger(__name__) + + +def _coerce_backend_name(value: str | None) -> str: + v = str(value or "").strip().lower() + if v in ("yolo", "normal"): + return v + return "normal" + + +def _coerce_yolo_runtime(value: str | None) -> str: + v = str(value or "").strip().lower() + if v in ("ultralytics", "opencv"): + return v + return "ultralytics" + + +def _resolve_model_path(path_value: str | None) -> Path | None: + if not path_value: + return None + p = Path(str(path_value)).expanduser() + if not p.is_absolute(): + p = (config.PROJECT_ROOT / p).resolve() + return p + + +def _probe_onnx_model(path_value: str | None) -> dict: + out = {"path": "", "exists": False, "loadable": False, "error": ""} + p = _resolve_model_path(path_value) + if p is None: + return out + + out["path"] = str(p) + if not p.exists() or (not p.is_file()): + out["error"] = "model file missing" + return out + + out["exists"] = True + try: + cv2.dnn.readNetFromONNX(str(p)) + out["loadable"] = True + except Exception as e: + out["error"] = str(e) + return out + + +def _probe_ultralytics_model(path_value: str | None) -> dict: + out = {"path": "", "exists": False, "loadable": False, "error": ""} + p = _resolve_model_path(path_value) + if p is None: + return out + + out["path"] = str(p) + if not p.exists() or (not p.is_file()): + out["error"] = "model file missing" + return out + out["exists"] = True + + if not _HAS_ULTRALYTICS: + out["error"] = "ultralytics not installed" + return out + + try: + YOLO(str(p)) + out["loadable"] = True + except Exception as e: + out["error"] = str(e) + return out + + +def probe_ai_readiness(backend: str | None = None, strict_required: bool | None = None) -> dict: + configured_backend = _coerce_backend_name( + backend if backend is not None else config.read_vision_detector_backend() + ) + yolo_runtime = _coerce_yolo_runtime(config.read_vision_yolo_runtime()) + strict = bool(config.read_vision_yolo_strict_required() if strict_required is None else strict_required) + + person_path = ( + os.environ.get("DETECTOR_PERSON_YOLO_ONNX", "").strip() + or os.environ.get("DETECTOR_ONNX_PATH", "").strip() + or str(getattr(config, "VISION_PERSON_YOLO_ONNX", "")).strip() + ) + face_path = ( + os.environ.get("DETECTOR_FACE_YOLO_ONNX", "").strip() + or str(getattr(config, "VISION_FACE_YOLO_ONNX", "")).strip() + ) + + if yolo_runtime == "ultralytics": + person = _probe_ultralytics_model(person_path) + face = _probe_ultralytics_model(face_path) + else: + person = _probe_onnx_model(person_path) + face = _probe_onnx_model(face_path) + person_ok = bool(person.get("loadable")) + face_ok = bool(face.get("loadable")) + yolo_loaded = bool(configured_backend == "yolo" and person_ok) + + block_reason = "" + if strict and configured_backend != "yolo": + block_reason = "Strict AI mode requires detection_backend=yolo." + elif strict and yolo_runtime == "ultralytics" and not _HAS_ULTRALYTICS: + block_reason = "Ultralytics runtime selected but package is not installed." + elif strict and not person_ok: + block_reason = "Person YOLO model is missing/invalid. Fix vision.person_yolo_onnx." + + ok = not bool(block_reason) + return { + "ok": bool(ok), + "strict_required": bool(strict), + "configured_backend": configured_backend, + "yolo_runtime": yolo_runtime, + "effective_backend": "yolo" if yolo_loaded else "normal", + "yolo_loaded": bool(yolo_loaded), + "person_model_ok": bool(person_ok), + "face_model_ok": bool(face_ok), + "person_model_path": str(person.get("path") or ""), + "face_model_path": str(face.get("path") or ""), + "person_model_error": str(person.get("error") or ""), + "face_model_error": str(face.get("error") or ""), + "block_reason": block_reason, + } + + +class VisionDetector: + def __init__(self, zmq_host="127.0.0.1", zmq_port=55555, poll_hz=10, video_source: str | None = None): + self.zmq_host = zmq_host + self.zmq_port = int(zmq_port) + self.poll_hz = float(poll_hz) + self.video_source = video_source + + self._stop = Event() + self._thread = None + self._latest_lock = Lock() + self._latest = { + "frame_time": 0.0, + "detector_backend": "normal", + "yolo_runtime": "ultralytics", + "face_count": 0, + "person_count": 0, + "group_count": 0, + "group_size": 0, + "group_detected": False, + "boxes": [], + "face_boxes": [], + "group_boxes": [], + "frame": None, + "intent_detected": False, + "max_area": 0.0, + "is_close": False, + "is_approaching": False, + "depth_m": None, + "approach_speed_mps": 0.0, + "subject_id": None, + "subject_box": None, + "subject_visible": False, + "subject_locked": False, + "target_lock_active": False, + "target_lock_type": "", + "target_lock_id": None, + "target_switch_blocked_count": 0, + "camera_ok": False, + "depth_ok": False, + "camera_restarts": 0, + "depth_restarts": 0, + } + + # Runtime-selectable detector backend + self._detector_backend = self._coerce_backend( + os.environ.get("DETECTOR_BACKEND", "").strip() or config.read_vision_detector_backend() + ) + self._last_backend_check_ts = 0.0 + + # YOLO detection config + self._yolo_runtime = _coerce_yolo_runtime( + os.environ.get("DETECTOR_YOLO_RUNTIME", "").strip() or config.read_vision_yolo_runtime() + ) + self._ultralytics_device = ( + os.environ.get("DETECTOR_YOLO_DEVICE", "").strip() or config.read_vision_yolo_ultralytics_device() + ) + self._person_model_path = str( + _resolve_model_path( + os.environ.get("DETECTOR_PERSON_YOLO_ONNX", "").strip() + or os.environ.get("DETECTOR_ONNX_PATH", "").strip() + or str(getattr(config, "VISION_PERSON_YOLO_ONNX", "")).strip() + or "" + ) + or "" + ).strip() + self._face_model_path = str( + _resolve_model_path( + os.environ.get("DETECTOR_FACE_YOLO_ONNX", "").strip() + or str(getattr(config, "VISION_FACE_YOLO_ONNX", "")).strip() + or "" + ) + or "" + ).strip() + input_size = int(max(320, getattr(config, "VISION_INPUT_SIZE", 640))) + self._dnn_input_size = (input_size, input_size) + self._person_score_thresh = float(getattr(config, "VISION_PERSON_SCORE_THRESH", 0.35)) + self._face_score_thresh = float(getattr(config, "VISION_FACE_SCORE_THRESH", 0.35)) + self._nms_iou_thresh = float(getattr(config, "VISION_NMS_IOU_THRESH", 0.45)) + self._person_class_id = int(getattr(config, "VISION_PERSON_CLASS_ID", 0)) + self._group_min_people = max(2, int(getattr(config, "VISION_GROUP_MIN_PEOPLE", 3))) + self._group_link_distance_px = float(getattr(config, "VISION_GROUP_LINK_DISTANCE_PX", 220.0)) + + self._person_net = None + self._face_net = None + self._warned_person_fallback = False + self._warned_yolo_unavailable = False + self._warned_ultralytics_missing = False + self._last_model_retry_ts = 0.0 + self._model_retry_sec = float(os.environ.get("YOLO_MODEL_RETRY_SEC", "2.0")) + + # Area-based fallback intent + self._proximity_threshold = float(os.environ.get("PROXIMITY_THRESHOLD", "50000")) + self._approach_delta = float(os.environ.get("APPROACH_DELTA", "12000")) + self._history_len = max(2, int(os.environ.get("INTENT_HISTORY_LEN", "5"))) + self._area_history = deque(maxlen=self._history_len) + + # Depth-first intent + self._min_depth_m = float(os.environ.get("MIN_DEPTH_M", "1.7")) + self._min_approach_speed_mps = float(os.environ.get("MIN_APPROACH_SPEED_MPS", "0.08")) + self._depth_history_len = max(2, int(os.environ.get("DEPTH_HISTORY_LEN", "6"))) + self._depth_history = deque(maxlen=self._depth_history_len) + + # Subject lock + self._hard_target_lock_enabled = bool(config.read_vision_hard_target_lock_enabled()) + self._locked_target_type = "" + self._locked_subject_id = None + self._locked_group_id = None + self._target_switch_blocked_count = 0 + self._subject_lock_lost_frames = max(1, int(os.environ.get("SUBJECT_LOCK_LOST_FRAMES", "20"))) + self._subject_lost_count = 0 + + # Camera/depth watchdog + self._no_frame_count = 0 + self._recover_after_no_frame = max(3, int(os.environ.get("CAMERA_RECOVER_AFTER_FRAMES", "10"))) + self._camera_ok = False + self._depth_ok = False + self._camera_restarts = 0 + self._depth_restarts = 0 + self._depth_enabled = os.environ.get("DETECTOR_USE_REALSENSE_DEPTH", "1").strip().lower() not in ( + "0", + "false", + "no", + "off", + ) + self._rs_pipeline = None + self._rs_profile = None + self._last_rs_restart = 0.0 + + self._apply_detector_backend(self._detector_backend, reason="init") + self._latest["detector_backend"] = self._effective_backend() + self._latest["yolo_runtime"] = self._yolo_runtime + self._face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + "haarcascade_frontalface_default.xml") + + self._camera = CameraCapture() + try: + self._camera.initialize() + except Exception: + logger.warning("VisionDetector: could not init CameraCapture fallback") + + self._video_cap = None + if self.video_source: + try: + self._video_cap = cv2.VideoCapture(self.video_source) + if not self._video_cap.isOpened(): + logger.warning(f"VisionDetector: could not open video source {self.video_source}") + self._video_cap = None + else: + logger.info(f"VisionDetector: using video source {self.video_source} for simulation") + except Exception as e: + logger.warning(f"VisionDetector: video source init failed: {e}") + + self._ensure_depth_pipeline(force=False) + + @staticmethod + def _coerce_backend(value: str | None) -> str: + return _coerce_backend_name(value) + + def _effective_backend(self) -> str: + if self._detector_backend == "yolo" and self._person_net is not None: + return "yolo" + return "normal" + + def _build_readiness(self, strict_required: bool | None = None) -> dict: + strict = bool(config.read_vision_yolo_strict_required() if strict_required is None else strict_required) + configured_backend = self._coerce_backend(self._detector_backend) + yolo_runtime = _coerce_yolo_runtime(self._yolo_runtime) + if yolo_runtime == "ultralytics": + person_model_ok = bool(self._person_net is not None and hasattr(self._person_net, "predict")) + face_model_ok = bool(self._face_net is not None and hasattr(self._face_net, "predict")) if self._face_model_path else False + else: + person_model_ok = bool(self._person_net is not None and hasattr(self._person_net, "setInput")) + face_model_ok = bool(self._face_net is not None and hasattr(self._face_net, "setInput")) if self._face_model_path else False + yolo_loaded = bool(configured_backend == "yolo" and person_model_ok) + + block_reason = "" + if strict and configured_backend != "yolo": + block_reason = "Strict AI mode requires detection_backend=yolo." + elif strict and yolo_runtime == "ultralytics" and not _HAS_ULTRALYTICS: + block_reason = "Ultralytics runtime selected but package is not installed." + elif strict and not person_model_ok: + block_reason = "Person YOLO model is missing/invalid. Fix vision.person_yolo_onnx." + + return { + "ok": not bool(block_reason), + "strict_required": bool(strict), + "configured_backend": configured_backend, + "yolo_runtime": yolo_runtime, + "effective_backend": self._effective_backend(), + "yolo_loaded": bool(yolo_loaded), + "person_model_ok": bool(person_model_ok), + "face_model_ok": bool(face_model_ok), + "person_model_path": str(self._person_model_path or ""), + "face_model_path": str(self._face_model_path or ""), + "person_model_error": "" if person_model_ok else "model not loaded", + "face_model_error": "" if (face_model_ok or (not self._face_model_path)) else "model not loaded", + "block_reason": block_reason, + } + + def readiness(self, strict_required: bool | None = None) -> dict: + return self._build_readiness(strict_required=strict_required) + + @classmethod + def probe_readiness(cls, backend: str | None = None, strict_required: bool | None = None) -> dict: + return probe_ai_readiness(backend=backend, strict_required=strict_required) + + def _maybe_retry_yolo_models(self, now_ts: float): + if self._detector_backend != "yolo": + return + if self._person_net is not None and (self._face_net is not None or not self._face_model_path): + return + if (now_ts - self._last_model_retry_ts) < max(0.5, self._model_retry_sec): + return + self._last_model_retry_ts = now_ts + if self._yolo_runtime == "ultralytics": + if self._person_net is None: + self._person_net = self._load_ultralytics_model(self._person_model_path, label="person") + if self._face_net is None and self._face_model_path: + self._face_net = self._load_ultralytics_model(self._face_model_path, label="face") + else: + if self._person_net is None: + self._person_net = self._load_onnx_model(self._person_model_path, label="person") + if self._face_net is None and self._face_model_path: + self._face_net = self._load_onnx_model(self._face_model_path, label="face") + + def _apply_detector_backend(self, backend: str, reason: str = ""): + backend = self._coerce_backend(backend) + prev_runtime = self._yolo_runtime + self._detector_backend = backend + self._warned_person_fallback = False + self._warned_yolo_unavailable = False + self._warned_ultralytics_missing = False + + try: + self._yolo_runtime = _coerce_yolo_runtime(config.read_vision_yolo_runtime()) + except Exception: + self._yolo_runtime = _coerce_yolo_runtime(self._yolo_runtime) + self._yolo_runtime = _coerce_yolo_runtime( + os.environ.get("DETECTOR_YOLO_RUNTIME", "").strip() or self._yolo_runtime + ) + if self._yolo_runtime != prev_runtime: + self._person_net = None + self._face_net = None + + if backend == "yolo": + if self._yolo_runtime == "ultralytics": + if self._person_net is None: + self._person_net = self._load_ultralytics_model(self._person_model_path, label="person") + if self._face_net is None and self._face_model_path: + self._face_net = self._load_ultralytics_model(self._face_model_path, label="face") + else: + if self._person_net is None: + self._person_net = self._load_onnx_model(self._person_model_path, label="person") + if self._face_net is None and self._face_model_path: + self._face_net = self._load_onnx_model(self._face_model_path, label="face") + + if self._person_net is None: + logger.warning( + f"VisionDetector: YOLO backend selected ({self._yolo_runtime}) but person model unavailable. Falling back to normal." + ) + elif self._face_net is None and self._face_model_path: + logger.info("VisionDetector: YOLO person active, face model missing -> Haar face fallback.") + else: + # Force non-AI normal mode. + self._person_net = None + self._face_net = None + + suffix = f" ({reason})" if reason else "" + logger.info(f"VisionDetector: detector backend set to {self._effective_backend()} [runtime={self._yolo_runtime}]{suffix}") + + def _refresh_detector_backend(self, now_ts: float): + if (now_ts - self._last_backend_check_ts) < 1.0: + self._maybe_retry_yolo_models(now_ts) + return + self._last_backend_check_ts = now_ts + try: + self._hard_target_lock_enabled = bool(config.read_vision_hard_target_lock_enabled()) + except Exception: + pass + try: + cfg_backend = self._coerce_backend(config.read_vision_detector_backend()) + except Exception: + cfg_backend = self._detector_backend + try: + cfg_runtime = _coerce_yolo_runtime(config.read_vision_yolo_runtime()) + except Exception: + cfg_runtime = self._yolo_runtime + if cfg_backend != self._detector_backend or cfg_runtime != self._yolo_runtime: + self._apply_detector_backend(cfg_backend, reason="runtime switch") + else: + self._maybe_retry_yolo_models(now_ts) + + @staticmethod + def _load_onnx_model(path: str | None, label: str): + if not path: + return None + try: + net = cv2.dnn.readNetFromONNX(str(path)) + net.setPreferableBackend(cv2.dnn.DNN_BACKEND_DEFAULT) + net.setPreferableTarget(cv2.dnn.DNN_TARGET_CPU) + logger.info(f"VisionDetector: loaded {label} YOLO ONNX model: {path}") + return net + except Exception as e: + logger.warning(f"VisionDetector: failed to load {label} model {path}: {e}") + return None + + def _load_ultralytics_model(self, path: str | None, label: str): + if not path: + return None + if not _HAS_ULTRALYTICS: + if not self._warned_ultralytics_missing: + self._warned_ultralytics_missing = True + logger.warning("VisionDetector: ultralytics package not installed; cannot use ultralytics runtime.") + return None + try: + model = YOLO(str(path)) + logger.info(f"VisionDetector: loaded {label} Ultralytics model: {path}") + return model + except Exception as e: + logger.warning(f"VisionDetector: failed to load {label} ultralytics model {path}: {e}") + return None + + def _run_yolo_ultralytics(self, model, frame, conf_thresh: float, class_filter: int | None = None): + if model is None or frame is None: + return [] + try: + results = model.predict( + source=frame, + conf=float(conf_thresh), + iou=float(self._nms_iou_thresh), + imgsz=int(self._dnn_input_size[0]), + device=str(self._ultralytics_device), + verbose=False, + ) + if not results: + return [] + res = results[0] + boxes_obj = getattr(res, "boxes", None) + if boxes_obj is None: + return [] + xyxy = boxes_obj.xyxy + confs = boxes_obj.conf + classes = boxes_obj.cls + if xyxy is None or confs is None or classes is None: + return [] + + try: + xyxy_np = xyxy.cpu().numpy() + conf_np = confs.cpu().numpy() + cls_np = classes.cpu().numpy() + except Exception: + xyxy_np = np.asarray(xyxy) + conf_np = np.asarray(confs) + cls_np = np.asarray(classes) + + out = [] + for i in range(len(xyxy_np)): + cls_id = int(round(float(cls_np[i]))) + if class_filter is not None and cls_id != int(class_filter): + continue + x1, y1, x2, y2 = [float(v) for v in xyxy_np[i][:4]] + x = int(round(max(0.0, x1))) + y = int(round(max(0.0, y1))) + w = int(round(max(0.0, x2 - x1))) + h = int(round(max(0.0, y2 - y1))) + if w < 4 or h < 4: + continue + out.append( + { + "x": x, + "y": y, + "w": w, + "h": h, + "conf": float(conf_np[i]), + "class_id": cls_id, + } + ) + return out + except Exception as e: + record_error("vision_detector", "run_yolo_ultralytics", e) + return [] + + @staticmethod + def _prepare_output_rows(output) -> np.ndarray: + if isinstance(output, (list, tuple)): + chunks = [] + for out in output: + rows = VisionDetector._prepare_output_rows(out) + if rows.size > 0: + chunks.append(rows) + if not chunks: + return np.empty((0, 0), dtype=np.float32) + try: + return np.concatenate(chunks, axis=0) + except Exception: + return chunks[0] + + arr = np.asarray(output) + if arr.size == 0: + return np.empty((0, 0), dtype=np.float32) + + if arr.ndim >= 4: + arr = arr.reshape(arr.shape[0], -1, arr.shape[-1]) + + if arr.ndim == 3: + if arr.shape[0] == 1: + arr = arr[0] + else: + arr = arr.reshape(-1, arr.shape[-1]) + elif arr.ndim == 2: + pass + elif arr.ndim == 1: + arr = arr.reshape(1, -1) + else: + arr = arr.reshape(-1, 1) + + if arr.ndim != 2: + return np.empty((0, 0), dtype=np.float32) + + # Typical YOLO ONNX output can be [84, 8400], transpose to [8400, 84]. + if arr.shape[0] < arr.shape[1] and arr.shape[1] > 64 and arr.shape[0] <= 256: + arr = arr.T + + return arr.astype(np.float32, copy=False) + + @staticmethod + def _decode_conf_and_class(row: np.ndarray) -> tuple[float, int] | None: + n = int(row.shape[0]) + if n < 5: + return None + + # End-to-end format: [x1, y1, x2, y2, conf, class_id] + if ( + n == 6 + and row[2] > row[0] + and row[3] > row[1] + and (row[2] > 2.0 or row[3] > 2.0 or row[0] < 0.0 or row[1] < 0.0) + and 0.0 <= float(row[4]) <= 1.0 + and abs(float(row[5]) - round(float(row[5]))) <= 1e-3 + ): + return float(row[4]), int(round(float(row[5]))) + + obj = max(0.0, float(row[4])) + if n <= 5: + return obj, 0 + + class_scores = row[5:] + cls_id = int(np.argmax(class_scores)) + cls_score = max(0.0, float(class_scores[cls_id])) + + if obj <= 1.5: + conf = obj * cls_score + else: + conf = cls_score + return float(conf), cls_id + + @staticmethod + def _coords_to_xywh(coords: np.ndarray, frame_w: int, frame_h: int) -> tuple[int, int, int, int] | None: + if coords.shape[0] < 4: + return None + + a, b, c, d = (float(coords[0]), float(coords[1]), float(coords[2]), float(coords[3])) + max_abs = max(abs(a), abs(b), abs(c), abs(d)) + + # xyxy-style + if c > a and d > b: + if max_abs <= 2.0: + x1, y1 = a * frame_w, b * frame_h + x2, y2 = c * frame_w, d * frame_h + else: + x1, y1, x2, y2 = a, b, c, d + else: + # cx, cy, w, h style (YOLO default) + if max_abs <= 2.0: + cx, cy = a * frame_w, b * frame_h + bw, bh = c * frame_w, d * frame_h + else: + cx, cy = a, b + bw, bh = c, d + x1 = cx - (bw / 2.0) + y1 = cy - (bh / 2.0) + x2 = cx + (bw / 2.0) + y2 = cy + (bh / 2.0) + + x1_i = max(0, min(frame_w - 1, int(round(x1)))) + y1_i = max(0, min(frame_h - 1, int(round(y1)))) + x2_i = max(0, min(frame_w, int(round(x2)))) + y2_i = max(0, min(frame_h, int(round(y2)))) + + w_i = max(0, x2_i - x1_i) + h_i = max(0, y2_i - y1_i) + if w_i < 4 or h_i < 4: + return None + return x1_i, y1_i, w_i, h_i + + def _decode_yolo_output(self, output, frame_w: int, frame_h: int, conf_thresh: float, class_filter: int | None): + rows = self._prepare_output_rows(output) + if rows.size == 0: + return [] + + candidates = [] + rects = [] + confs = [] + for row in rows: + conf_and_class = self._decode_conf_and_class(row) + if conf_and_class is None: + continue + conf, class_id = conf_and_class + if conf < conf_thresh: + continue + if class_filter is not None and int(class_id) != int(class_filter): + continue + xywh = self._coords_to_xywh(row[:4], frame_w=frame_w, frame_h=frame_h) + if xywh is None: + continue + x, y, w, h = xywh + candidates.append({"x": x, "y": y, "w": w, "h": h, "conf": float(conf), "class_id": int(class_id)}) + rects.append([int(x), int(y), int(w), int(h)]) + confs.append(float(conf)) + + if not candidates: + return [] + + try: + idxs = cv2.dnn.NMSBoxes(rects, confs, conf_thresh, self._nms_iou_thresh) + except Exception: + idxs = None + + if idxs is None or len(idxs) == 0: + return candidates + + if isinstance(idxs, np.ndarray): + keep = [int(i) for i in idxs.flatten().tolist()] + else: + keep = [] + for i in idxs: + if isinstance(i, (list, tuple, np.ndarray)): + keep.append(int(i[0])) + else: + keep.append(int(i)) + + filtered = [] + for idx in keep: + if 0 <= idx < len(candidates): + filtered.append(candidates[idx]) + return filtered + + def _run_yolo_onnx(self, net, frame, conf_thresh: float, class_filter: int | None = None): + if net is None or frame is None: + return [] + try: + blob = cv2.dnn.blobFromImage(frame, 1.0 / 255.0, self._dnn_input_size, swapRB=True, crop=False) + net.setInput(blob) + output = None + try: + names = net.getUnconnectedOutLayersNames() + if names: + output = net.forward(names) + except Exception: + output = None + if output is None: + output = net.forward() + h, w = frame.shape[:2] + return self._decode_yolo_output(output, frame_w=w, frame_h=h, conf_thresh=conf_thresh, class_filter=class_filter) + except Exception as e: + record_error("vision_detector", "run_yolo_onnx", e) + return [] + + @staticmethod + def _bbox_iou(a: tuple[int, int, int, int], b: tuple[int, int, int, int]) -> float: + ax, ay, aw, ah = a + bx, by, bw, bh = b + ax2, ay2 = ax + aw, ay + ah + bx2, by2 = bx + bw, by + bh + + ix1 = max(ax, bx) + iy1 = max(ay, by) + ix2 = min(ax2, bx2) + iy2 = min(ay2, by2) + iw = max(0, ix2 - ix1) + ih = max(0, iy2 - iy1) + inter = float(iw * ih) + if inter <= 0.0: + return 0.0 + union = float(aw * ah + bw * bh) - inter + if union <= 0.0: + return 0.0 + return inter / union + + def _detect_person_boxes(self, frame, tracker): + if self._detector_backend == "yolo" and self._person_net is not None: + if self._yolo_runtime == "ultralytics": + raw = self._run_yolo_ultralytics( + self._person_net, + frame, + conf_thresh=self._person_score_thresh, + class_filter=self._person_class_id, + ) + else: + raw = self._run_yolo_onnx( + self._person_net, + frame, + conf_thresh=self._person_score_thresh, + class_filter=self._person_class_id, + ) + boxes_raw = [(int(d["x"]), int(d["y"]), int(d["w"]), int(d["h"])) for d in raw] + assigned = tracker.update(boxes_raw) + + boxes = [] + for (cid, box) in assigned: + best_conf = 0.0 + for det in raw: + dbox = (int(det["x"]), int(det["y"]), int(det["w"]), int(det["h"])) + iou = self._bbox_iou(tuple(box), dbox) + if iou > 0.5: + best_conf = max(best_conf, float(det.get("conf", 0.0))) + boxes.append( + { + "x": int(box[0]), + "y": int(box[1]), + "w": int(box[2]), + "h": int(box[3]), + "id": int(cid), + "conf": float(best_conf), + } + ) + return boxes + + if self._detector_backend == "yolo" and self._person_net is None and not self._warned_yolo_unavailable: + self._warned_yolo_unavailable = True + logger.warning("VisionDetector: YOLO person model unavailable at runtime; using normal detector.") + + if not self._warned_person_fallback: + self._warned_person_fallback = True + logger.warning("VisionDetector: person fallback enabled (Haar face boxes used as person proxies).") + + gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) + faces = self._face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=4, minSize=(30, 30)) + boxes_raw = [tuple(map(int, f)) for f in faces] + assigned = tracker.update(boxes_raw) + return [ + {"x": int(b[0]), "y": int(b[1]), "w": int(b[2]), "h": int(b[3]), "id": int(i), "conf": 1.0} + for (i, b) in assigned + ] + + def _detect_face_boxes(self, frame): + if self._detector_backend == "yolo" and self._face_net is not None: + if self._yolo_runtime == "ultralytics": + raw = self._run_yolo_ultralytics( + self._face_net, + frame, + conf_thresh=self._face_score_thresh, + class_filter=None, + ) + else: + raw = self._run_yolo_onnx(self._face_net, frame, conf_thresh=self._face_score_thresh, class_filter=None) + return [ + { + "x": int(d["x"]), + "y": int(d["y"]), + "w": int(d["w"]), + "h": int(d["h"]), + "conf": float(d.get("conf", 0.0)), + } + for d in raw + ] + + gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) + faces = self._face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=4, minSize=(30, 30)) + return [{"x": int(x), "y": int(y), "w": int(w), "h": int(h), "conf": 1.0} for (x, y, w, h) in faces] + + def _detect_groups(self, person_boxes): + if len(person_boxes) < self._group_min_people: + return [] + + centers = [] + for b in person_boxes: + cx = float(b.get("x", 0.0)) + (float(b.get("w", 0.0)) / 2.0) + cy = float(b.get("y", 0.0)) + (float(b.get("h", 0.0)) / 2.0) + centers.append((cx, cy)) + + n = len(person_boxes) + visited = set() + components = [] + link_dist_sq = float(self._group_link_distance_px) * float(self._group_link_distance_px) + + for i in range(n): + if i in visited: + continue + stack = [i] + comp = [] + while stack: + cur = stack.pop() + if cur in visited: + continue + visited.add(cur) + comp.append(cur) + cx, cy = centers[cur] + for j in range(n): + if j in visited: + continue + dx = cx - centers[j][0] + dy = cy - centers[j][1] + if (dx * dx + dy * dy) <= link_dist_sq: + stack.append(j) + components.append(comp) + + groups = [] + gid = 1 + for comp in components: + if len(comp) < self._group_min_people: + continue + xs = [int(person_boxes[k]["x"]) for k in comp] + ys = [int(person_boxes[k]["y"]) for k in comp] + x2s = [int(person_boxes[k]["x"] + person_boxes[k]["w"]) for k in comp] + y2s = [int(person_boxes[k]["y"] + person_boxes[k]["h"]) for k in comp] + x1 = min(xs) + y1 = min(ys) + x2 = max(x2s) + y2 = max(y2s) + groups.append( + { + "id": gid, + "size": int(len(comp)), + "members": [int(person_boxes[k].get("id", 0)) for k in comp], + "x": int(x1), + "y": int(y1), + "w": int(max(0, x2 - x1)), + "h": int(max(0, y2 - y1)), + } + ) + gid += 1 + + groups.sort(key=lambda g: (-int(g.get("size", 0)), int(g.get("id", 0)))) + return groups + + def start(self): + if self._thread and self._thread.is_alive(): + return + self._stop.clear() + self._thread = Thread(target=self._run, daemon=True) + self._thread.start() + + def stop(self): + self._stop.set() + if self._thread: + self._thread.join(timeout=1.0) + self._close_depth_pipeline() + try: + if self._video_cap is not None: + self._video_cap.release() + except Exception as e: + record_error("vision_detector", "stop_release_video", e) + + def latest(self): + with self._latest_lock: + return dict(self._latest) + + def set_hard_lock(self, enabled: bool): + self._hard_target_lock_enabled = bool(enabled) + + def lock_target_from_snapshot(self, snapshot: dict | None = None, lock_group: bool = False): + s = snapshot or self.latest() + self._locked_target_type = "" + self._locked_group_id = None + self._locked_subject_id = None + + if lock_group: + groups = s.get("group_boxes") or [] + if groups: + try: + g = max( + groups, + key=lambda x: (int(x.get("size", 0)), float(x.get("w", 0.0)) * float(x.get("h", 0.0))), + ) + except Exception: + g = groups[0] + gid = g.get("id") + members = g.get("members") or [] + try: + self._locked_group_id = int(gid) if gid is not None else None + except Exception: + self._locked_group_id = None + try: + self._locked_subject_id = int(members[0]) if members else None + except Exception: + self._locked_subject_id = None + if self._locked_group_id is not None: + self._locked_target_type = "group" + + if self._locked_target_type != "group": + sid = s.get("subject_id") + if sid is None: + boxes = s.get("boxes") or [] + if boxes: + try: + sid = max(boxes, key=lambda x: float(x.get("w", 0.0)) * float(x.get("h", 0.0))).get("id") + except Exception: + sid = boxes[0].get("id") + try: + self._locked_subject_id = int(sid) if sid is not None else None + except Exception: + self._locked_subject_id = None + if self._locked_subject_id is not None: + self._locked_target_type = "subject" + + self._subject_lost_count = 0 + + def unlock_target(self): + self._locked_target_type = "" + self._locked_group_id = None + self._locked_subject_id = None + self._subject_lost_count = 0 + + def lock_subject(self, subject_id: int | None = None): + if subject_id is None: + snap = self.latest() + subject_id = snap.get("subject_id") + try: + self._locked_subject_id = int(subject_id) if subject_id is not None else None + except Exception: + self._locked_subject_id = None + self._locked_group_id = None + self._locked_target_type = "subject" if self._locked_subject_id is not None else "" + self._subject_lost_count = 0 + + def lock_subject_from_snapshot(self, snapshot: dict | None = None): + s = snapshot or self.latest() + sid = s.get("subject_id") + if sid is None: + boxes = s.get("boxes") or [] + if boxes: + b = max(boxes, key=lambda x: float(x.get("w", 0.0)) * float(x.get("h", 0.0))) + sid = b.get("id") + self.lock_subject(sid) + + def unlock_subject(self): + self.unlock_target() + + def _close_depth_pipeline(self): + if self._rs_pipeline is not None: + try: + self._rs_pipeline.stop() + except Exception: + pass + self._rs_pipeline = None + self._rs_profile = None + self._depth_ok = False + + def _ensure_depth_pipeline(self, force: bool = False): + if not self._depth_enabled or not _HAS_RS: + self._depth_ok = False + return False + if self._rs_pipeline is not None and not force: + self._depth_ok = True + return True + now = time.time() + if (not force) and (now - self._last_rs_restart) < 2.0: + return self._rs_pipeline is not None + self._last_rs_restart = now + self._close_depth_pipeline() + try: + pipe = rs.pipeline() + cfg = rs.config() + cfg.enable_stream(rs.stream.depth, 640, 480, rs.format.z16, 30) + self._rs_profile = pipe.start(cfg) + self._rs_pipeline = pipe + self._depth_ok = True + if force: + self._depth_restarts += 1 + logger.info("VisionDetector: RealSense depth pipeline started") + return True + except Exception as e: + self._rs_pipeline = None + self._rs_profile = None + self._depth_ok = False + logger.warning(f"VisionDetector: depth pipeline unavailable: {e}") + return False + + def _recover_inputs(self): + logger.warning("VisionDetector: recovering camera/depth inputs") + self._camera_restarts += 1 + try: + self._camera.release() + except Exception as e: + record_error("vision_detector", "recover_inputs_release", e) + try: + self._camera.initialize() + except Exception as e: + record_error("vision_detector", "recover_inputs_initialize", e) + self._ensure_depth_pipeline(force=True) + self._no_frame_count = 0 + + @staticmethod + def _coerce_depth_payload(depth_payload, subject_box=None): + if depth_payload is None: + return None + if isinstance(depth_payload, (int, float)): + d = float(depth_payload) + return d if d > 0.0 else None + + if isinstance(depth_payload, np.ndarray): + arr = depth_payload + h, w = arr.shape[:2] + if subject_box: + x = max(0, int(subject_box.get("x", 0))) + y = max(0, int(subject_box.get("y", 0))) + bw = max(1, int(subject_box.get("w", 1))) + bh = max(1, int(subject_box.get("h", 1))) + x2 = min(w, x + bw) + y2 = min(h, y + bh) + roi = arr[y:y2, x:x2] + else: + roi = arr + if roi.size <= 0: + return None + vals = roi[roi > 0] + if vals.size <= 0: + return None + med = float(np.median(vals)) + if arr.dtype in (np.uint16, np.int16, np.uint32, np.int32): + med *= 0.001 # mm -> m + return med if med > 0.0 else None + return None + + def _estimate_depth_m(self, subject_box=None, depth_payload=None): + d = self._coerce_depth_payload(depth_payload, subject_box=subject_box) + if d is not None: + self._depth_ok = True + return d + + if not self._ensure_depth_pipeline(force=False): + self._depth_ok = False + return None + try: + frames = self._rs_pipeline.poll_for_frames() + if not frames: + return None + depth_frame = frames.get_depth_frame() + if not depth_frame: + return None + w = depth_frame.get_width() + h = depth_frame.get_height() + if subject_box: + cx = int(subject_box.get("x", 0) + (subject_box.get("w", 0) / 2)) + cy = int(subject_box.get("y", 0) + (subject_box.get("h", 0) / 2)) + else: + cx, cy = int(w / 2), int(h / 2) + cx = max(0, min(w - 1, cx)) + cy = max(0, min(h - 1, cy)) + d = float(depth_frame.get_distance(cx, cy)) + if d <= 0.0: + self._depth_ok = False + return None + self._depth_ok = True + return d + except Exception: + self._depth_ok = False + return None + + def _extract_frame_and_depth(self): + if self._video_cap is not None: + try: + ret, frame = self._video_cap.read() + if not ret: + self._video_cap.set(cv2.CAP_PROP_POS_FRAMES, 0) + ret, frame = self._video_cap.read() + self._camera_ok = bool(ret and frame is not None) + return frame, None + except Exception: + self._camera_ok = False + return None, None + + if direct_camera_client.is_enabled(): + try: + frame = direct_camera_client.frame_bgr(timeout=1.5) + if frame is not None: + self._camera_ok = True + return frame, None + except Exception: + pass + + try: + frame = self._camera.capture_frame() + self._camera_ok = frame is not None + return frame, None + except Exception: + self._camera_ok = False + return None, None + + def _select_subject(self, boxes, groups=None): + groups = groups or [] + if not boxes: + self._subject_lost_count += 1 + if (not self._hard_target_lock_enabled) and self._subject_lost_count > self._subject_lock_lost_frames: + self._locked_subject_id = None + self._locked_group_id = None + self._locked_target_type = "" + return None, False + + self._subject_lost_count = 0 + if self._hard_target_lock_enabled and self._locked_group_id is not None: + locked_group = None + for g in groups: + try: + if int(g.get("id", -1)) == int(self._locked_group_id): + locked_group = g + break + except Exception: + continue + if locked_group is None: + self._target_switch_blocked_count += 1 + return None, False + members = set() + try: + members = {int(x) for x in (locked_group.get("members") or [])} + except Exception: + members = set() + cands = [b for b in boxes if int(b.get("id", -1)) in members] + if not cands: + self._target_switch_blocked_count += 1 + return None, False + best = max(cands, key=lambda b: float(b.get("w", 0.0)) * float(b.get("h", 0.0))) + try: + self._locked_subject_id = int(best.get("id")) + except Exception: + pass + return best, True + + if self._locked_subject_id is not None: + for b in boxes: + if int(b.get("id", -1)) == int(self._locked_subject_id): + return b, True + if self._hard_target_lock_enabled: + self._target_switch_blocked_count += 1 + return None, False + + # No lock: select largest target. + best = max(boxes, key=lambda b: float(b.get("w", 0.0)) * float(b.get("h", 0.0))) + return best, True + + def _check_interaction_intent(self, boxes, subject_box, depth_m, now): + max_area = 0.0 + for b in boxes: + try: + area = max(0.0, float(b.get("w", 0.0))) * max(0.0, float(b.get("h", 0.0))) + if area > max_area: + max_area = area + except Exception: + continue + + self._area_history.append(max_area) + area_first = self._area_history[0] if self._area_history else 0.0 + is_close_area = max_area >= self._proximity_threshold + is_approach_area = len(self._area_history) >= self._history_len and (max_area - area_first) >= self._approach_delta + + approach_speed = 0.0 + is_close_depth = False + is_approach_depth = False + if depth_m is not None: + self._depth_history.append((now, float(depth_m))) + if len(self._depth_history) >= 2: + t0, d0 = self._depth_history[0] + dt = max(1e-3, now - float(t0)) + approach_speed = max(0.0, (float(d0) - float(depth_m)) / dt) + is_close_depth = float(depth_m) <= self._min_depth_m + is_approach_depth = approach_speed >= self._min_approach_speed_mps + else: + self._depth_history.clear() + + if depth_m is not None: + is_close = is_close_depth + is_approaching = is_approach_depth + else: + is_close = is_close_area + is_approaching = is_approach_area + + subject_visible = subject_box is not None + intent_detected = bool(subject_visible and (is_close or is_approaching)) + return { + "intent_detected": intent_detected, + "max_area": float(max_area), + "is_close": bool(is_close), + "is_approaching": bool(is_approaching), + "depth_m": float(depth_m) if depth_m is not None else None, + "approach_speed_mps": float(approach_speed), + } + + def _run(self): + interval = max(0.01, 1.0 / max(1.0, self.poll_hz)) + tracker = CentroidTracker() + + while not self._stop.is_set(): + t0 = time.time() + now = time.time() + self._refresh_detector_backend(now) + frame, depth_payload = self._extract_frame_and_depth() + if frame is None: + self._no_frame_count += 1 + if self._no_frame_count >= self._recover_after_no_frame: + self._recover_inputs() + intent = self._check_interaction_intent([], None, None, now) + with self._latest_lock: + self._latest.update( + { + "frame_time": now, + "detector_backend": self._effective_backend(), + "yolo_runtime": self._yolo_runtime, + "face_count": 0, + "person_count": 0, + "group_count": 0, + "group_size": 0, + "group_detected": False, + "boxes": [], + "face_boxes": [], + "group_boxes": [], + "frame": None, + "subject_id": self._locked_subject_id, + "subject_box": None, + "subject_visible": False, + "subject_locked": self._locked_subject_id is not None, + "target_lock_active": bool(self._locked_subject_id is not None or self._locked_group_id is not None), + "target_lock_type": str(self._locked_target_type or ""), + "target_lock_id": self._locked_group_id if self._locked_group_id is not None else self._locked_subject_id, + "target_switch_blocked_count": int(self._target_switch_blocked_count), + "camera_ok": bool(self._camera_ok), + "depth_ok": bool(self._depth_ok), + "camera_restarts": int(self._camera_restarts), + "depth_restarts": int(self._depth_restarts), + **intent, + } + ) + time.sleep(interval) + continue + + self._no_frame_count = 0 + try: + person_boxes = self._detect_person_boxes(frame, tracker) + face_boxes = self._detect_face_boxes(frame) + groups = self._detect_groups(person_boxes) + group_size = max((int(g.get("size", 0)) for g in groups), default=0) + + subject_box, subject_visible = self._select_subject(person_boxes, groups=groups) + depth_m = self._estimate_depth_m(subject_box=subject_box, depth_payload=depth_payload) + intent = self._check_interaction_intent(person_boxes, subject_box, depth_m, now) + + with self._latest_lock: + self._latest.update( + { + "frame_time": now, + "detector_backend": self._effective_backend(), + "yolo_runtime": self._yolo_runtime, + "face_count": len(face_boxes), + "person_count": len(person_boxes), + "group_count": len(groups), + "group_size": int(group_size), + "group_detected": bool(group_size >= self._group_min_people), + "boxes": person_boxes, + "face_boxes": face_boxes, + "group_boxes": groups, + "frame": frame.copy() if frame is not None else None, + "subject_id": subject_box.get("id") if subject_box else self._locked_subject_id, + "subject_box": dict(subject_box) if isinstance(subject_box, dict) else None, + "subject_visible": bool(subject_visible), + "subject_locked": self._locked_subject_id is not None, + "target_lock_active": bool(self._locked_subject_id is not None or self._locked_group_id is not None), + "target_lock_type": str(self._locked_target_type or ""), + "target_lock_id": self._locked_group_id if self._locked_group_id is not None else self._locked_subject_id, + "target_switch_blocked_count": int(self._target_switch_blocked_count), + "camera_ok": bool(self._camera_ok), + "depth_ok": bool(self._depth_ok), + "camera_restarts": int(self._camera_restarts), + "depth_restarts": int(self._depth_restarts), + **intent, + } + ) + except Exception as e: + record_error("vision_detector", "run_loop_detect", e) + logger.warning(f"VisionDetector: detect failed: {e}") + intent = self._check_interaction_intent([], None, None, now) + with self._latest_lock: + self._latest.update( + { + "frame_time": now, + "detector_backend": self._effective_backend(), + "yolo_runtime": self._yolo_runtime, + "face_count": 0, + "person_count": 0, + "group_count": 0, + "group_size": 0, + "group_detected": False, + "boxes": [], + "face_boxes": [], + "group_boxes": [], + "frame": frame.copy() if frame is not None else None, + "subject_id": self._locked_subject_id, + "subject_box": None, + "subject_visible": False, + "subject_locked": self._locked_subject_id is not None, + "target_lock_active": bool(self._locked_subject_id is not None or self._locked_group_id is not None), + "target_lock_type": str(self._locked_target_type or ""), + "target_lock_id": self._locked_group_id if self._locked_group_id is not None else self._locked_subject_id, + "target_switch_blocked_count": int(self._target_switch_blocked_count), + "camera_ok": bool(self._camera_ok), + "depth_ok": bool(self._depth_ok), + "camera_restarts": int(self._camera_restarts), + "depth_restarts": int(self._depth_restarts), + **intent, + } + ) + + dt = time.time() - t0 + time.sleep(max(0.0, interval - dt)) + + +class CentroidTracker: + """Small centroid tracker assigning incremental IDs to objects.""" + + def __init__(self, max_disappeared: int = 10, max_distance: int = 80): + self.next_id = 1 + self.objects = {} # id -> centroid + self.disappeared = {} # id -> frames disappeared + self.max_disappeared = max_disappeared + self.max_distance = max_distance + + def _centroid(self, box): + x, y, w, h = box + return (int(x + w / 2), int(y + h / 2)) + + def register(self, box): + cid = self.next_id + self.next_id += 1 + cent = self._centroid(box) + self.objects[cid] = cent + self.disappeared[cid] = 0 + return cid + + def deregister(self, cid): + del self.objects[cid] + del self.disappeared[cid] + + def update(self, boxes): + """boxes: list of (x, y, w, h), returns list of (id, box).""" + if len(boxes) == 0: + remove = [] + for cid in list(self.disappeared.keys()): + self.disappeared[cid] += 1 + if self.disappeared[cid] > self.max_disappeared: + remove.append(cid) + for cid in remove: + self.deregister(cid) + return [] + + input_centroids = [self._centroid(b) for b in boxes] + + if len(self.objects) == 0: + assigned = [] + for b in boxes: + cid = self.register(b) + assigned.append((cid, b)) + return assigned + + object_ids = list(self.objects.keys()) + object_centroids = list(self.objects.values()) + + D = np.linalg.norm(np.array(object_centroids)[:, None, :] - np.array(input_centroids)[None, :, :], axis=2) + rows = D.min(axis=1).argsort() + cols = D.argmin(axis=1)[rows] + + used_rows = set() + used_cols = set() + assigned = [] + + for r, c in zip(rows, cols): + if r in used_rows or c in used_cols: + continue + if D[r, c] > self.max_distance: + continue + cid = object_ids[r] + self.objects[cid] = input_centroids[c] + self.disappeared[cid] = 0 + assigned.append((cid, boxes[c])) + used_rows.add(r) + used_cols.add(c) + + for i, b in enumerate(boxes): + if i in used_cols: + continue + cid = self.register(b) + assigned.append((cid, b)) + + for i, cid in enumerate(object_ids): + if i in used_rows: + continue + self.disappeared[cid] += 1 + if self.disappeared[cid] > self.max_disappeared: + self.deregister(cid) + + return assigned + + +if __name__ == "__main__": + logging.basicConfig(level=logging.INFO) + v = VisionDetector() + v.start() + try: + for _ in range(30): + s = v.latest() + logger.info( + "people=%s faces=%s groups=%s intent=%s time=%s", + s.get("person_count", 0), + s.get("face_count", 0), + s.get("group_count", 0), + s.get("intent_detected", False), + s.get("frame_time", 0.0), + ) + time.sleep(0.5) + finally: + v.stop() diff --git a/Modes/Manual/__init__.py b/Modes/Manual/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/Modes/Manual/controller.py b/Modes/Manual/controller.py new file mode 100644 index 0000000..0b99240 --- /dev/null +++ b/Modes/Manual/controller.py @@ -0,0 +1,96 @@ +# controller.py +import time +import struct +from pathlib import Path + +from unitree_sdk2py.idl.unitree_hg.msg.dds_ import LowState_ + + +def auto_pick_iface() -> str: + try: + net_dir = Path("/sys/class/net") + if not net_dir.exists(): + return "lo" + names = [p.name for p in net_dir.iterdir() if p.is_dir()] + for pref in ("en", "eth", "wl"): + for n in names: + if n != "lo" and n.startswith(pref): + return n + for n in names: + if n != "lo": + return n + return "lo" + except Exception: + return "lo" + + +class unitreeRemoteController: + def __init__(self): + self.Lx = 0; self.Rx = 0; self.Ry = 0; self.Ly = 0 + self.L1 = 0; self.L2 = 0; self.R1 = 0; self.R2 = 0 + self.A = 0; self.B = 0; self.X = 0; self.Y = 0 + self.Up = 0; self.Down = 0; self.Left = 0; self.Right = 0 + self.Select = 0; self.F1 = 0; self.F3 = 0; self.Start = 0 + + def parse_botton(self, data1, data2): + self.R1 = (data1 >> 0) & 1; self.L1 = (data1 >> 1) & 1 + self.Start = (data1 >> 2) & 1; self.Select = (data1 >> 3) & 1 + self.R2 = (data1 >> 4) & 1; self.L2 = (data1 >> 5) & 1 + self.F1 = (data1 >> 6) & 1; self.F3 = (data1 >> 7) & 1 + self.A = (data2 >> 0) & 1; self.B = (data2 >> 1) & 1 + self.X = (data2 >> 2) & 1; self.Y = (data2 >> 3) & 1 + self.Up = (data2 >> 4) & 1; self.Right = (data2 >> 5) & 1 + self.Down = (data2 >> 6) & 1; self.Left = (data2 >> 7) & 1 + + def parse_key(self, data): + offsets = [4, 8, 12, 20] # Lx, Rx, Ry, Ly + self.Lx, self.Rx, self.Ry, self.Ly = [struct.unpack(' bool: + return (time.time() - self.last_state_time) < self.watchdog_timeout + + def combo_r2x(self) -> bool: + s = self.controller_state + return bool(s.get("R2", 0) and s.get("X", 0)) + + def combo_r2l1(self) -> bool: + s = self.controller_state + return bool(s.get("R2", 0) and s.get("L1", 0)) + + def hard_cancel_combo(self) -> bool: + """ + Global safety cancel combo. + Keep this as the single mapping point so all runtimes (manual/AI) + can share the same hard-cancel behavior. + """ + return self.combo_r2l1() diff --git a/Modes/Manual/replay_engine.py b/Modes/Manual/replay_engine.py new file mode 100644 index 0000000..c3570c5 --- /dev/null +++ b/Modes/Manual/replay_engine.py @@ -0,0 +1,243 @@ +# replay_engine.py +import json +import time +from pathlib import Path + +from unitree_sdk2py.core.channel import ChannelPublisher +from unitree_sdk2py.idl.default import unitree_hg_msg_dds__LowCmd_ +from unitree_sdk2py.idl.unitree_hg.msg.dds_ import LowCmd_ +from unitree_sdk2py.utils.crc import CRC +from Core.Logger import Logs + +G1_NUM_MOTOR = 29 +ENABLE_ARM_SDK_INDEX = 29 +REPLAY_HZ = 60.0 + +KP_HIGH = 300.0 +KD_HIGH = 3.0 +KP_LOW = 80.0 +KD_LOW = 3.0 +KP_WRIST = 40.0 +KD_WRIST = 1.5 + +WEAK_MOTORS = [4, 10, 15, 16, 17, 18, 22, 23, 24, 25] +WRIST_MOTORS = [19, 20, 21, 26, 27, 28] + +sanad_logger = Logs() +sanad_logger.LogEngine("G1_Logs", "replay_engine") + +def load_home_pose(home_path: Path): + try: + last_valid_q = None + with open(home_path, "r") as f: + for line in f: + d = json.loads(line) + if "q" in d and len(d["q"]) == G1_NUM_MOTOR: + last_valid_q = d["q"] + if last_valid_q: + sanad_logger.print_and_log(f"โœ… Loaded Home Pose from {home_path}", "info") + return last_valid_q + sanad_logger.print_and_log(f"โš ๏ธ Home file has no valid q: {home_path}", "warning") + except FileNotFoundError: + sanad_logger.print_and_log(f"โš ๏ธ Home file not found: {home_path}", "warning") + + sanad_logger.print_and_log("โš ๏ธ Using Default Home (Arms at 0.0)", "warning") + return [0.0] * G1_NUM_MOTOR + + +class ReplayWithHome: + def __init__(self, hub, watchdog_disable_after=1.0): + self.hub = hub + + self.low_cmd = unitree_hg_msg_dds__LowCmd_() + self.crc = CRC() + + self.arm_pub = ChannelPublisher("rt/arm_sdk", LowCmd_) + self.arm_pub.Init() + + self.watchdog_disable_after = float(watchdog_disable_after) + self.is_playing = False + + def _cancel(self) -> bool: + if hasattr(self.hub, "hard_cancel_combo"): + return bool(self.hub.hard_cancel_combo()) + return bool(self.hub.combo_r2l1()) + + def _send_frame(self, arm_target_q, body_lock_q): + self.low_cmd.motor_cmd[ENABLE_ARM_SDK_INDEX].q = 1.0 + + for i in range(G1_NUM_MOTOR): + self.low_cmd.motor_cmd[i].mode = 1 + self.low_cmd.motor_cmd[i].dq = 0 + self.low_cmd.motor_cmd[i].tau = 0 + + self.low_cmd.motor_cmd[i].q = arm_target_q[i] if i >= 15 else body_lock_q[i] + + if i in WEAK_MOTORS: + self.low_cmd.motor_cmd[i].kp = KP_LOW + self.low_cmd.motor_cmd[i].kd = KD_LOW + elif i in WRIST_MOTORS: + self.low_cmd.motor_cmd[i].kp = KP_WRIST + self.low_cmd.motor_cmd[i].kd = KD_WRIST + else: + self.low_cmd.motor_cmd[i].kp = KP_HIGH + self.low_cmd.motor_cmd[i].kd = KD_HIGH + + self.low_cmd.crc = self.crc.Crc(self.low_cmd) + self.arm_pub.Write(self.low_cmd) + + def _disable_sdk(self): + sanad_logger.print_and_log("๐Ÿ”Œ Disabling SDK...", "info") + self.low_cmd.motor_cmd[ENABLE_ARM_SDK_INDEX].q = 0.0 + self.low_cmd.crc = self.crc.Crc(self.low_cmd) + for _ in range(10): + self.arm_pub.Write(self.low_cmd) + time.sleep(0.02) + + def _return_home(self, last_q, body_lock_q, home_q, steps=180): + sanad_logger.print_and_log("๐Ÿก Returning arms to HOME...", "info") + for k in range(steps): + stale_for = time.time() - self.hub.last_state_time + if stale_for > self.watchdog_disable_after: + sanad_logger.print_and_log("๐Ÿ›‘ WATCHDOG: lost during home. Disable SDK.", "error") + self._disable_sdk() + return + + if not self.hub.fresh(): + self._send_frame(last_q, body_lock_q) + time.sleep(1.0 / REPLAY_HZ) + continue + + alpha = k / steps + interp_q = list(last_q) + for j in range(15, 29): + interp_q[j] = (1 - alpha) * last_q[j] + alpha * home_q[j] + self._send_frame(interp_q, body_lock_q) + time.sleep(1.0 / REPLAY_HZ) + + sanad_logger.print_and_log("โœ… Home Reached.", "info") + + def run(self, replay_file: Path, home_file: Path, speed: float, trigger_callback=None): + self.is_playing = True + cancel = False + + try: + sanad_logger.print_and_log(f"๐ŸŽฌ Replay: {replay_file}", "info") + while not self.hub.first_state: + time.sleep(0.05) + + home_q = load_home_pose(home_file) + body_lock_q = [self.hub.low_state.motor_state[i].q for i in range(G1_NUM_MOTOR)] + + frames = [] + with open(replay_file, "r") as f: + for line in f: + line = line.strip() + if not line: + continue + try: + d = json.loads(line) + except Exception: + continue + if "q" in d and "t" in d: + frames.append(d) + + if not frames: + sanad_logger.print_and_log("โŒ No frames found.", "error") + return + + file_start_q = frames[0]["q"] + last_played_q = file_start_q + + # Move to start + for k in range(60): + if self._cancel(): + cancel = True + sanad_logger.print_and_log("๐Ÿ›‘ CANCEL during move-to-start.", "warning") + break + + if not self.hub.fresh(): + self._send_frame(last_played_q, body_lock_q) + time.sleep(1.0 / REPLAY_HZ) + continue + + alpha = k / 60 + interp_q = list(body_lock_q) + for j in range(15, 29): + interp_q[j] = (1 - alpha) * body_lock_q[j] + alpha * file_start_q[j] + self._send_frame(interp_q, body_lock_q) + last_played_q = interp_q + time.sleep(1.0 / REPLAY_HZ) + + # Play + if not cancel: + sanad_logger.print_and_log("โ–ถ๏ธ Playing...", "info") + play_elapsed = 0.0 + last_real = time.time() + + while True: + if self._cancel(): + cancel = True + sanad_logger.print_and_log("๐Ÿ›‘ CANCEL during replay.", "warning") + break + + stale_for = time.time() - self.hub.last_state_time + if stale_for > self.watchdog_disable_after: + sanad_logger.print_and_log("๐Ÿ›‘ WATCHDOG: lost. Disable SDK.", "error") + self._disable_sdk() + return + + if not self.hub.fresh(): + self._send_frame(last_played_q, body_lock_q) + time.sleep(1.0 / REPLAY_HZ) + continue + + now = time.time() + dt = now - last_real + last_real = now + play_elapsed += dt * speed + + target = None + for fr in frames: + if fr["t"] - frames[0]["t"] >= play_elapsed: + target = fr + break + if target is None: + break + + # If this frame contains a trigger marker, call the callback (non-blocking) + try: + meta = target.get("meta") if isinstance(target, dict) else None + if trigger_callback and meta: + # support meta: "trigger" or meta: {"trigger": true} + call_cb = False + if isinstance(meta, str) and "trigger" in meta.lower(): + call_cb = True + elif isinstance(meta, dict) and meta.get("trigger"): + call_cb = True + if call_cb: + try: + from threading import Thread as _Thread + _Thread(target=lambda: trigger_callback(target), daemon=True).start() + sanad_logger.print_and_log("๐Ÿ”” Trigger callback invoked (replay).", "info") + except Exception as _e: + sanad_logger.print_and_log(f"Trigger callback error: {_e}", "warning") + except Exception: + pass + + self._send_frame(target["q"], body_lock_q) + last_played_q = target["q"] + time.sleep(1.0 / REPLAY_HZ) + + # Always home + self._return_home(last_played_q, body_lock_q, home_q, steps=180) + self._disable_sdk() + + except Exception as e: + sanad_logger.print_and_log(f"โŒ Replay exception: {e}", "error") + try: + self._disable_sdk() + except Exception: + pass + finally: + self.is_playing = False diff --git a/Modes/Manual/trigger_loop.py b/Modes/Manual/trigger_loop.py new file mode 100644 index 0000000..3e87f00 --- /dev/null +++ b/Modes/Manual/trigger_loop.py @@ -0,0 +1,183 @@ +# trigger_loop.py +import asyncio +import threading +import time +from pathlib import Path + +from Core import settings as config +from Core.Logger import Logs +from Server.capture_service import capture_with_replay_sync, replay_timing_profile + + +sanad_logger = Logs() +sanad_logger.LogEngine("G1_Logs", "trigger_loop") + +async def _play_prompt(voice, prompt_key: str, fallback_text: str) -> bool: + try: + return bool(await voice.play_prompt_key(prompt_key, fallback_text)) + except Exception as e: + sanad_logger.print_and_log(f"โš ๏ธ Prompt playback failed for {prompt_key}: {e}", message_type="warning") + return False + + +async def _play_capture_prompt(voice, prompt_key: str, fallback_text: str) -> bool: + try: + return bool( + await voice.play_prompt_key( + prompt_key, + fallback_text="", + allow_gemini_fallback=False, + mode_override="audio", + ) + ) + except Exception as e: + sanad_logger.print_and_log(f"โš ๏ธ Capture prompt playback failed for {prompt_key}: {e}", message_type="warning") + return False + + +async def _play_manual_capture_prompt_sequence( + voice, + shot_delay_sec: float, + cancel_event: threading.Event, +): + start_ts = time.time() + await _play_capture_prompt( + voice, + "countdown_intro", + "Look at the camera, stay ready, hold your pose with me, keep still, keep your smile soft, and in a moment I will count down for the photo.", + ) + announced = set() + + while True: + if cancel_event.is_set(): + raise asyncio.CancelledError + + remaining = max(0.0, shot_delay_sec - (time.time() - start_ts)) + sec_left = int(round(remaining)) + + if sec_left in (3, 2, 1) and sec_left not in announced: + announced.add(sec_left) + await _play_capture_prompt(voice, f"count_{sec_left}", f"{sec_left}...") + elif sec_left <= 0 and 0 not in announced: + announced.add(0) + await _play_capture_prompt(voice, "smile", "Smile.") + return + + await asyncio.sleep(0.05) + + +async def trigger_loop( + hub, + replay, + voice, + take_photo_sync_callable=None, + ws=None, +): + """ + R2+X: + - play the fixed capture prompt sequence (recorded audio by default) + - run unified capture pipeline (replay + timed capture/upload) + R2+L1: + - cancels pending delayed photo (replay cancel handled in replay engine) + Debounce: + - must release R2+X to re-trigger + - blocks retrigger for PHOTO_TOTAL_SEC window + """ + r2x_prev = False + waiting_release = False + photo_busy_until = 0.0 + + pending_photo_task: asyncio.Task | None = None + pending_audio_task: asyncio.Task | None = None + pending_capture_cancel: threading.Event | None = None + + def _hard_cancel_pressed() -> bool: + if hasattr(hub, "hard_cancel_combo"): + return bool(hub.hard_cancel_combo()) + return bool(hub.combo_r2l1()) + + async def delayed_photo(delay_sec: float, cancel_event: threading.Event): + # Unified pipeline: replay + trigger/fallback capture + upload touch. + base_prefix = None # keep existing default naming behavior + photo_result = await asyncio.to_thread( + capture_with_replay_sync, + replay_runner=replay, + replay_file=config.REPLAY_FILE, + home_file=config.HOME_FILE, + delay_sec=delay_sec, + prefix=base_prefix, + speed=1.0, + cancel_event=cancel_event, + ) + sanad_logger.print_and_log(f"๐Ÿ“ธ Capture pipeline result: {photo_result}", message_type="info") + if cancel_event.is_set(): + return + if isinstance(photo_result, str) and not photo_result.startswith("[ERR]"): + await _play_capture_prompt( + voice, + "photo_saved_thanks", + "Thank you. Photo saved. Do not forget to check your photos.", + ) + + while True: + await asyncio.sleep(0.02) + if not hub.first_state: + continue + + # Cancel combo: cancel pending photo + if _hard_cancel_pressed(): + if pending_capture_cancel is not None: + pending_capture_cancel.set() + if pending_photo_task and not pending_photo_task.done(): + pending_photo_task.cancel() + if pending_audio_task and not pending_audio_task.done(): + pending_audio_task.cancel() + sanad_logger.print_and_log("๐Ÿ›‘ HARD CANCEL: pending photo cancelled (R2+L1).", message_type="warning") + + r2x_now = hub.combo_r2x() + + # Require release before next trigger + if waiting_release: + if not r2x_now: + waiting_release = False + r2x_prev = r2x_now + continue + + # Do not retrigger while replay is playing + if replay.is_playing: + r2x_prev = r2x_now + continue + + now = time.time() + + # Rising edge trigger + not inside busy window + if r2x_now and (not r2x_prev) and (now >= photo_busy_until): + waiting_release = True + + # 1) schedule manual countdown speech using the same prompt keys as AI mode + if pending_photo_task and not pending_photo_task.done(): + if pending_capture_cancel is not None: + pending_capture_cancel.set() + pending_photo_task.cancel() + if pending_audio_task and not pending_audio_task.done(): + pending_audio_task.cancel() + + timing = replay_timing_profile(config.REPLAY_FILE) + delay = float(timing.get("capture_offset_sec") or max(0.0, min(config.PHOTO_DELAY_SEC, config.PHOTO_TOTAL_SEC))) + replay_duration = float(timing.get("duration_sec") or 0.0) + photo_busy_until = now + max(config.PHOTO_TOTAL_SEC, replay_duration + 3.2, delay + config.PHOTO_THANKS_SEC) + sanad_logger.print_and_log( + "๐ŸŽฏ Manual capture timing: " + f"replay={Path(config.REPLAY_FILE).name} " + f"duration={replay_duration:.3f}s " + f"shot_at={delay:.3f}s " + f"source={timing.get('capture_source', 'config_fallback')}", + message_type="info", + ) + pending_capture_cancel = threading.Event() + pending_audio_task = asyncio.create_task( + _play_manual_capture_prompt_sequence(voice, delay, pending_capture_cancel) + ) + pending_photo_task = asyncio.create_task(delayed_photo(delay, pending_capture_cancel)) + + r2x_prev = r2x_now diff --git a/Modes/__init__.py b/Modes/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/README.md b/README.md new file mode 100644 index 0000000..c840f6d --- /dev/null +++ b/README.md @@ -0,0 +1,268 @@ +# AI Photographer + +Production-oriented robot photographer stack for Unitree G1. + +## Quick Start + +1. Set API key in config: + - edit `Data/Settings/config.json` -> `gemini.api_key` +2. Run launcher: + - `cd Scripts && ./photo_sanad.sh` + +Launcher behavior: +- resets `mode.current_mode` to the configured `mode.default_mode` on each launch, +- resolves the active PulseAudio speaker/microphone and exports them for the runtime, +- starts the direct camera service (`Core/direct_camera_service.py` in the `teleimager` conda env) for the full runtime path, +- starts Gemini runtime (`gemini` conda env), +- runs `Gemini/voice_sanad.py` as the main process, +- keeps `manual` as the default startup mode unless changed in `Data/Settings/config.json`, +- keeps `Gemini/voice_sanad.py`, the dashboard server, the direct camera server, and replay/trigger services running in the full runtime path across mode switches, +- arms autonomous services in the full runtime path so switching dashboard mode from `manual` to `ai` works without a restart. + +Optional startup profile: +- `MANUAL_LEAN_RUNTIME=1` + - manual-mode voice + dashboard only + - skips direct camera, DDS, replay, uploader, and autonomous startup + - capture/replay services are unavailable in that profile + - this is an explicit reduced profile, not the normal production mode + +## Project Layout + +- `Scripts/` + - startup and ops shell entrypoints + - `photo_sanad.sh`, `fix_realsense_usb.sh` + - `direct_camera_samples_server.py` remains as a compatibility wrapper + - `fix_realsense_usb.sh` supports `--check`, `--fix`, and `--serials` +- `Data/` + - categorized runtime assets and state + - `Settings/config.json` + - `Scripts/photo_command_ai.txt`, `Scripts/sanad_script.txt` + - `Runtime/upload_db.json`, generated runtime JSON state files + - `Settings/config.json -> camera.preferred_realsense_serial` selects the preferred default RealSense by serial + - generated runtime JSON files are created on demand during execution +- `Data/Audio/` + - fixed prerecorded AI situation prompts (`*.wav`) + - matching raw Gemini captures (`*_raw.wav`) +- `Data/Settings/audio_prompt_records.json` + - prompt recording metadata for files in `Data/Audio/` +- `photos/people/` + - AI face-recognition registry + - each returning guest gets a folder with face/scene references, metadata, and captured-photo links +- `photos/Captures/` + - final saved runtime captures from dashboard, manual trigger, and AI capture flow +- `photos/samples/` + - standalone direct-camera sample captures +- `Logs/` + - one stable log file per runtime component + - examples: `voice_sanad.log`, `gemini_voice.log`, `photo_server.log`, `direct_camera.log` +- `Web/` + - operator dashboard frontend (`gallery.html`, `gallery.js`, `style.css`) + - direct camera service frontend (`direct_camera.html`, `direct_camera.js`, `direct_camera.css`) +- `Data/G1/` + - replay/gesture motion files (`*.jsonl`) + - dashboard-recorded replay captures are saved directly here +- `Core/` + - shared runtime foundations (`settings.py`, `Logger.py`, `error_events.py`, `direct_camera_service.py`) + - `direct_camera_service.py` handles camera backend/API and serves its UI from `Web/` +- `Gemini/` + - voice orchestration (`voice_sanad.py`, `gemini_voice.py`, `sanad_text_utils.py`) +- `Server/` + - dashboard/API/capture/upload (`photo_server.py`, `capture_service.py`, `direct_camera_client.py`, `uploader.py`) +- `Modes/AI/` + - autonomous vision/intent/session manager (`autonomous_manager.py`, `vision_detector.py`, `camera_module.py`) +- `Modes/Manual/` + - controller + replay + trigger loop (`controller.py`, `replay_engine.py`, `trigger_loop.py`) + +## Runtime Modes + +Mode is persisted in `Data/Settings/config.json` under `mode.current_mode`: +- `manual` + - Gemini conversation stays available when `gemini.mic_enabled=true` + - voice `request_photo / yes_photo / no_photo` disabled + - `R2+X` replay/capture path stays available in the full runtime path + - `Gemini/voice_sanad.py`, dashboard server, direct camera server, and replay services stay running + - autonomous services can be armed in the background, but autonomous flow stays paused until mode becomes `ai` +- `ai` + - voice `request_photo / yes_photo / no_photo` enabled + - `R2+X` replay/capture path still works + - `Gemini/voice_sanad.py`, dashboard server, direct camera server, and replay services continue running without restart + - autonomous flow runs live when `AUTONOMOUS_ENABLE=1` + - on stable visual intent, AI identifies or enrolls a single guest, optionally greets with a short hand replay, asks for photo confirmation, guides guests into frame, then captures using the active replay during the shot when AI capture replay is enabled + - returning guests are recognized from `photos/people/` and can be greeted as returning visitors + +Command-mode functionality was extracted from this project and moved to: +- `G1_Lootah/AI_Command` + +## Remote Controls + +- `R2+X` + - replay + photographer talk + capture pipeline +- `R2+L1` + - global hard cancel safety combo + - active in runtime loops to cancel pending capture/replay and reset active interaction + +Mode APIs: +- `GET /api/mode` +- `GET /api/set_mode?mode=manual|ai` +- `GET /api/mode_policy` +- `GET /api/mic` +- `GET /api/set_mic?enabled=0|1` +- `GET /api/detector_backend` +- `GET /api/set_detector_backend?backend=normal|yolo` +- `GET /api/ai_readiness` +- `GET /api/ai_options` +- `GET /api/set_ai_options?hard_target_lock_enabled=0|1&retake_prompt_enabled=0|1&autonomous_greeting_replay_enabled=0|1&autonomous_greeting_replay_file=...&autonomous_capture_replay_enabled=0|1&face_recognition_enabled=0|1&face_recognition_threshold=...` +- `GET /api/autonomous_state` +- `GET /api/runtime_health` + +## Autonomous Flow + +Autonomous services are armed by environment: +- `AUTONOMOUS_ENABLE=1` + - allows `Modes/AI/autonomous_manager.py` to run inside `voice_sanad.py` + - in `manual` mode it stays paused + - core services still remain up in `manual` (`voice_sanad.py`, dashboard, direct camera server, replay/trigger) + - switching dashboard mode to `ai` starts autonomous flow live without a restart +- `AUTONOMOUS_ENABLE=0` + - disables autonomous manager entirely + - manual trigger loop + voice runtime still work + +Session state machine: +- `IDLE -> WAIT_CONFIRM -> FRAMING -> COUNTDOWN -> RETAKE_CONFIRM (optional) -> COMPLETE -> IDLE` +- strict readiness block state: `IDLE_BLOCKED` when required YOLO readiness is not met + +## Dashboard / API Highlights + +- `GET /` gallery dashboard +- `GET /preview.mjpg` live preview + - preview is off by default and starts only when requested from the dashboard + - preview camera/OpenCV is loaded lazily when preview is requested +- Camera control APIs: + - `GET /api/camera_health` + - `GET /api/camera_sources` + - `GET /api/set_camera_source?source=...` + - `GET /api/set_camera_resolution?width=...&height=...&fps=...` + - `GET /api/set_preferred_camera?serial=...` + - dashboard can switch camera source, show active camera info, change resolution live, and save a preferred RealSense serial into `Data/Settings/config.json` +- Audio prompt APIs: + - `GET /api/audio_prompts` + - `GET /api/set_audio_prompt_mode?mode=audio|gemini` + - `GET /api/set_audio_prompt_fallback?enabled=0|1` + - `GET /api/audio_prompt_record_status` + - `GET /api/download_audio_prompt?key=...` + - `GET /api/delete_audio_prompt?key=...` + - `POST /api/upload_audio_prompt` + - `POST /api/audio_prompt_record` + - dashboard can upload, replace, download, delete, inspect, and record prerecorded AI prompt clips stored in `Data/Audio/` + - dashboard can switch fixed AI situation speech between recorded audio and Gemini without restart +- `GET /api/autonomous_state` runtime autonomous state panel data (lock/retake/health fields) +- `GET /api/runtime_health` component health (WS/mic/speaker/gate/restarts) +- `GET /api/mic` and `GET /api/set_mic` + - microphone ON/OFF toggle for both modes +- `GET /api/ai_readiness` strict AI readiness + block reason +- `GET /api/ai_options` and `GET /api/set_ai_options` for hard lock/retake toggles +- Replay APIs: + - `GET /api/replays` + - `GET /api/get_replay` + - `GET /api/set_replay?name=...` + - `GET /api/delete_replay?name=...` + - `GET /api/rename_replay?old=...&new=...` + - `GET /api/download_replay?name=...` + - `GET /api/replay_record_status` + - `GET /api/replay_record_start?name=...&seconds=...` + - `GET /api/replay_test_status` + - `GET /api/test_replay?name=...` + - `POST /api/upload_replay` + - dashboard can record new replays into `Data/G1`, replay-test them, rename them, download them, delete them, upload new `.jsonl` replays, and set the active replay + - replay recording and replay test are allowed only while runtime mode is `manual` +- People APIs: + - `GET /api/people` + - `GET /api/person_image?id=...&kind=face|scene` + - `GET /api/download_person?id=...` + - `GET /api/delete_person?id=...` + - `GET /api/reset_people` + - `POST /api/upload_person` + - dashboard can upload face photos for future recognition, download a saved guest package, delete one guest, or reset the full registry +- `GET /api/capture` capture via unified pipeline +- `GET /api/photos`, `GET /api/sessions`, `GET /api/delete`, `GET /api/reupload` +- `GET /api/errors` structured error counters + +## Configuration + +Source of truth: +- `Data/Settings/config.json` loaded by `Core/settings.py` + +Environment overrides are supported (timing, ports, upload settings, camera, etc.). + +Direct camera serial selection precedence: +- `REALSENSE_SERIAL` +- `PREFERRED_REALSENSE_SERIAL` +- `Data/Settings/config.json -> camera.preferred_realsense_serial` +- teleimager camera config serial +- any other detected RealSense + +Dashboard camera behavior: +- main production dashboard can switch between available camera sources without restarting the runtime +- camera status panel shows requested source, active source, backend, active profile, preferred serial, and active RealSense serial +- resolution changes are applied live through the direct camera service +- `Save As Default` stores the preferred RealSense serial into `Data/Settings/config.json` + +AI prerecorded prompt behavior: +- `Data/Audio/` stores fixed WAV clips by prompt key +- `Data/Settings/audio_prompt_records.json` stores prompt recording metadata and raw-output file references +- `audio_prompts.files` in `Data/Settings/config.json` maps each key to its filename +- `audio_prompts.mode` controls fixed AI situation speech: + - `audio`: use recorded clips first for AI situation prompts + - `gemini`: use Gemini speech instead for those same fixed prompts +- `audio_prompts.fallback_to_gemini` controls whether missing prompt clips fall back to Gemini text +- dashboard prompt library manages upload/download/delete, text-to-record generation, speech mode, and fallback state +- imported prerecorded prompts currently cover 18 situation keys; missing keys continue through Gemini fallback until recorded + +AI replay behavior: +- `vision.autonomous_greeting_replay_enabled` controls the short greeting gesture when intent stabilizes +- `vision.autonomous_greeting_replay_file` selects the greeting replay file +- `vision.autonomous_capture_replay_enabled` controls whether AI photo capture uses the active replay during the shot +- `replay.active_file` in `Data/Settings/config.json` is the single persisted active-replay setting +- the active replay is shared between manual `R2+X`, dashboard capture choreography, and AI capture when AI capture replay is enabled +- replay inventory is shared across the full `Data/G1` tree + +Face recognition behavior: +- `vision.face_recognition_enabled` enables single-guest recognition/enrollment in AI mode +- `vision.face_recognition_threshold` controls the similarity threshold for matching a returning guest +- new guests are enrolled into `photos/people/` +- successful AI captures are linked back into the guest folder for future reference + +Vision model configuration (`Data/Settings/config.json` -> `vision`): +- `detection_backend`: `normal` or `yolo` (runtime switchable from dashboard in AI mode) +- `yolo_runtime`: `ultralytics` (production) or `opencv` (legacy ONNX parser) +- `yolo_ultralytics_device`: inference device for ultralytics (`cpu`, `0`, `0,1`, ...) +- `person_yolo_onnx`: path to YOLO ONNX person model +- `face_yolo_onnx`: path to YOLO ONNX face model +- `group_min_people`: minimum people count to mark a group +- `group_link_distance_px`: max centroid-link distance for group clustering + +## Documentation + +- `Current_runtime.md`: detailed current runtime behavior and script chain. + +## Data Layout + +- `Data/Settings/` + - `config.json` +- `Data/Scripts/` + - `photo_command_ai.txt` + - `sanad_script.txt` +- `Data/Runtime/` + - runtime health/state/error JSON files +- `Data/Audio/` + - prerecorded AI prompt WAV files + - matching `_raw.wav` Gemini output captures +- `Data/Settings/audio_prompt_records.json` + - prompt recording metadata for files in `Data/Audio/` + +## Notes + +- `config.py` is intentionally removed; runtime config is JSON + env overrides. +- legacy AI mover/autonomous prototype scripts were removed from the production tree. +- Generated artifacts (`__pycache__`, runtime logs) should not be committed. +- Generated runtime files such as `Data/Runtime/runtime_health.json`, `Data/Runtime/autonomous_state.json`, `Data/Runtime/error_counters.json`, `Data/Runtime/error_events.jsonl`, and `Logs/*.log` may be absent in a clean checkout until the runtime starts. diff --git a/Scripts/direct_camera_samples_server.py b/Scripts/direct_camera_samples_server.py new file mode 100644 index 0000000..9f0328a --- /dev/null +++ b/Scripts/direct_camera_samples_server.py @@ -0,0 +1,20 @@ +#!/usr/bin/env python3 +""" +Compatibility wrapper for the direct camera service. + +The main camera service now lives in Core/direct_camera_service.py. +This wrapper is kept so older commands and scripts still work. +""" + +from pathlib import Path +import sys + +PROJECT_ROOT = Path(__file__).resolve().parent.parent +if str(PROJECT_ROOT) not in sys.path: + sys.path.insert(0, str(PROJECT_ROOT)) + +from Core.direct_camera_service import main + + +if __name__ == "__main__": + main() diff --git a/Scripts/fix_realsense_usb.sh b/Scripts/fix_realsense_usb.sh new file mode 100755 index 0000000..496249a --- /dev/null +++ b/Scripts/fix_realsense_usb.sh @@ -0,0 +1,122 @@ +#!/usr/bin/env bash +set -euo pipefail + +need_cmd() { + command -v "$1" >/dev/null 2>&1 || { echo "[ERR] Missing command: $1" >&2; exit 1; } +} + +need_cmd rs-enumerate-devices +need_cmd awk +need_cmd sed +need_cmd grep + +realsense_output() { + rs-enumerate-devices 2>/dev/null || true +} + +is_realsense_present() { + local out + out="$(realsense_output)" + echo "$out" | grep -qi "Intel RealSense" +} + +print_bool() { + if is_realsense_present; then + echo "true" + else + echo "false" + fi +} + +list_serials() { + local out + out="$(realsense_output)" + if ! echo "$out" | grep -qi "Intel RealSense"; then + return 0 + fi + + echo "$out" \ + | awk -F':' '/Serial Number/ {print $2}' \ + | sed 's/^[[:space:]]*//; s/[[:space:]]*$//' \ + | grep -v '^$' \ + | awk '!seen[$0]++' +} + +# Apply USB power settings to the RealSense sysfs path + its parent hub +apply_fix() { + local RS_OUT SERIAL PHY USB_NODE PARENT_HUB DEV_SYS HUB_SYS + + RS_OUT="$(realsense_output)" + if ! echo "$RS_OUT" | grep -qi "Intel RealSense"; then + # No device: just print false + echo "false" + return 0 + fi + + SERIAL="$(echo "$RS_OUT" | awk -F':' '/Serial Number/ {gsub(/[ \t]/,"",$2); print $2; exit}')" + PHY="$(echo "$RS_OUT" | awk -F':' '/Physical Port/ {print $2; exit}' | sed 's/^[ \t]*//')" + + # Extract USB node like "2-2.3" from Physical Port + USB_NODE="$(echo "$PHY" | grep -oE '/usb[0-9]+/[^ ]+' | sed -E 's#.*/usb[0-9]+/##' | cut -d'/' -f2 | head -n1 || true)" + if [[ -z "${USB_NODE:-}" ]]; then + USB_NODE="$(echo "$PHY" | grep -oE 'usb[0-9]+/[0-9]+-[0-9]+(\.[0-9]+)?' | sed 's#usb[0-9]+/##' | head -n1 || true)" + fi + + if [[ -z "${USB_NODE:-}" ]]; then + # Can't map sysfs; still detected though + echo "true" + return 0 + fi + + PARENT_HUB="${USB_NODE%%.*}" + DEV_SYS="/sys/bus/usb/devices/${USB_NODE}" + HUB_SYS="/sys/bus/usb/devices/${PARENT_HUB}" + + # Disable autosuspend globally (optional) + echo -1 | sudo tee /sys/module/usbcore/parameters/autosuspend >/dev/null || true + + apply_power_fix() { + local path="$1" + [[ -d "$path" ]] || return 0 + [[ -e "$path/power/control" ]] && echo on | sudo tee "$path/power/control" >/dev/null || true + [[ -e "$path/power/autosuspend" ]] && echo -1 | sudo tee "$path/power/autosuspend" >/dev/null || true + [[ -e "$path/power/autosuspend_delay_ms" ]] && echo 0 | sudo tee "$path/power/autosuspend_delay_ms" >/dev/null || true + } + + apply_power_fix "$HUB_SYS" + apply_power_fix "$DEV_SYS" + + # Final verification + print_bool +} + +usage() { + cat <<'EOF' +Usage: + bash fix_realsense_usb.sh --check # prints true/false only + bash fix_realsense_usb.sh --fix # applies fix then prints true/false + bash fix_realsense_usb.sh --serials # prints available RealSense serials, one per line +Default: --fix +EOF +} + +mode="${1:---fix}" + +case "$mode" in + --check) + print_bool + ;; + --fix) + apply_fix + ;; + --serials|--list-serials) + list_serials + ;; + -h|--help) + usage + ;; + *) + usage >&2 + exit 1 + ;; +esac diff --git a/Scripts/photo_sanad.sh b/Scripts/photo_sanad.sh new file mode 100755 index 0000000..dc3782f --- /dev/null +++ b/Scripts/photo_sanad.sh @@ -0,0 +1,568 @@ +#!/usr/bin/env bash +set -euo pipefail + +# ============================================================ +# photo_sanad.sh +# ------------------------------------------------------------ +# ONE command to run everything: +# ./photo_sanad.sh +# +# What it does: +# 1) Activates the camera env (py3.10) and starts the Core direct camera service in background +# 2) Activates gemini (py3.11) and runs Gemini/voice_sanad.py in foreground +# 3) Sets PulseAudio default sink/source (optional) +# 4) Sets PYTHONPATH for unitree_sdk2_python (so unitree_sdk2py imports work) +# 5) On exit, stops the direct camera server +# ============================================================ + +SCRIPT_DIR="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")" && pwd)" +DEFAULT_BASE_DIR="$(cd -- "$SCRIPT_DIR/.." && pwd)" +BASE_DIR="${BASE_DIR:-$DEFAULT_BASE_DIR}" +PY_FILE="$BASE_DIR/Gemini/voice_sanad.py" +RUN_USER="${SUDO_USER:-${USER:-$(id -un)}}" +RUN_USER_HOME="$(getent passwd "$RUN_USER" 2>/dev/null | cut -d: -f6 || true)" +if [[ -z "${RUN_USER_HOME:-}" ]]; then + RUN_USER_HOME="$HOME" +fi +RUN_USER_ID="$(id -u "$RUN_USER" 2>/dev/null || true)" +export HOME="$RUN_USER_HOME" +if [[ -n "${RUN_USER_ID:-}" ]] && [[ -d "/run/user/$RUN_USER_ID" ]]; then + export XDG_RUNTIME_DIR="/run/user/$RUN_USER_ID" + if [[ -S "$XDG_RUNTIME_DIR/pulse/native" ]]; then + export PULSE_SERVER="unix:$XDG_RUNTIME_DIR/pulse/native" + fi +fi + +# conda +CONDA_SH="${CONDA_SH:-$RUN_USER_HOME/miniconda3/etc/profile.d/conda.sh}" +ENV_TELE="teleimager" # Python 3.10 camera env (pyrealsense2) +ENV_GEM="gemini" # Python 3.11 +SDK_PY_PATH="${SDK_PY_PATH:-$RUN_USER_HOME/unitree_sdk2_python}" +DIRECT_CAMERA_PORT="${DIRECT_CAMERA_PORT:-8091}" +DIRECT_CAMERA_HOST="${DIRECT_CAMERA_HOST:-127.0.0.1}" +DIRECT_CAMERA_SOURCE="${DIRECT_CAMERA_SOURCE:-realsense}" +DIRECT_CAMERA_SCRIPT="${DIRECT_CAMERA_SCRIPT:-$BASE_DIR/Core/direct_camera_service.py}" +LEGACY_DIRECT_CAMERA_SCRIPT="$BASE_DIR/Scripts/direct_camera_samples_server.py" + +# Optional: choose your camera (if needed) +# export CAMERA_DEVICE=/dev/video2 +# export PHOTO_PREFIX=photo +export CAMERA_DEVICE="${CAMERA_DEVICE:-/dev/video0}" +export PHOTO_PREFIX="${PHOTO_PREFIX:-photo}" + +# RealSense fix/sudo behavior +SUDO_ENABLE_FIX="${SUDO_ENABLE_FIX:-1}" # 1=cache sudo so /api/fix can run +SUDO_PROMPT_ON_START="${SUDO_PROMPT_ON_START:-0}" # 1=allow interactive sudo prompt at startup +AUTO_FIX_ON_START="${AUTO_FIX_ON_START:-0}" # 1=run fix script once on startup +SUDO_KEEPALIVE_INTERVAL="${SUDO_KEEPALIVE_INTERVAL:-60}" +FIX_SCRIPT="${FIX_SCRIPT:-$BASE_DIR/Scripts/fix_realsense_usb.sh}" +SUDO_KEEPALIVE_PID="" +LOG_DIR="${LOG_DIR:-$BASE_DIR/Logs}" +PHOTO_SERVER_PORT="${PHOTO_SERVER_PORT:-8080}" +PRE_KILL_OLD="${PRE_KILL_OLD:-1}" # 1=stop stale sanad/camera services from previous runs +FREE_PORT_BEFORE_START="${FREE_PORT_BEFORE_START:-1}" # 1=kill listeners on PHOTO_SERVER_PORT +ALLOW_EXISTING_PORT_SERVER="${ALLOW_EXISTING_PORT_SERVER:-0}" # 1=allow attaching to an already-running gallery server + +# PulseAudio device names (change if needed) +SINK="${SINK:-alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo}" +SOURCE="${SOURCE:-alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback}" + +# ALSA plugin fix (helps conda envs stop spamming ALSA errors) +if [[ -d "/usr/lib/aarch64-linux-gnu/alsa-lib" ]]; then + export ALSA_PLUGIN_DIR="/usr/lib/aarch64-linux-gnu/alsa-lib" +elif [[ -d "/usr/lib/alsa-lib" ]]; then + export ALSA_PLUGIN_DIR="/usr/lib/alsa-lib" +fi +if [[ -f "/usr/share/alsa/alsa.conf" ]]; then + export ALSA_CONFIG_PATH="/usr/share/alsa/alsa.conf" +fi +export ALSA_LOG_LEVEL=0 + +echo "๐Ÿ“ Base dir: $BASE_DIR" +echo "๐Ÿ‘ค Runtime user: $RUN_USER" +echo "๐Ÿ  Runtime home: $RUN_USER_HOME" +cd "$BASE_DIR" + +# ---------- logging dir ---------- +if ! mkdir -p "$LOG_DIR" >/dev/null 2>&1; then + LOG_DIR="$HOME/.ai_photographer_logs" + mkdir -p "$LOG_DIR" +fi +if ! touch "$LOG_DIR/.write_test" >/dev/null 2>&1; then + LOG_DIR="$HOME/.ai_photographer_logs" + mkdir -p "$LOG_DIR" + touch "$LOG_DIR/.write_test" >/dev/null 2>&1 || true +fi +rm -f "$LOG_DIR/.write_test" >/dev/null 2>&1 || true +export AI_PHOTOGRAPHER_LOG_DIR="$LOG_DIR" + +# ---------- stale-process cleanup ---------- +show_port_owner() { + local port="$1" + if command -v ss >/dev/null 2>&1; then + # shellcheck disable=SC2016 + ss -ltnp 2>/dev/null | awk -v p=":$port" '$4 ~ p {print $0}' || true + fi +} + +start_sudo_keepalive() { + ( + while true; do + sleep "$SUDO_KEEPALIVE_INTERVAL" + sudo -n true >/dev/null 2>&1 || exit 0 + done + ) & + SUDO_KEEPALIVE_PID=$! + echo "โœ… sudo cached (keepalive PID=$SUDO_KEEPALIVE_PID)" +} + +setup_sudo_cache() { + if [[ "$SUDO_ENABLE_FIX" != "1" ]]; then + return 0 + fi + + if ! command -v sudo >/dev/null 2>&1; then + echo "โš ๏ธ sudo not found; /api/fix cannot run privileged fixes." + return 0 + fi + + if sudo -n true >/dev/null 2>&1; then + echo "๐Ÿ” sudo credentials already cached." + start_sudo_keepalive + return 0 + fi + + if [[ "$SUDO_PROMPT_ON_START" == "1" && -t 0 ]]; then + echo "๐Ÿ” Preparing sudo for RealSense fix endpoint..." + if sudo -v; then + start_sudo_keepalive + else + echo "โš ๏ธ sudo auth failed; /api/fix may require manual terminal command." + fi + else + echo "โš ๏ธ sudo not cached. Use SUDO_PROMPT_ON_START=1 to allow startup prompt." + fi +} + +get_port_pids() { + local port="$1" + { + if command -v lsof >/dev/null 2>&1; then + lsof -t -iTCP:"$port" -sTCP:LISTEN -Pn 2>/dev/null || true + fi + if command -v ss >/dev/null 2>&1; then + ss -ltnp 2>/dev/null \ + | awk -v p=":$port" '$4 ~ p {print $0}' \ + | sed -n 's/.*pid=\([0-9][0-9]*\).*/\1/p' || true + fi + if command -v fuser >/dev/null 2>&1; then + fuser -n tcp "$port" 2>/dev/null | tr ' ' '\n' || true + fi + } | sed '/^[[:space:]]*$/d' | sort -u +} + +get_pid_cmdline() { + local pid="$1" + ps -o args= -p "$pid" 2>/dev/null || true +} + +kill_one_pid() { + local pid="$1" + local signal="${2:-TERM}" + local pgid="" + [[ -z "${pid:-}" ]] && return 0 + + if ! kill "-$signal" "$pid" >/dev/null 2>&1; then + sudo -n kill "-$signal" "$pid" >/dev/null 2>&1 || true + fi + + pgid="$(ps -o pgid= -p "$pid" 2>/dev/null | tr -d ' ' || true)" + if [[ -n "${pgid:-}" ]]; then + if ! kill "-$signal" "--" "-$pgid" >/dev/null 2>&1; then + sudo -n kill "-$signal" "--" "-$pgid" >/dev/null 2>&1 || true + fi + fi +} + +kill_port_owner() { + local port="$1" + local pids pid attempt + pids="$(get_port_pids "$port" || true)" + [[ -z "${pids:-}" ]] && return 0 + + echo "๐Ÿ›‘ Attempting to free port $port (PID(s): $(echo "$pids" | tr '\n' ' '))" + for attempt in 1 2 3; do + while IFS= read -r pid; do + [[ -z "${pid:-}" ]] && continue + if [[ "$attempt" -lt 3 ]]; then + kill_one_pid "$pid" TERM + else + kill_one_pid "$pid" KILL + fi + done <<< "$pids" + sleep 1 + pids="$(get_port_pids "$port" || true)" + [[ -z "${pids:-}" ]] && return 0 + if [[ "$attempt" -eq 2 ]]; then + echo "โš ๏ธ Port $port still busy, sending SIGKILL..." + fi + done +} + +report_port_owners() { + local port="$1" + local pids pid cmd + pids="$(get_port_pids "$port" || true)" + [[ -z "${pids:-}" ]] && return 0 + while IFS= read -r pid; do + [[ -z "${pid:-}" ]] && continue + cmd="$(get_pid_cmdline "$pid")" + echo " - PID $pid: ${cmd:-}" + done <<< "$pids" +} + +stop_stale_processes() { + echo "๐Ÿงฝ Checking stale processes..." + local stopped=0 + + # Previous Sanad app instances from same project copy + if pgrep -f "$BASE_DIR/Gemini/voice_sanad.py" >/dev/null 2>&1; then + echo "๐Ÿ›‘ Stopping previous voice_sanad.py processes..." + pkill -f "$BASE_DIR/Gemini/voice_sanad.py" >/dev/null 2>&1 || sudo -n pkill -f "$BASE_DIR/Gemini/voice_sanad.py" >/dev/null 2>&1 || true + stopped=1 + fi + # Legacy pre-restructure path support + if pgrep -f "$BASE_DIR/voice_sanad.py" >/dev/null 2>&1; then + echo "๐Ÿ›‘ Stopping previous legacy voice_sanad.py processes..." + pkill -f "$BASE_DIR/voice_sanad.py" >/dev/null 2>&1 || sudo -n pkill -f "$BASE_DIR/voice_sanad.py" >/dev/null 2>&1 || true + stopped=1 + fi + +# Previous direct camera servers + if pgrep -f "$DIRECT_CAMERA_SCRIPT" >/dev/null 2>&1; then + echo "๐Ÿ›‘ Stopping previous direct camera service processes..." + pkill -f "$DIRECT_CAMERA_SCRIPT" >/dev/null 2>&1 || sudo -n pkill -f "$DIRECT_CAMERA_SCRIPT" >/dev/null 2>&1 || true + stopped=1 + fi + if [[ "$DIRECT_CAMERA_SCRIPT" != "$LEGACY_DIRECT_CAMERA_SCRIPT" ]] && pgrep -f "$LEGACY_DIRECT_CAMERA_SCRIPT" >/dev/null 2>&1; then + echo "๐Ÿ›‘ Stopping previous legacy direct_camera_samples_server.py processes..." + pkill -f "$LEGACY_DIRECT_CAMERA_SCRIPT" >/dev/null 2>&1 || sudo -n pkill -f "$LEGACY_DIRECT_CAMERA_SCRIPT" >/dev/null 2>&1 || true + stopped=1 + fi + + # Give OS a moment to release sockets/resources. + if [[ "$stopped" -eq 1 ]]; then + sleep 1 + fi +} + +# Try to cache sudo early so stale cleanup can stop root-owned leftovers. +setup_sudo_cache + +if [[ "$PRE_KILL_OLD" == "1" ]]; then + stop_stale_processes +fi + +PORT_OWNER="$(show_port_owner "$PHOTO_SERVER_PORT" || true)" +if [[ -n "${PORT_OWNER:-}" ]]; then + echo "โš ๏ธ Port $PHOTO_SERVER_PORT currently in use:" + echo "$PORT_OWNER" +fi + +# ---------- conda init ---------- +if [[ ! -f "$CONDA_SH" ]]; then + echo "โŒ conda.sh not found: $CONDA_SH" + exit 1 +fi +# shellcheck disable=SC1090 +source "$CONDA_SH" + +# ---------- time sync wait ---------- +echo "โฐ Checking system time..." +while [ "$(date +%Y)" -lt 2025 ]; do + echo "โณ Waiting for time sync... $(date)" + sleep 2 +done +echo "โœ… Time synced: $(date)" + +# ---------- PulseAudio defaults (optional) ---------- +pick_pactl_device() { + local kind="$1" + local requested="$2" + local current="" + local names="" + local chosen="" + + if [[ "$kind" == "sink" ]]; then + current="$(pactl info 2>/dev/null | sed -n 's/^Default Sink: //p' | head -n1)" + names="$(pactl list short sinks 2>/dev/null | awk '{print $2}')" + else + current="$(pactl info 2>/dev/null | sed -n 's/^Default Source: //p' | head -n1)" + names="$(pactl list short sources 2>/dev/null | awk '{print $2}')" + fi + + if [[ -n "${requested:-}" ]] && echo "$names" | grep -Fxq "$requested"; then + chosen="$requested" + elif [[ -n "${current:-}" ]] && echo "$names" | grep -Fxq "$current"; then + chosen="$current" + else + chosen="$(echo "$names" | grep -Ei 'anker|powerconf|usb' | head -n1 || true)" + if [[ -z "${chosen:-}" ]]; then + chosen="$(echo "$names" | head -n1 || true)" + fi + fi + + printf '%s' "$chosen" +} + +if command -v pactl >/dev/null 2>&1; then + echo "๐Ÿ”Š Checking audio server..." + READY=0 + for _ in {1..20}; do + if timeout 0.3s pactl info >/dev/null 2>&1; then + READY=1 + break + fi + sleep 0.3 + done + + if [[ "$READY" -eq 1 ]]; then + RESOLVED_SINK="$(pick_pactl_device sink "$SINK")" + RESOLVED_SOURCE="$(pick_pactl_device source "$SOURCE")" + + if [[ -n "${RESOLVED_SINK:-}" ]]; then + if [[ "$RESOLVED_SINK" != "$SINK" ]]; then + echo "โš ๏ธ Requested speaker not found. Using โ†’ $RESOLVED_SINK" + else + echo "๐ŸŽง Setting default speaker โ†’ $RESOLVED_SINK" + fi + pactl set-default-sink "$RESOLVED_SINK" || true + else + echo "โš ๏ธ No PulseAudio sink found. Continuing without speaker selection." + fi + + if [[ -n "${RESOLVED_SOURCE:-}" ]]; then + if [[ "$RESOLVED_SOURCE" != "$SOURCE" ]]; then + echo "โš ๏ธ Requested microphone not found. Using โ†’ $RESOLVED_SOURCE" + else + echo "๐ŸŽค Setting default microphone โ†’ $RESOLVED_SOURCE" + fi + pactl set-default-source "$RESOLVED_SOURCE" || true + else + echo "โš ๏ธ No PulseAudio source found. Continuing without microphone selection." + fi + + ACTIVE_SINK="$(pactl info 2>/dev/null | sed -n 's/^Default Sink: //p' | head -n1 || true)" + ACTIVE_SOURCE="$(pactl info 2>/dev/null | sed -n 's/^Default Source: //p' | head -n1 || true)" + [[ -n "${ACTIVE_SINK:-}" ]] && echo "๐Ÿ”ˆ Active speaker default: $ACTIVE_SINK" + [[ -n "${ACTIVE_SOURCE:-}" ]] && echo "๐ŸŽ™๏ธ Active microphone default: $ACTIVE_SOURCE" + else + echo "โš ๏ธ PulseAudio/PipeWire not ready. Continuing anyway." + fi +else + echo "โš ๏ธ pactl not found. Skipping audio defaults." +fi + +# ---------- paths check ---------- +if [[ ! -f "$PY_FILE" ]]; then + echo "โŒ voice_sanad.py not found: $PY_FILE" + exit 1 +fi + +# ---------- startup mode / runtime profile ---------- +# Primary config lives in Data/Settings/config.json. Keep legacy Data/config.json +# and Scripts/config.json fallbacks so older robot copies can still boot during migrations. +MODE_FROM_CFG="$(python - <<'PY' +import json +from pathlib import Path +p = Path("Data/Settings/config.json") +legacy_candidates = [Path("Data/config.json"), Path("Scripts/config.json")] +if not p.exists(): + for legacy in legacy_candidates: + if legacy.exists(): + p = legacy + break +mode = "manual" +try: + if p.exists(): + d = json.loads(p.read_text(encoding="utf-8")) + mode_block = d.get("mode") or {} + mode = str(mode_block.get("default_mode", mode_block.get("current_mode", "manual"))).strip().lower() +except Exception: + mode = "manual" +if mode == "command": + mode = "ai" +try: + if p.exists(): + d = json.loads(p.read_text(encoding="utf-8")) + mode_block = d.get("mode") or {} + mode_block["current_mode"] = mode + d["mode"] = mode_block + p.write_text(json.dumps(d, indent=2), encoding="utf-8") +except Exception: + pass +print(mode if mode in ("manual", "ai") else "manual") +PY +)" +echo "โœ… Runtime mode reset to default: $MODE_FROM_CFG" + +PHOTO_OUTPUT_DIR="$(python - <<'PY' +import json +from pathlib import Path +base = Path(".").resolve() +p = Path("Data/Settings/config.json") +legacy_candidates = [Path("Data/config.json"), Path("Scripts/config.json")] +if not p.exists(): + for legacy in legacy_candidates: + if legacy.exists(): + p = legacy + break +value = "AI_Photographer/photos/Captures" +try: + if p.exists(): + d = json.loads(p.read_text(encoding="utf-8")) + paths = d.get("paths") or {} + value = str(paths.get("photos_dir", value) or value).strip() +except Exception: + pass +target = Path(value).expanduser() +if not target.is_absolute(): + parts = target.parts + if parts and parts[0] == base.name: + target = (base.parent / target).resolve() + else: + target = (base / target).resolve() +print(target) +PY +)" +echo "๐Ÿ—‚๏ธ Capture output dir: $PHOTO_OUTPUT_DIR" + +if [[ -z "${MANUAL_LEAN_RUNTIME:-}" ]]; then + if [[ "$MODE_FROM_CFG" == "manual" ]]; then + export MANUAL_LEAN_RUNTIME=0 + else + export MANUAL_LEAN_RUNTIME=0 + fi +fi +if [[ "$MODE_FROM_CFG" == "manual" && "${MANUAL_LEAN_RUNTIME}" == "1" ]]; then + echo "๐Ÿชถ Manual lean runtime enabled: direct camera/DDS/replay startup will be skipped." +fi + +# ---------- start direct camera server (py3.10) ---------- +TELE_PID="" +TELE_LOG="$LOG_DIR/direct_camera.log" +if [[ "$MODE_FROM_CFG" == "manual" && "${MANUAL_LEAN_RUNTIME}" == "1" ]]; then + echo "๐Ÿ“ท Skipping direct camera startup for lean manual runtime." +else + kill_port_owner "$DIRECT_CAMERA_PORT" + echo "๐Ÿ Activating camera env: $ENV_TELE" + conda activate "$ENV_TELE" + + echo "๐Ÿ camera env python: $(which python)" + python -c "import sys; print('โœ… camera env sys.executable:', sys.executable); print('โœ… camera env sys.version:', sys.version.split()[0])" + + echo "๐Ÿ“ท Starting direct camera server in background..." + python "$DIRECT_CAMERA_SCRIPT" \ + --camera "$DIRECT_CAMERA_SOURCE" \ + --host "$DIRECT_CAMERA_HOST" \ + --port "$DIRECT_CAMERA_PORT" \ + --samples-dir "$PHOTO_OUTPUT_DIR" \ + --capture-prefix "$PHOTO_PREFIX" \ + --capture-ext jpg >"$TELE_LOG" 2>&1 & + TELE_PID=$! + echo "โœ… direct camera PID=$TELE_PID log=$TELE_LOG" +fi + +cleanup() { + echo "" + echo "๐Ÿงน Cleaning up..." + if [[ -n "${SUDO_KEEPALIVE_PID:-}" ]] && kill -0 "$SUDO_KEEPALIVE_PID" >/dev/null 2>&1; then + echo "๐Ÿ›‘ Stopping sudo keepalive PID=$SUDO_KEEPALIVE_PID" + kill "$SUDO_KEEPALIVE_PID" >/dev/null 2>&1 || true + wait "$SUDO_KEEPALIVE_PID" >/dev/null 2>&1 || true + fi + if [[ -n "${TELE_PID:-}" ]] && kill -0 "$TELE_PID" >/dev/null 2>&1; then + echo "๐Ÿ›‘ Stopping direct camera server PID=$TELE_PID" + kill "$TELE_PID" >/dev/null 2>&1 || true + wait "$TELE_PID" >/dev/null 2>&1 || true + fi + echo "โœ… Done." +} +trap cleanup EXIT INT TERM + +# Give server time to start +if [[ -n "${TELE_PID:-}" ]]; then + sleep 2 +fi + +# ---------- run sanad (py3.11) ---------- +echo "๐Ÿ Activating gemini env: $ENV_GEM" +conda activate "$ENV_GEM" + +echo "๐Ÿ gemini python: $(which python)" +python -c "import sys; print('โœ… gemini sys.executable:', sys.executable); print('โœ… gemini sys.version:', sys.version.split()[0])" + +# ---------- autonomous enable policy ---------- +# If AUTONOMOUS_ENABLE is not explicitly provided, derive from startup default mode: +# - full runtime -> arm autonomous services so AI mode can start live without restart +# - lean manual runtime -> keep disabled +if [[ -z "${AUTONOMOUS_ENABLE:-}" ]]; then + if [[ "$MODE_FROM_CFG" == "manual" && "${MANUAL_LEAN_RUNTIME}" == "1" ]]; then + export AUTONOMOUS_ENABLE=0 + else + export AUTONOMOUS_ENABLE=1 + fi + echo "๐Ÿค– AUTONOMOUS_ENABLE auto-set to $AUTONOMOUS_ENABLE (mode=$MODE_FROM_CFG, lean_manual=${MANUAL_LEAN_RUNTIME})" +else + echo "๐Ÿค– AUTONOMOUS_ENABLE preset to $AUTONOMOUS_ENABLE" +fi + +# Ensure unitree_sdk2py can import using the local project modules. +export PYTHONPATH="$SDK_PY_PATH:${BASE_DIR}:${PYTHONPATH:-}" +echo "๐Ÿ”ง Using local AI_Photographer modules" +export DIRECT_CAMERA_ENABLED="${DIRECT_CAMERA_ENABLED:-1}" +export DIRECT_CAMERA_SERVER_URL="${DIRECT_CAMERA_SERVER_URL:-http://$DIRECT_CAMERA_HOST:$DIRECT_CAMERA_PORT}" + +echo "๐Ÿ”ง PYTHONPATH=$PYTHONPATH" +echo "๐Ÿ“ท DIRECT_CAMERA_SERVER_URL=$DIRECT_CAMERA_SERVER_URL" +echo "๐Ÿ”ง ALSA_PLUGIN_DIR=${ALSA_PLUGIN_DIR:-"(not set)"}" +echo "๐Ÿ”ง ALSA_CONFIG_PATH=${ALSA_CONFIG_PATH:-"(not set)"}" +echo "๐ŸŽฅ CAMERA_DEVICE=$CAMERA_DEVICE" +echo "๐Ÿ–ผ๏ธ PHOTO_PREFIX=$PHOTO_PREFIX" +echo "๐Ÿ”ง FIX_SCRIPT=$FIX_SCRIPT" +echo "๐Ÿชต LOG_DIR=$LOG_DIR" + +# sudo cache is handled earlier by setup_sudo_cache. + +if [[ "$AUTO_FIX_ON_START" == "1" ]]; then + if [[ -f "$FIX_SCRIPT" ]]; then + echo "๐Ÿ› ๏ธ Running RealSense fix on startup..." + if sudo bash "$FIX_SCRIPT" --fix; then + echo "โœ… RealSense fix completed." + else + echo "โš ๏ธ RealSense fix failed; continuing startup." + fi + else + echo "โš ๏ธ AUTO_FIX_ON_START=1 but fix script not found: $FIX_SCRIPT" + fi +fi + +# Final port cleanup right before launching main app (after sudo caching) +if [[ "$FREE_PORT_BEFORE_START" == "1" ]]; then + kill_port_owner "$PHOTO_SERVER_PORT" +fi +PORT_OWNER="$(show_port_owner "$PHOTO_SERVER_PORT" || true)" +if [[ -n "${PORT_OWNER:-}" ]]; then + echo "โš ๏ธ Port $PHOTO_SERVER_PORT remains in use:" + echo "$PORT_OWNER" + report_port_owners "$PHOTO_SERVER_PORT" + if [[ "$ALLOW_EXISTING_PORT_SERVER" != "1" ]]; then + echo "โŒ Refusing to continue while a stale server still owns port $PHOTO_SERVER_PORT." + echo " Set ALLOW_EXISTING_PORT_SERVER=1 only if you intentionally want to attach to the existing server." + exit 1 + fi +fi + +echo "๐Ÿš€ Starting Sanad AI_Photographer..." +# Run in foreground (so trap cleanup runs when process exits) +python "$PY_FILE" diff --git a/Server/__init__.py b/Server/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/Server/capture_service.py b/Server/capture_service.py new file mode 100644 index 0000000..671e854 --- /dev/null +++ b/Server/capture_service.py @@ -0,0 +1,396 @@ +# capture_service.py +import os +import subprocess +import threading +import time +from pathlib import Path + +from Core.error_events import record_error +from Core import settings as config +from Server import direct_camera_client + +SERVER_DIR = Path(__file__).resolve().parent +PROJECT_ROOT = SERVER_DIR.parent + +FIX_SCRIPT = str((PROJECT_ROOT / "Scripts" / "fix_realsense_usb.sh").resolve()) +UPLOAD_NOW_FLAG = (PROJECT_ROOT / "Scripts" / "upload_now.flag").resolve() + + +def _touch_upload_now_flag(): + try: + UPLOAD_NOW_FLAG.parent.mkdir(parents=True, exist_ok=True) + UPLOAD_NOW_FLAG.write_text(str(time.time()), encoding="utf-8") + except Exception as e: + record_error("capture_service", "touch_upload_now_flag", e) + + +def _next_photo_name(out_dir: Path, prefix: str, ext: str) -> Path: + base = out_dir / f"{prefix}.{ext}" + if not base.exists(): + return base + i = 1 + while True: + p = out_dir / f"{prefix}({i}).{ext}" + if not p.exists(): + return p + i += 1 + + +def take_photo_sync(prefix: str | None = None) -> str: + """ + Captures one photo and returns the saved path or a compact error. + Production runtime uses the direct camera service only. + """ + retry_count = max(0, int(config.read_watchdog_camera_capture_retry_count())) + retry_delay = max(0.0, float(config.read_watchdog_camera_capture_retry_delay_sec())) + total_attempts = max(1, retry_count + 1) + last_err = "[ERR] take_photo unknown error" + + for attempt in range(1, total_attempts + 1): + try: + env = os.environ.copy() + env.setdefault("PHOTOS_DIR", str(Path(config.PHOTOS_DIR).resolve())) + if prefix: + env["PHOTO_PREFIX"] = prefix + else: + env.setdefault("PHOTO_PREFIX", "photo") + if not direct_camera_client.is_enabled(): + last_err = "[ERR] direct camera service is disabled" + record_error( + "capture_service", + "take_photo_sync_attempt_failed", + context={"attempt": attempt, "total_attempts": total_attempts, "reason": "direct_camera_disabled"}, + ) + continue + + saved = direct_camera_client.capture( + prefix=env.get("PHOTO_PREFIX", "photo"), + ext=env.get("PHOTO_EXT", "jpg").strip().lstrip(".") or "jpg", + timeout=10.0, + ) + _touch_upload_now_flag() + return saved + except Exception as e: + last_err = f"[ERR] take_photo exception: {e}" + record_error( + "capture_service", + "take_photo_sync_exception", + e, + {"attempt": attempt, "total_attempts": total_attempts}, + ) + + if attempt < total_attempts and retry_delay > 0.0: + time.sleep(retry_delay) + + return last_err + + +def take_photo_test_sync() -> str: + """ + Takes a photo and deletes it immediately. Good as a camera health test. + Returns "OK" or an error string. + """ + result = take_photo_sync() + if result.startswith("/"): + try: + p = Path(result) + if p.exists(): + p.unlink() + return "OK" + except Exception as e: + return f"[WARN] captured but delete failed: {e}" + return result + + +def run_fix_realsense_sync() -> str: + """ + Runs fix_realsense_usb.sh. NOTE: script uses sudo tee -> needs passwordless sudo to fully work. + """ + try: + if not Path(FIX_SCRIPT).exists(): + return f"[ERR] fix script not found: {FIX_SCRIPT}" + + p = subprocess.run( + ["bash", FIX_SCRIPT], + capture_output=True, + text=True, + timeout=20, + ) + out = (p.stdout or "").strip() + err = (p.stderr or "").strip() + if p.returncode == 0: + return out or "OK" + return f"[ERR] fix script rc={p.returncode}\n{out}\n{err}".strip() + except Exception as e: + record_error("capture_service", "run_fix_realsense_sync_exception", e) + return f"[ERR] fix exception: {e}" + + +def replay_file_integrity(path: Path) -> dict: + """ + Checks: + - file exists + - has at least one frame with 'q' + - has at least one trigger marker (meta contains trigger) + """ + p = Path(path).resolve() + out = { + "ok": False, # usable replay (has frames) + "trigger_ok": False, # has explicit trigger markers + "path": str(p), + "exists": False, + "frames": 0, + "triggers": 0, + "error": "", + } + if not p.exists() or not p.is_file(): + out["error"] = "missing replay file" + return out + out["exists"] = True + + import json + + try: + with p.open("r", encoding="utf-8") as f: + for line in f: + line = line.strip() + if not line: + continue + try: + d = json.loads(line) + except Exception: + continue + if isinstance(d, dict) and isinstance(d.get("q"), list): + out["frames"] += 1 + meta = d.get("meta") + trig = False + if isinstance(meta, str) and ("trigger" in meta.lower()): + trig = True + elif isinstance(meta, dict) and bool(meta.get("trigger")): + trig = True + if trig: + out["triggers"] += 1 + out["ok"] = out["frames"] > 0 + out["trigger_ok"] = out["triggers"] > 0 + if out["frames"] <= 0: + out["error"] = "replay has no valid frames" + elif out["triggers"] <= 0: + out["warning"] = "replay has no trigger markers; timed fallback capture will be used" + return out + except Exception as e: + out["error"] = str(e) + record_error("capture_service", "replay_file_integrity", e, {"path": str(p)}) + return out + + +def replay_timing_profile(path: Path, end_margin_sec: float | None = None) -> dict: + """ + Returns replay timing information used to align countdown audio and fallback capture. + + If the replay contains explicit trigger markers, the first trigger offset is treated as the + desired shot time. Otherwise the shot is scheduled slightly before the replay ends so capture + happens before the arm starts returning home. + """ + p = Path(path).resolve() + margin = max(0.0, float(end_margin_sec if end_margin_sec is not None else config.REPLAY_CAPTURE_END_MARGIN_SEC)) + out = { + "ok": False, + "path": str(p), + "exists": False, + "frames": 0, + "timed_frames": 0, + "duration_sec": 0.0, + "trigger_offsets_sec": [], + "trigger_count": 0, + "capture_offset_sec": max(0.0, min(config.PHOTO_DELAY_SEC, config.PHOTO_TOTAL_SEC)), + "capture_source": "config_fallback", + "end_margin_sec": margin, + "error": "", + } + if not p.exists() or not p.is_file(): + out["error"] = "missing replay file" + return out + out["exists"] = True + + import json + + timed_offsets: list[float] = [] + trigger_offsets: list[float] = [] + first_t: float | None = None + + try: + with p.open("r", encoding="utf-8") as f: + for line in f: + line = line.strip() + if not line: + continue + try: + d = json.loads(line) + except Exception: + continue + if not (isinstance(d, dict) and isinstance(d.get("q"), list)): + continue + + out["frames"] += 1 + try: + t_val = float(d.get("t")) + except Exception: + continue + + if first_t is None: + first_t = t_val + rel_t = max(0.0, t_val - first_t) + timed_offsets.append(rel_t) + out["timed_frames"] += 1 + + meta = d.get("meta") + if isinstance(meta, str) and ("trigger" in meta.lower()): + trigger_offsets.append(rel_t) + elif isinstance(meta, dict) and bool(meta.get("trigger")): + trigger_offsets.append(rel_t) + + out["ok"] = out["frames"] > 0 + if not out["ok"]: + out["error"] = "replay has no valid frames" + return out + + if timed_offsets: + duration_sec = max(0.0, timed_offsets[-1]) + out["duration_sec"] = duration_sec + out["trigger_offsets_sec"] = [round(x, 3) for x in trigger_offsets] + out["trigger_count"] = len(trigger_offsets) + + if trigger_offsets: + out["capture_offset_sec"] = max(0.0, min(duration_sec, trigger_offsets[0])) + out["capture_source"] = "trigger" + elif duration_sec > 0.0: + out["capture_offset_sec"] = max(0.0, duration_sec - margin) + out["capture_source"] = "timed_end" + else: + out["capture_source"] = "config_fallback" + else: + out["error"] = "replay has no timestamped frames; config fallback timing will be used" + + return out + except Exception as e: + out["error"] = str(e) + record_error("capture_service", "replay_timing_profile", e, {"path": str(p)}) + return out + + +def ensure_replay_integrity(active_replay: Path, fallback_replay: Path) -> tuple[Path, dict]: + """ + Returns a valid replay path. If active invalid, tries fallback. + """ + active = Path(active_replay).resolve() + fallback = Path(fallback_replay).resolve() + active_report = replay_file_integrity(active) + if active_report.get("ok") and active_report.get("trigger_ok"): + return active, {"selected": str(active), "active": active_report, "fallback_used": False} + + fallback_report = replay_file_integrity(fallback) + if fallback_report.get("ok") and fallback_report.get("trigger_ok"): + return fallback, { + "selected": str(fallback), + "active": active_report, + "fallback": fallback_report, + "fallback_used": True, + "reason": "active replay missing trigger markers", + } + + # Degraded mode: no trigger-marked file found, keep active if it has frames. + if active_report.get("ok"): + return active, { + "selected": str(active), + "active": active_report, + "fallback": fallback_report, + "fallback_used": False, + "degraded_no_trigger": True, + } + + # If both invalid, keep active and report both failures. + return active, { + "selected": str(active), + "active": active_report, + "fallback": fallback_report, + "fallback_used": False, + } + + +def capture_with_replay_sync( + replay_runner, + replay_file: Path, + home_file: Path, + delay_sec: float, + prefix: str | None = None, + speed: float = 1.0, + finalize_timeout_sec: float = 4.0, + cancel_event: threading.Event | None = None, +) -> str: + """ + Unified capture pipeline: + replay + trigger callback capture + fallback timed capture + upload flag. + """ + delay_sec = max(0.0, float(delay_sec)) + done = threading.Event() + lock = threading.Lock() + result = {"value": None} + capture_started = {"value": False} + + def _is_cancelled() -> bool: + return bool(cancel_event is not None and cancel_event.is_set()) + + def _capture_once(reason: str): + if _is_cancelled(): + return + with lock: + if capture_started["value"]: + return + capture_started["value"] = True + try: + result["value"] = take_photo_sync(prefix=prefix) + except Exception as e: + record_error("capture_service", "capture_with_replay_capture_once", e, {"reason": reason}) + result["value"] = f"[ERR] capture failed ({reason}): {e}" + finally: + done.set() + + if replay_runner is not None and bool(getattr(replay_runner, "is_playing", False)): + return "[ERR] replay busy" + if _is_cancelled(): + return "[ERR] capture cancelled" + + try: + if replay_runner is not None: + def _trigger_cb(_frame): + threading.Thread(target=lambda: _capture_once("trigger"), daemon=True).start() + + threading.Thread( + target=lambda: replay_runner.run(replay_file, home_file, speed, trigger_callback=_trigger_cb), + daemon=True, + ).start() + except Exception as e: + record_error("capture_service", "capture_with_replay_start_replay", e) + return f"[ERR] replay start failed: {e}" + + deadline = time.time() + delay_sec + while (not done.is_set()) and (time.time() < deadline): + if _is_cancelled(): + return "[ERR] capture cancelled" + time.sleep(0.02) + + if (not done.is_set()) and (not _is_cancelled()): + _capture_once("fallback") + + finalize_deadline = time.time() + max(0.1, finalize_timeout_sec) + while not done.is_set(): + if _is_cancelled(): + return "[ERR] capture cancelled" + if time.time() >= finalize_deadline: + break + time.sleep(0.02) + if not done.is_set(): + record_error("capture_service", "capture_with_replay_timeout", context={"delay_sec": delay_sec}) + return "[ERR] capture pipeline timeout" + + return str(result["value"] or "[ERR] capture pipeline no result") diff --git a/Server/direct_camera_client.py b/Server/direct_camera_client.py new file mode 100644 index 0000000..49f8ada --- /dev/null +++ b/Server/direct_camera_client.py @@ -0,0 +1,103 @@ +from __future__ import annotations + +import json +import os +import urllib.error +import urllib.parse +import urllib.request +from typing import Any, Optional + +import cv2 +import numpy as np + + +def is_enabled() -> bool: + return os.environ.get("DIRECT_CAMERA_ENABLED", "1").strip().lower() not in ("0", "false", "no", "off") + + +def base_url() -> str: + return ( + os.environ.get("DIRECT_CAMERA_SERVER_URL", "").strip() + or f"http://127.0.0.1:{int(os.environ.get('DIRECT_CAMERA_PORT', '8091'))}" + ).rstrip("/") + + +def _open(path: str, timeout: float = 3.0): + url = base_url() + path + req = urllib.request.Request(url, method="GET") + return urllib.request.urlopen(req, timeout=timeout) + + +def get_json(path: str, timeout: float = 3.0) -> dict[str, Any]: + with _open(path, timeout=timeout) as resp: + raw = resp.read() + data = json.loads(raw.decode("utf-8")) + if isinstance(data, dict): + return data + raise RuntimeError("direct camera server returned non-object JSON") + + +def get_bytes(path: str, timeout: float = 3.0) -> bytes: + with _open(path, timeout=timeout) as resp: + return resp.read() + + +def health(timeout: float = 2.0) -> dict[str, Any]: + return get_json("/api/health", timeout=timeout) + + +def cameras(timeout: float = 2.0) -> dict[str, Any]: + return get_json("/api/cameras", timeout=timeout) + + +def capture(prefix: str = "photo", ext: str = "jpg", timeout: float = 10.0) -> str: + q = urllib.parse.urlencode({"prefix": prefix, "ext": ext}) + data = get_json(f"/api/capture?{q}", timeout=timeout) + if not data.get("ok"): + raise RuntimeError(str(data.get("error") or "capture failed")) + path = str(data.get("path") or "").strip() + if not path: + raise RuntimeError("capture response missing saved path") + return path + + +def set_source(source: str, timeout: float = 8.0) -> dict[str, Any]: + q = urllib.parse.urlencode({"source": source}) + data = get_json(f"/api/set_camera?{q}", timeout=timeout) + if not data.get("ok"): + raise RuntimeError(str(data.get("error") or "camera switch failed")) + return data + + +def set_preferred_camera(serial: str, timeout: float = 8.0) -> dict[str, Any]: + q = urllib.parse.urlencode({"serial": serial}) + data = get_json(f"/api/set_preferred_camera?{q}", timeout=timeout) + if not data.get("ok"): + raise RuntimeError(str(data.get("error") or "preferred camera update failed")) + return data + + +def set_resolution(width: int, height: int, fps: int, timeout: float = 8.0) -> dict[str, Any]: + q = urllib.parse.urlencode({"width": int(width), "height": int(height), "fps": int(fps)}) + data = get_json(f"/api/set_resolution?{q}", timeout=timeout) + if not data.get("ok"): + raise RuntimeError(str(data.get("error") or "resolution change failed")) + return data + + +def frame_jpeg(timeout: float = 2.0) -> bytes: + return get_bytes("/api/frame.jpg", timeout=timeout) + + +def frame_bgr(timeout: float = 2.0) -> Optional[np.ndarray]: + try: + raw = frame_jpeg(timeout=timeout) + except urllib.error.URLError: + return None + except Exception: + return None + arr = np.frombuffer(raw, dtype=np.uint8) + if arr.size <= 0: + return None + frame = cv2.imdecode(arr, cv2.IMREAD_COLOR) + return frame diff --git a/Server/photo_server.py b/Server/photo_server.py new file mode 100644 index 0000000..ab437fe --- /dev/null +++ b/Server/photo_server.py @@ -0,0 +1,2195 @@ +#!/usr/bin/env python3 +""" +photo_server.py +--------------- +HTTP photo gallery server for the configured AI_Photographer photos directory. + +โœ… Features: +- Phone/Laptop gallery UI: GET / +- Serves photos directly (open/download): GET / +- Delete photo: GET /api/delete?name= +- Capture via unified replay pipeline: GET /api/capture +- Camera status: GET /api/status +- Camera test (RealSense enumerate via camera env python): GET /api/test +- Run RealSense USB fix script: GET /api/fix +- CSS/HTML split: + Web/gallery.html + Web/style.css + Served as: + / -> gallery.html template (photo list injected) + /static/style.css -> style.css file + +โš ๏ธ Security note: +- This is an open LAN server (anyone on same WiFi can view/download/delete). + Use only on trusted networks. + +Works well with your structure (no new folders). +""" + +from __future__ import annotations + +import json +import os +import socket +import sys +import threading +import tempfile +import time +import urllib.parse +import subprocess +import cgi +from pathlib import Path +from http.server import SimpleHTTPRequestHandler, ThreadingHTTPServer +from typing import Optional, Callable, Dict, Any, List +from Core import settings as config +from Core import audio_prompts +from Core import audio_prompt_recorder +from Core.error_events import get_error_counters, record_error +from Core import people_registry +from Server.capture_service import replay_file_integrity, take_photo_sync +from Server import direct_camera_client + +try: + from Core.Logger import Logs +except Exception: + Logs = None # type: ignore + + +# ============================================================ +# Defaults / Paths +# ============================================================ +SERVER_DIR = Path(__file__).resolve().parent +PROJECT_ROOT = SERVER_DIR.parent +SCRIPTS_DIR = (PROJECT_ROOT / "Scripts").resolve() +APP_DATA_DIR = Path(getattr(config, "APP_DATA_DIR", PROJECT_ROOT / "Data")).resolve() +DATA_SCRIPTS_DIR = Path(getattr(config, "APP_SCRIPTS_DIR", APP_DATA_DIR / "Scripts")).resolve() +AUTONOMOUS_STATE_FILE = Path(getattr(config, "AUTONOMOUS_STATE_FILE", APP_DATA_DIR / "Runtime" / "autonomous_state.json")).resolve() +RUNTIME_HEALTH_FILE = Path(getattr(config, "RUNTIME_HEALTH_FILE", APP_DATA_DIR / "Runtime" / "runtime_health.json")).resolve() +DEFAULT_PHOTOS_DIR = Path(getattr(config, "PHOTOS_DIR", PROJECT_ROOT / "photos" / "Captures")).resolve() +WEB_DIR = (PROJECT_ROOT / "Web").resolve() + +GALLERY_HTML = WEB_DIR / "gallery.html" +STYLE_CSS = WEB_DIR / "style.css" +GALLERY_JS = WEB_DIR / "gallery.js" + +FIX_SCRIPT_ENV = os.environ.get("FIX_SCRIPT_PATH", "").strip() +_DEFAULT_RUNTIME_HOME = Path(os.environ.get("HOME", "~")).expanduser() +CAMERA_ENV_PY = os.environ.get( + "TELEIMAGER_PY", + str((_DEFAULT_RUNTIME_HOME / "miniconda3" / "envs" / "teleimager" / "bin" / "python").resolve()), +) + +# Preview fallback controls +PREVIEW_USE_OPENCV_FALLBACK = os.environ.get("PREVIEW_USE_OPENCV_FALLBACK", "1").strip().lower() not in ( + "0", "false", "no", "off" +) +PREVIEW_RETRY_SEC = float(os.environ.get("PREVIEW_RETRY_SEC", "2.0")) + +# Shared preview camera state to avoid reopening camera on every frame +_PREVIEW_CAM_LOCK = threading.Lock() +_PREVIEW_CAM: Optional[Any] = None +_PREVIEW_LAST_OPEN_TRY = 0.0 +_CV2_MODULE = None +_CAMERA_CAPTURE_CLS = None + +_RECORDER_LOCK = threading.Lock() +_RECORDER_STATE: Dict[str, Any] = { + "running": False, + "name": "", + "seconds": 0.0, + "output": "", + "returncode": None, + "ok": False, + "error": "", + "started_at": 0.0, + "finished_at": 0.0, + "stdout_tail": [], +} + +_REPLAY_TEST_LOCK = threading.Lock() +_REPLAY_TEST_STATE: Dict[str, Any] = { + "running": False, + "name": "", + "ok": False, + "error": "", + "result": "", + "started_at": 0.0, + "finished_at": 0.0, +} + +_AUDIO_PROMPT_RECORD_LOCK = threading.Lock() +_AUDIO_PROMPT_RECORD_STATE: Dict[str, Any] = { + "running": False, + "key": "", + "filename": "", + "text": "", + "ok": False, + "error": "", + "started_at": 0.0, + "finished_at": 0.0, + "result": {}, +} + + +# ============================================================ +# Logging helpers +# ============================================================ +def _make_logger(log_name: str = "photo_server"): + if Logs is None: + return None + lg = Logs() + try: + lg.LogEngine("G1_Logs", log_name) + except Exception: + pass + return lg + + +def _log(lg, msg: str, level: str = "info"): + # level: info / warning / error + if lg is not None: + try: + lg.print_and_log(msg, message_type=level) + return + except Exception: + pass + print(msg) + + +# ============================================================ +# Utilities +# ============================================================ +def _get_local_ip() -> str: + """ + Best-effort IP that phones can reach (same WiFi). + """ + try: + s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM) + s.connect(("8.8.8.8", 80)) + ip = s.getsockname()[0] + s.close() + return ip + except Exception: + return "127.0.0.1" + + +def _safe_name(name: str) -> str: + """ + Prevent path traversal: keep only filename (no dirs). + """ + name = name.strip().replace("\\", "/") + name = name.split("/")[-1] + return name + + +def _fix_script_candidates() -> List[Path]: + cands: List[Path] = [] + if FIX_SCRIPT_ENV: + p = Path(FIX_SCRIPT_ENV).expanduser() + if not p.is_absolute(): + p = (PROJECT_ROOT / p).resolve() + cands.append(p) + cands.append((SCRIPTS_DIR / "fix_realsense_usb.sh").resolve()) + cands.append((PROJECT_ROOT / "fix_realsense_usb.sh").resolve()) + return cands + + +def _resolve_fix_script() -> Optional[Path]: + for p in _fix_script_candidates(): + if p.exists() and p.is_file(): + return p + return None + + +def _get_cv2(): + global _CV2_MODULE + if _CV2_MODULE is None: + import cv2 + + _CV2_MODULE = cv2 + return _CV2_MODULE + + +def _get_camera_capture_cls(): + global _CAMERA_CAPTURE_CLS + if _CAMERA_CAPTURE_CLS is None: + from Modes.AI.camera_module import CameraCapture + + _CAMERA_CAPTURE_CLS = CameraCapture + return _CAMERA_CAPTURE_CLS + + +def _is_photo_file(p: Path) -> bool: + if not p.is_file(): + return False + ext = p.suffix.lower() + return ext in (".jpg", ".jpeg", ".png", ".webp") + + +def _list_photos(folder: Path) -> List[Dict[str, Any]]: + items: List[Dict[str, Any]] = [] + folder.mkdir(parents=True, exist_ok=True) + + for p in sorted(folder.iterdir(), key=lambda x: x.stat().st_mtime, reverse=True): + if not _is_photo_file(p): + continue + st = p.stat() + items.append( + { + "name": p.name, + "size": st.st_size, + "mtime": st.st_mtime, + } + ) + return items + + +def _group_sessions(items: List[Dict[str, Any]], gap_sec: int = 120) -> List[Dict[str, Any]]: + """Group photos into sessions when gaps between photos exceed gap_sec.""" + sessions = [] + cur = None + for it in sorted(items, key=lambda x: x["mtime"]): + t = it["mtime"] + if cur is None: + cur = {"id": len(sessions) + 1, "start": t, "end": t, "photos": [it["name"]]} + continue + if t - cur["end"] > gap_sec: + sessions.append(cur) + cur = {"id": len(sessions) + 1, "start": t, "end": t, "photos": [it["name"]]} + else: + cur["photos"].append(it["name"]) + cur["end"] = t + + if cur is not None: + sessions.append(cur) + return sessions + + +def _read_text_file(path: Path) -> Optional[str]: + try: + return path.read_text(encoding="utf-8") + except Exception: + return None + + +def _read_bytes_file(path: Path) -> Optional[bytes]: + try: + return path.read_bytes() + except Exception: + return None + + +def _read_mode() -> str: + try: + m = str(config.read_runtime_mode()).strip().lower() + except Exception: + m = "manual" + if m == "command": + return "ai" + if m not in ("manual", "ai"): + return "manual" + return m + + +def _read_detector_backend() -> str: + try: + b = str(config.read_vision_detector_backend()).strip().lower() + except Exception: + b = "normal" + if b not in ("yolo", "normal"): + return "normal" + return b + + +def _strict_yolo_required() -> bool: + try: + return bool(config.read_vision_yolo_strict_required()) + except Exception: + return bool(getattr(config, "VISION_YOLO_STRICT_REQUIRED", False)) + + +def _read_ai_readiness() -> Dict[str, Any]: + from Modes.AI.vision_detector import probe_ai_readiness + + backend = _read_detector_backend() + strict_required = _strict_yolo_required() + readiness = probe_ai_readiness(backend=backend, strict_required=strict_required) + state = _read_autonomous_state() + + ai_blocked = bool(state.get("ai_blocked", False)) + ai_block_reason = str(state.get("ai_block_reason", "") or "").strip() + if ai_blocked and ai_block_reason: + readiness["ok"] = False + readiness["block_reason"] = ai_block_reason + + return { + "ok": bool(readiness.get("ok", False)), + "strict_required": bool(strict_required), + "backend": backend, + "yolo_runtime": str(readiness.get("yolo_runtime", "") or ""), + "yolo_loaded": bool(readiness.get("yolo_loaded", False)), + "person_model_ok": bool(readiness.get("person_model_ok", False)), + "face_model_ok": bool(readiness.get("face_model_ok", False)), + "block_reason": str(readiness.get("block_reason", "") or ""), + "person_model_path": str(readiness.get("person_model_path", "") or ""), + "face_model_path": str(readiness.get("face_model_path", "") or ""), + } + + +def _read_runtime_health() -> Dict[str, Any]: + default = { + "ws_connected": False, + "ws_state": "detached", + "ws_restarts": 0, + "ws_last_error": "", + "mic_enabled": True, + "mic_state": "idle", + "mic_restarts": 0, + "mic_last_error": "", + "speaker_state": "idle", + "speaker_restarts": 0, + "speaker_last_error": "", + "audio_gate_open": False, + "time": 0.0, + } + try: + if not RUNTIME_HEALTH_FILE.exists(): + return default + raw = json.loads(RUNTIME_HEALTH_FILE.read_text(encoding="utf-8")) + if not isinstance(raw, dict): + return default + out = dict(default) + out.update(raw) + return out + except Exception: + return default + + +def _read_ai_options() -> Dict[str, Any]: + try: + hard = bool(config.read_vision_hard_target_lock_enabled()) + except Exception: + hard = True + try: + retake = bool(config.read_vision_retake_prompt_enabled()) + except Exception: + retake = True + try: + greeting_replay_enabled = bool(config.read_vision_autonomous_greeting_replay_enabled()) + except Exception: + greeting_replay_enabled = True + try: + greeting_replay_file = str(config.read_vision_autonomous_greeting_replay_file() or "").strip() + except Exception: + greeting_replay_file = "right_hand_up.jsonl" + try: + capture_replay_enabled = bool(config.read_vision_autonomous_capture_replay_enabled()) + except Exception: + capture_replay_enabled = True + try: + face_recognition_enabled = bool(config.read_vision_face_recognition_enabled()) + except Exception: + face_recognition_enabled = True + try: + face_recognition_threshold = float(config.read_vision_face_recognition_threshold()) + except Exception: + face_recognition_threshold = 0.88 + return { + "hard_target_lock_enabled": hard, + "retake_prompt_enabled": retake, + "autonomous_greeting_replay_enabled": greeting_replay_enabled, + "autonomous_greeting_replay_file": greeting_replay_file, + "autonomous_capture_replay_enabled": capture_replay_enabled, + "face_recognition_enabled": face_recognition_enabled, + "face_recognition_threshold": face_recognition_threshold, + "active_replay": _read_active_replay_name(), + } + + +def _read_mic_options() -> Dict[str, Any]: + try: + enabled = bool(config.read_gemini_mic_enabled()) + except Exception: + enabled = True + return {"mic_enabled": enabled} + + +def _safe_relative_name(name: str) -> str: + raw = str(name or "").strip().replace("\\", "/").lstrip("/") + if not raw: + return "" + p = Path(raw) + if p.is_absolute(): + return "" + parts = [part for part in p.parts if part not in ("", ".")] + if any(part == ".." for part in parts): + return "" + return Path(*parts).as_posix() if parts else "" + + +def _normalize_replay_name(name: str, default_parent: str | None = None) -> str: + safe = _safe_relative_name(name) + if not safe: + raise ValueError("invalid replay path") + + p = Path(safe) + if len(p.parts) == 1 and default_parent: + p = Path(default_parent) / p.name + if p.suffix.lower() != ".jsonl": + p = p.with_suffix(".jsonl") + if p.name == config.HOME_FILE.name: + raise ValueError("reserved replay name") + return p.as_posix() + + +def _resolve_replay_path(name: str) -> Path: + candidate = config.resolve_replay_path(_normalize_replay_name(name)) + try: + candidate.relative_to(config.DATA_DIR) + except Exception as e: + raise ValueError("invalid replay path") from e + return candidate + + +def _is_replay_file(path: Path) -> bool: + return path.is_file() and path.suffix.lower() == ".jsonl" and path.name != config.HOME_FILE.name + + +def _read_active_replay_name() -> str: + try: + return config.read_selected_replay_name() + except Exception: + return str(config.REPLAY_FILE.name) + + +def _list_replays() -> List[Dict[str, Any]]: + items: List[Dict[str, Any]] = [] + root = config.DATA_DIR.resolve() + root.mkdir(parents=True, exist_ok=True) + active_name = _read_active_replay_name() + greeting_name = str(config.read_vision_autonomous_greeting_replay_file() or "").strip().replace("\\", "/") + for path in sorted(root.rglob("*.jsonl")): + if not _is_replay_file(path): + continue + try: + rel = str(path.resolve().relative_to(root)).replace("\\", "/") + except Exception: + rel = path.name + st = path.stat() + integrity = replay_file_integrity(path) + items.append( + { + "name": rel, + "label": path.name, + "size": st.st_size, + "mtime": st.st_mtime, + "active": rel == active_name, + "greeting": rel == greeting_name or path.name == greeting_name, + "trigger_ok": bool(integrity.get("trigger_ok", False)), + "ok": bool(integrity.get("ok", False)), + } + ) + return items + + +def _replay_recorder_candidates() -> List[Path]: + candidates = [] + env_path = os.environ.get("REPLAY_RECORDER_SCRIPT", "").strip() + if env_path: + candidates.append(Path(env_path).expanduser()) + cfg_raw = str(getattr(config, "REPLAY_RECORDER_SCRIPT", "") or "").strip() + if cfg_raw: + cfg_path = Path(cfg_raw).expanduser() + candidates.append(cfg_path) + candidates.append((PROJECT_ROOT.parent / "G1_Lootah" / "Manual_Recorder" / "g1_teach_v4_stable.py").resolve()) + candidates.append((PROJECT_ROOT.parents[1] / "G1_Lootah" / "Manual_Recorder" / "g1_teach_v4_stable.py").resolve()) + candidates.append((Path.home() / "G1_Lootah" / "Manual_Recorder" / "g1_teach_v4_stable.py").resolve()) + return [p if p.is_absolute() else p.resolve() for p in candidates] + + +def _resolve_replay_recorder_script() -> Optional[Path]: + for candidate in _replay_recorder_candidates(): + try: + if candidate.exists() and candidate.is_file(): + return candidate + except Exception: + continue + return None + + +def _read_recorder_state() -> Dict[str, Any]: + with _RECORDER_LOCK: + return dict(_RECORDER_STATE) + + +def _set_recorder_state(**kwargs): + with _RECORDER_LOCK: + _RECORDER_STATE.update(kwargs) + + +def _read_replay_test_state() -> Dict[str, Any]: + with _REPLAY_TEST_LOCK: + return dict(_REPLAY_TEST_STATE) + + +def _set_replay_test_state(**kwargs): + with _REPLAY_TEST_LOCK: + _REPLAY_TEST_STATE.update(kwargs) + + +def _read_audio_prompt_record_state() -> Dict[str, Any]: + with _AUDIO_PROMPT_RECORD_LOCK: + return dict(_AUDIO_PROMPT_RECORD_STATE) + + +def _set_audio_prompt_record_state(**kwargs): + with _AUDIO_PROMPT_RECORD_LOCK: + _AUDIO_PROMPT_RECORD_STATE.update(kwargs) + + +def _run_audio_prompt_record(key: str, text: str, filename: str): + try: + result = audio_prompt_recorder.record_prompt_from_text(key, text, filename=filename) + _set_audio_prompt_record_state( + running=False, + ok=True, + error="", + finished_at=time.time(), + result=result, + ) + except Exception as e: + _set_audio_prompt_record_state( + running=False, + ok=False, + error=str(e), + finished_at=time.time(), + result={}, + ) + + +def _run_replay_recorder(name: str, seconds: float): + script = _resolve_replay_recorder_script() + if script is None: + _set_recorder_state( + running=False, + ok=False, + error="recorder script not found", + finished_at=time.time(), + ) + return + try: + from Modes.Manual.controller import auto_pick_iface + + iface = auto_pick_iface() + except Exception as e: + _set_recorder_state( + running=False, + ok=False, + error=f"failed to resolve DDS interface: {e}", + finished_at=time.time(), + ) + return + + output_path = _resolve_replay_path(name) + output_path.parent.mkdir(parents=True, exist_ok=True) + cmd = [ + sys.executable, + str(script), + iface, + "--output", + str(output_path), + "--seconds", + str(seconds), + "--home", + str(config.HOME_FILE), + ] + try: + proc = subprocess.run( + cmd, + input="y\nn\n", + capture_output=True, + text=True, + timeout=max(30.0, seconds + 45.0), + cwd=str(PROJECT_ROOT), + ) + combined = ((proc.stdout or "") + "\n" + (proc.stderr or "")).strip() + tail = [line for line in combined.splitlines() if line.strip()][-25:] + saved_path = "" + for line in tail: + marker = "๐Ÿ’พ Saved " + if marker in line and " to " in line: + saved_path = line.split(" to ", 1)[1].strip() + ok = proc.returncode == 0 and bool(saved_path) + _set_recorder_state( + running=False, + ok=ok, + error="" if ok else (tail[-1] if tail else f"recorder failed rc={proc.returncode}"), + returncode=proc.returncode, + finished_at=time.time(), + output=saved_path, + stdout_tail=tail, + ) + except Exception as e: + _set_recorder_state( + running=False, + ok=False, + error=str(e), + finished_at=time.time(), + stdout_tail=[], + ) + + +def _run_replay_test(name: str, replay_test_func: Callable[[str], str]): + try: + result = replay_test_func(name) + ok = not str(result or "").startswith("[ERR]") + _set_replay_test_state( + running=False, + ok=ok, + error="" if ok else str(result or "").replace("[ERR] ", "").replace("[ERR]", "").strip(), + result=str(result or ""), + finished_at=time.time(), + ) + except Exception as e: + _set_replay_test_state( + running=False, + ok=False, + error=str(e), + result="", + finished_at=time.time(), + ) + + +def _update_replay_references_after_rename(old_rel: str, new_rel: str, new_path: Path): + if _read_active_replay_name() == old_rel: + config.write_selected_replay_name(new_rel) + config.REPLAY_FILE = new_path + greeting_name = str(config.read_vision_autonomous_greeting_replay_file() or "").strip().replace("\\", "/") + if greeting_name == old_rel: + config.write_vision_autonomous_greeting_replay_file(new_rel) + + +def _is_greeting_replay(rel_name: str) -> bool: + greeting_name = str(config.read_vision_autonomous_greeting_replay_file() or "").strip().replace("\\", "/") + return rel_name == greeting_name + + +def _mode_policy(mode: str) -> Dict[str, Any]: + mode = mode if mode in ("manual", "ai") else "manual" + if mode == "manual": + return { + "voice_request_photo": False, + "description": "Manual mode: Gemini mic can stay on, but mapped photo commands and AI detection are disabled.", + } + if mode == "ai": + return { + "voice_request_photo": True, + "description": "AI mode: mapped voice can request photo.", + } + return { + "voice_request_photo": False, + "description": "Unknown mode.", + } + + +def _read_autonomous_state() -> Dict[str, Any]: + default: Dict[str, Any] = { + "state": "IDLE", + "session_id": 0, + "interaction_active": False, + "intent_detected": False, + "detector_backend": "normal", + "ai_blocked": False, + "ai_block_reason": "", + "person_count": 0, + "face_count": 0, + "group_count": 0, + "group_size": 0, + "group_detected": False, + "max_area": 0.0, + "audio_gate_open": False, + "subject_id": None, + "subject_visible": False, + "target_lock_active": False, + "target_lock_type": "", + "target_lock_id": None, + "target_switch_blocked_count": 0, + "depth_m": None, + "approach_speed_mps": 0.0, + "camera_ok": False, + "depth_ok": False, + "camera_restarts": 0, + "depth_restarts": 0, + "ws_connected": False, + "mic_state": "", + "speaker_state": "", + "cooldown_remaining": 0.0, + "confirm_timeout_remaining": 0.0, + "framing_timeout_remaining": 0.0, + "countdown_remaining": 0.0, + "retake_prompt_enabled": False, + "retake_recommended": False, + "retake_reason": "", + "retake_count": 0, + "retake_limit": 0, + "recognized_person_id": "", + "recognized_person_known": False, + "recognized_person_new": False, + "recognized_person_label": "", + "recognized_person_match_score": 0.0, + "recognized_person_created_date": "", + "time": 0.0, + } + try: + if not AUTONOMOUS_STATE_FILE.exists(): + return default + data = json.loads(AUTONOMOUS_STATE_FILE.read_text(encoding="utf-8")) + if not isinstance(data, dict): + return default + merged = dict(default) + merged.update(data) + return merged + except Exception: + return default + + +# ============================================================ +# Capture/Test/Fix implementations +# ============================================================ +def _capture_via_service() -> str: + """ + Capture a photo using the shared capture service. + """ + try: + return take_photo_sync(prefix="photo") + except Exception as e: + return f"[ERR] capture exception: {e}" + + +def _preview_camera_source() -> Optional[str]: + src = os.environ.get("CAMERA_DEVICE", "").strip() + if src: + return src + idx = os.environ.get("CAMERA_INDEX", "").strip() + return idx or None + + +def _get_preview_frame(zmq_host: str = "127.0.0.1", zmq_port: int = 55555, video_source: Optional[str] = None): + """Best-effort single frame for MJPEG preview. + Tries direct camera server, then CameraCapture fallback. + Returns BGR frame or None. + """ + global _PREVIEW_CAM, _PREVIEW_LAST_OPEN_TRY + try: + if direct_camera_client.is_enabled(): + frame = direct_camera_client.frame_bgr(timeout=2.0) + if frame is not None: + return frame + + if not PREVIEW_USE_OPENCV_FALLBACK: + return None + + now = time.time() + with _PREVIEW_CAM_LOCK: + if _PREVIEW_CAM is None and (now - _PREVIEW_LAST_OPEN_TRY) >= PREVIEW_RETRY_SEC: + _PREVIEW_LAST_OPEN_TRY = now + src = video_source if video_source is not None else _preview_camera_source() + cam = _get_camera_capture_cls()(src) + if cam.initialize(): + _PREVIEW_CAM = cam + else: + try: + cam.release() + except Exception: + pass + _PREVIEW_CAM = None + + if _PREVIEW_CAM is None: + return None + + frame = _PREVIEW_CAM.capture_frame() + if frame is None: + # If device dropped, close it and retry after cooldown. + cap = getattr(_PREVIEW_CAM, "cap", None) + if cap is None or not cap.isOpened(): + try: + _PREVIEW_CAM.release() + except Exception: + pass + _PREVIEW_CAM = None + return None + + return frame + except Exception: + return None + + +def _realsense_test() -> Dict[str, Any]: + """ + Quick test using the camera env python: + - import pyrealsense2 + - count devices + """ + try: + code = ( + "import pyrealsense2 as rs\n" + "ctx = rs.context()\n" + "devs = list(ctx.query_devices())\n" + "print(len(devs))\n" + "print([d.get_info(rs.camera_info.serial_number) for d in devs])\n" + ) + p = subprocess.run( + [CAMERA_ENV_PY, "-c", code], + capture_output=True, + text=True, + timeout=10, + ) + out = (p.stdout or "").strip().splitlines() + err = (p.stderr or "").strip() + + if p.returncode != 0: + return {"ok": False, "rc": p.returncode, "error": err or "realsense test failed", "stdout": out[-20:]} + + count = int(out[0]) if out else 0 + serials = [] + if len(out) >= 2: + # second line prints python list + serials = out[1] + return {"ok": True, "devices": count, "serials": serials, "rc": 0} + + except Exception as e: + return {"ok": False, "error": str(e)} + + +def _run_fix_script() -> Dict[str, Any]: + """ + Runs fix_realsense_usb.sh in NON-INTERACTIVE mode. + If sudo password is required, it fails gracefully (no terminal prompt). + """ + fix_script = _resolve_fix_script() + if not fix_script: + checked = [str(p) for p in _fix_script_candidates()] + return {"ok": False, "error": "fix script not found", "checked": checked} + + try: + # IMPORTANT: -n = non-interactive (won't prompt for password) + p = subprocess.run( + ["sudo", "-n", "bash", str(fix_script)], + capture_output=True, + text=True, + timeout=40, + ) + + out = (p.stdout or "").strip().splitlines()[-80:] + err = (p.stderr or "").strip().splitlines()[-80:] + + if p.returncode == 0: + return {"ok": True, "rc": 0, "stdout": out, "stderr": err} + + # Most common case: sudo needs password + joined_err = "\n".join(err).lower() + if "a password is required" in joined_err or "sudo:" in joined_err: + return { + "ok": False, + "rc": p.returncode, + "error": f"sudo password required. Run manually in terminal: sudo bash {fix_script}", + "stdout": out, + "stderr": err, + } + + return {"ok": False, "rc": p.returncode, "stdout": out, "stderr": err} + + except Exception as e: + return {"ok": False, "error": str(e)} + + + +# ============================================================ +# HTML template fallback (if Scripts/gallery.html missing) +# ============================================================ +# All HTML/CSS/JS files live in WEB_DIR. The server reads them at runtime. + + +# ============================================================ +# Main server factory +# ============================================================ +def start_photo_server( + folder: Path = DEFAULT_PHOTOS_DIR, + port: int = 8080, + bind: str = "0.0.0.0", + capture_func: Optional[Callable[[], str]] = None, + replay_test_func: Optional[Callable[[str], str]] = None, + logger=None, +) -> str: + """ + Starts the gallery server in a daemon thread. + Returns the URL (best-effort reachable IP). + + If port is already in use, it logs and returns the URL anyway (assumes old server is running). + """ + lg = logger or _make_logger("photo_server.log") + folder = folder.resolve() + folder.mkdir(parents=True, exist_ok=True) + + ip = _get_local_ip() + url = f"http://{ip}:{port}/" + + if capture_func is None: + capture_func = _capture_via_service + + class Handler(SimpleHTTPRequestHandler): + QUIET_PATHS = { + "/api/autonomous_state", + "/api/runtime_health", + "/api/photos", + "/api/people", + "/api/audio_prompts", + "/api/audio_prompt_record_status", + "/api/set_audio_prompt_mode", + "/api/set_audio_prompt_fallback", + "/api/replays", + "/api/get_replay", + "/api/replay_record_status", + "/api/replay_test_status", + "/api/mode", + "/api/ai_readiness", + "/api/ai_options", + "/api/detector_backend", + "/api/camera_health", + "/api/camera_sources", + "/api/person_image", + "/preview.mjpg", + } + + # Serve files from PHOTOS folder by default + def __init__(self, *args, **kwargs): + super().__init__(*args, directory=str(folder), **kwargs) + + def log_message(self, fmt, *args): + path = urllib.parse.urlparse(getattr(self, "path", "")).path + if path.startswith("/static/"): + return + if path in self.QUIET_PATHS: + return + if path.endswith(".jpg") or path.endswith(".jpeg") or path.endswith(".png") or path.endswith(".zip"): + return + status = str(args[1]) if len(args) > 1 else "?" + print(f"๐ŸŒ HTTP {getattr(self, 'command', '?')} {path} -> {status}") + + def _send_json(self, obj: Dict[str, Any], code: int = 200): + data = json.dumps(obj, ensure_ascii=False, indent=2).encode("utf-8") + self.send_response(code) + self.send_header("Content-Type", "application/json; charset=utf-8") + self.send_header("Content-Length", str(len(data))) + self.end_headers() + self.wfile.write(data) + + def _send_text(self, text: str, code: int = 200, ctype: str = "text/plain; charset=utf-8"): + data = text.encode("utf-8") + self.send_response(code) + self.send_header("Content-Type", ctype) + self.send_header("Content-Length", str(len(data))) + self.end_headers() + self.wfile.write(data) + + def do_GET(self): + parsed = urllib.parse.urlparse(self.path) + path = parsed.path + q = urllib.parse.parse_qs(parsed.query) + + # Ignore favicon noise + if path == "/favicon.ico": + self.send_response(204) + self.end_headers() + return + + # Serve static CSS/JS from Web folder + if path == "/static/style.css": + css = _read_bytes_file(STYLE_CSS) + if css is None: + self.send_response(404) + self.end_headers() + return + self.send_response(200) + self.send_header("Content-Type", "text/css; charset=utf-8") + self.send_header("Content-Length", str(len(css))) + self.end_headers() + self.wfile.write(css) + return + + if path == "/static/gallery.js": + js = _read_text_file(GALLERY_JS) + if js is None: + self.send_response(404) + self.end_headers() + return + data = js.encode("utf-8") + self.send_response(200) + self.send_header("Content-Type", "application/javascript; charset=utf-8") + self.send_header("Content-Length", str(len(data))) + self.end_headers() + self.wfile.write(data) + return + + # API endpoints + if path == "/api/status": + items = _list_photos(folder) + res = { + "ok": True, + "photos_dir": str(folder), + "count": len(items), + "latest": items[0]["name"] if items else None, + "url": url, + "time": time.strftime("%Y-%m-%d %H:%M:%S"), + } + self._send_json(res, 200) + return + + if path == "/api/errors": + self._send_json({"ok": True, "counters": get_error_counters()}) + return + + if path == "/api/mode": + # return current mode + m = _read_mode() + self._send_json({"ok": True, "mode": m, "policy": _mode_policy(m)}) + return + + if path == "/api/detector_backend": + b = _read_detector_backend() + strict_required = _strict_yolo_required() + mode = _read_mode() + locked = bool(strict_required and mode == "ai") + self._send_json( + { + "ok": True, + "backend": b, + "yolo_runtime": str(config.read_vision_yolo_runtime()), + "options": ["normal", "yolo"], + "strict_required": strict_required, + "locked": locked, + } + ) + return + + if path == "/api/ai_readiness": + data = _read_ai_readiness() + self._send_json(data, 200 if data.get("ok") else 503) + return + + if path == "/api/runtime_health": + self._send_json({"ok": True, "health": _read_runtime_health()}) + return + + if path == "/api/camera_health": + try: + self._send_json(direct_camera_client.health(timeout=3.0)) + except Exception as e: + self._send_json({"ok": False, "error": str(e), "camera": {}}, 503) + return + + if path == "/api/camera_sources": + try: + self._send_json(direct_camera_client.cameras(timeout=3.0)) + except Exception as e: + self._send_json({"ok": False, "error": str(e), "options": []}, 503) + return + + if path == "/api/set_camera_source": + source = q.get("source", [""])[0].strip() + if not source: + self._send_json({"ok": False, "error": "missing source"}, 400) + return + try: + self._send_json(direct_camera_client.set_source(source, timeout=8.0)) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + if path == "/api/set_camera_resolution": + try: + width = int((q.get("width") or [""])[0]) + height = int((q.get("height") or [""])[0]) + fps = int((q.get("fps") or [""])[0]) + except Exception: + self._send_json({"ok": False, "error": "width, height, and fps are required integers"}, 400) + return + try: + self._send_json(direct_camera_client.set_resolution(width, height, fps, timeout=8.0)) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + if path == "/api/set_preferred_camera": + serial = q.get("serial", [""])[0].strip() + try: + saved = config.write_camera_preferred_realsense_serial(serial) + self._send_json(direct_camera_client.set_preferred_camera(saved, timeout=8.0)) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + if path == "/api/mic": + self._send_json({"ok": True, "options": _read_mic_options()}) + return + + if path == "/api/ai_options": + self._send_json({"ok": True, "options": _read_ai_options()}) + return + + if path == "/api/autonomous_state": + self._send_json({"ok": True, "state": _read_autonomous_state()}) + return + + if path == "/api/people": + try: + self._send_json({"ok": True, "people": people_registry.list_people()}) + except Exception as e: + self._send_json({"ok": False, "error": str(e), "people": []}, 500) + return + + if path == "/api/audio_prompts": + try: + self._send_json( + { + "ok": True, + "dir": str(config.AUDIO_PROMPTS_DIR), + "mode": str(config.read_audio_prompt_mode()), + "fallback_to_gemini": bool(config.read_audio_prompts_fallback_to_gemini()), + "prompts": audio_prompts.list_audio_prompts(), + } + ) + except Exception as e: + self._send_json({"ok": False, "error": str(e), "prompts": []}, 500) + return + + if path == "/api/audio_prompt_record_status": + self._send_json({"ok": True, "status": _read_audio_prompt_record_state()}) + return + + if path == "/api/set_audio_prompt_mode": + mode = q.get("mode", [""])[0] + if mode == "": + self._send_json({"ok": False, "error": "missing mode"}, 400) + return + try: + value = str(config.write_audio_prompt_mode(mode)) + self._send_json({"ok": True, "mode": value}) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + if path == "/api/set_audio_prompt_fallback": + enabled = q.get("enabled", [""])[0] + if enabled == "": + self._send_json({"ok": False, "error": "missing enabled"}, 400) + return + try: + value = bool(config.write_audio_prompts_fallback_to_gemini(enabled)) + self._send_json({"ok": True, "fallback_to_gemini": value}) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + if path == "/api/download_audio_prompt": + key = q.get("key", [""])[0].strip() + if not key: + self._send_json({"ok": False, "error": "missing key"}, 400) + return + try: + prompt_path, body = audio_prompts.read_audio_prompt_bytes(key) + self.send_response(200) + self.send_header("Content-Type", "audio/wav") + self.send_header("Content-Length", str(len(body))) + self.send_header("Content-Disposition", f'attachment; filename="{prompt_path.name}"') + self.end_headers() + self.wfile.write(body) + except FileNotFoundError: + self._send_json({"ok": False, "error": "audio prompt not found"}, 404) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + if path == "/api/delete_audio_prompt": + key = q.get("key", [""])[0].strip() + if not key: + self._send_json({"ok": False, "error": "missing key"}, 400) + return + try: + self._send_json(audio_prompts.delete_audio_prompt(key)) + except KeyError as e: + self._send_json({"ok": False, "error": str(e)}, 400) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + if path == "/api/person_image": + person_id = q.get("id", [""])[0].strip() + kind = q.get("kind", ["face"])[0].strip().lower() + if kind not in ("face", "scene"): + kind = "face" + data = people_registry.read_person_image(person_id, kind=kind) + if data is None: + self._send_json({"ok": False, "error": "person image not found"}, 404) + return + body, ctype, filename = data + self.send_response(200) + self.send_header("Content-Type", ctype) + self.send_header("Content-Length", str(len(body))) + self.send_header("Content-Disposition", f'inline; filename="{filename}"') + self.end_headers() + self.wfile.write(body) + return + + if path == "/api/delete_person": + person_id = q.get("id", [""])[0].strip() + if not person_id: + self._send_json({"ok": False, "error": "missing id"}, 400) + return + try: + ok = people_registry.delete_person(person_id) + if not ok: + self._send_json({"ok": False, "error": "person not found"}, 404) + return + self._send_json({"ok": True, "deleted": person_id}) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + if path == "/api/reset_people": + try: + count = int(people_registry.reset_people()) + self._send_json({"ok": True, "deleted": count}) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + if path == "/api/download_person": + person_id = q.get("id", [""])[0].strip() + if not person_id: + self._send_json({"ok": False, "error": "missing id"}, 400) + return + try: + with tempfile.NamedTemporaryFile(prefix=f"{person_id}_", suffix=".zip", delete=False) as tmp: + tmp_path = Path(tmp.name) + archive_path = people_registry.export_person_zip(person_id, tmp_path) + if archive_path is None or not archive_path.exists(): + try: + tmp_path.unlink() + except Exception: + pass + self._send_json({"ok": False, "error": "person not found"}, 404) + return + body = archive_path.read_bytes() + self.send_response(200) + self.send_header("Content-Type", "application/zip") + self.send_header("Content-Length", str(len(body))) + self.send_header("Content-Disposition", f'attachment; filename="{person_id}.zip"') + self.end_headers() + self.wfile.write(body) + try: + archive_path.unlink() + except Exception: + pass + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + if path == "/api/set_mode": + # set mode via ?mode=ai|manual + m = q.get("mode", [""])[0] + if m == "command": + self._send_json( + { + "ok": False, + "error": "command mode was moved to G1_Lootah/AI_Command", + }, + 410, + ) + return + if m not in ("ai", "manual"): + self._send_json({"ok": False, "error": "invalid mode"}, 400) + return + try: + m = config.write_runtime_mode(m) + self._send_json({"ok": True, "mode": m, "policy": _mode_policy(m)}) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + if path == "/api/set_ai_options": + try: + hard_v = q.get("hard_target_lock_enabled", [None])[0] + retake_v = q.get("retake_prompt_enabled", [None])[0] + greet_enabled_v = q.get("autonomous_greeting_replay_enabled", [None])[0] + greet_file_v = q.get("autonomous_greeting_replay_file", [None])[0] + capture_enabled_v = q.get("autonomous_capture_replay_enabled", [None])[0] + face_recognition_v = q.get("face_recognition_enabled", [None])[0] + face_threshold_v = q.get("face_recognition_threshold", [None])[0] + out = _read_ai_options() + if hard_v is not None: + out["hard_target_lock_enabled"] = bool( + config.write_vision_hard_target_lock_enabled(hard_v) + ) + if retake_v is not None: + out["retake_prompt_enabled"] = bool( + config.write_vision_retake_prompt_enabled(retake_v) + ) + if greet_enabled_v is not None: + out["autonomous_greeting_replay_enabled"] = bool( + config.write_vision_autonomous_greeting_replay_enabled(greet_enabled_v) + ) + if greet_file_v is not None: + out["autonomous_greeting_replay_file"] = str( + config.write_vision_autonomous_greeting_replay_file(greet_file_v) + ) + if capture_enabled_v is not None: + out["autonomous_capture_replay_enabled"] = bool( + config.write_vision_autonomous_capture_replay_enabled(capture_enabled_v) + ) + if face_recognition_v is not None: + out["face_recognition_enabled"] = bool( + config.write_vision_face_recognition_enabled(face_recognition_v) + ) + if face_threshold_v is not None: + out["face_recognition_threshold"] = float( + config.write_vision_face_recognition_threshold(face_threshold_v) + ) + out["active_replay"] = _read_active_replay_name() + self._send_json({"ok": True, "options": out}) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + if path == "/api/set_mic": + try: + enabled_v = q.get("enabled", [None])[0] + if enabled_v is None: + self._send_json({"ok": False, "error": "missing enabled"}, 400) + return + enabled = bool(config.write_gemini_mic_enabled(enabled_v)) + self._send_json({"ok": True, "options": {"mic_enabled": enabled}}) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + if path == "/api/mode_policy": + m = _read_mode() + self._send_json({"ok": True, "mode": m, "policy": _mode_policy(m)}) + return + + if path == "/api/set_detector_backend": + b = q.get("backend", [""])[0] + if b not in ("normal", "yolo"): + self._send_json({"ok": False, "error": "invalid backend"}, 400) + return + try: + mode = _read_mode() + strict_required = _strict_yolo_required() + if strict_required and mode == "ai" and b != "yolo": + self._send_json( + { + "ok": False, + "error": "Strict AI profile requires YOLO backend while mode=ai.", + "backend": _read_detector_backend(), + "strict_required": True, + }, + 409, + ) + return + b = config.write_vision_detector_backend(b) + self._send_json( + { + "ok": True, + "backend": b, + "yolo_runtime": str(config.read_vision_yolo_runtime()), + "options": ["normal", "yolo"], + "strict_required": strict_required, + "locked": bool(strict_required and mode == "ai"), + } + ) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + if path == "/api/command_info": + self._send_json( + { + "ok": False, + "error": "command mode moved", + "moved_to": "G1_Lootah/AI_Command", + }, + 410, + ) + return + + if path == "/api/test": + res = _realsense_test() + self._send_json(res, 200 if res.get("ok") else 500) + return + + if path == "/api/fix": + res = _run_fix_script() + self._send_json(res, 200 if res.get("ok") else 500) + return + + if path == "/api/run_scripts_fix": + # Run the Scripts/fix_realsense_usb.sh with optional mode ?mode=check|fix + mode = q.get('mode', ['--fix'])[0] or '--fix' + try: + scripts_sh = _resolve_fix_script() + if not scripts_sh: + self._send_json( + {"ok": False, "error": "script not found", "checked": [str(p) for p in _fix_script_candidates()]}, + 404, + ) + return + # run non-interactive + p = subprocess.run(["bash", str(scripts_sh), mode], capture_output=True, text=True, timeout=60) + out = (p.stdout or "").strip().splitlines() + err = (p.stderr or "").strip().splitlines() + ok = p.returncode == 0 + resp = {"ok": ok, "rc": p.returncode, "stdout": out[-60:], "stderr": err[-60:]} + self._send_json(resp, 200 if ok else 500) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + if path == "/api/capture": + # Take photo NOW (no remote) + result = capture_func() + ok = not result.startswith("[ERR]") + self._send_json({"ok": ok, "result": result}, 200 if ok else 500) + return + + if path == "/api/sessions": + items = _list_photos(folder) + sessions = _group_sessions(items) + self._send_json({"ok": True, "sessions": sessions}) + return + + if path == "/api/photos": + items = _list_photos(folder) + self._send_json({"ok": True, "photos": items}) + return + + # Request a photo from autonomous mover or external monitor + if path == "/api/request_photo": + try: + # touch a request file for external processes to pick up + reqf = SCRIPTS_DIR / "request_photo.flag" + reqf.write_text(str(time.time())) + self._send_json({"ok": True, "requested": True}) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + # Clear all photos (DELETE) - destructive + if path == "/api/clear_photos": + try: + for p in folder.iterdir(): + if _is_photo_file(p): + try: + p.unlink() + except Exception: + pass + self._send_json({"ok": True, "cleared": True}) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + # Create a ZIP archive of all photos and return path + if path == "/api/download_zip": + try: + import shutil + zip_base = folder / "_archives" + zip_base.mkdir(parents=True, exist_ok=True) + ts = int(time.time()) + archive_name = str(zip_base / f"photos_{ts}") + shutil.make_archive(archive_name, 'zip', root_dir=str(folder)) + archive_file = archive_name + '.zip' + # serve relative URL + rel = os.path.relpath(archive_file, start=folder) + self._send_json({"ok": True, "archive": rel}) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + # Trigger uploader now by touching a flag file + if path == "/api/upload_now": + try: + upf = SCRIPTS_DIR / "upload_now.flag" + upf.write_text(str(time.time())) + self._send_json({"ok": True, "upload_now": True}) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + if path == "/api/delete": + name = _safe_name(q.get("name", [""])[0]) + if not name: + self._send_json({"ok": False, "error": "missing name"}, 400) + return + target = (folder / name).resolve() + + # ensure inside folder + try: + target.relative_to(folder) + except Exception: + self._send_json({"ok": False, "error": "invalid path"}, 400) + return + + if not target.exists(): + self._send_json({"ok": False, "error": "not found"}, 404) + return + + try: + target.unlink() + self._send_json({"ok": True, "deleted": name}, 200) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + if path == "/api/retake": + # Trigger a capture and return result. Optionally accept session_id to associate. + session_id = q.get("session_id", [None])[0] + result = capture_func() + ok = not result.startswith("[ERR]") + self._send_json({"ok": ok, "result": result, "session_id": session_id}, 200 if ok else 500) + return + + if path == "/api/reupload": + # Allow manual reupload: clears uploaded flag in upload DB so the uploader daemon retries + name = _safe_name(q.get("name", [""])[0]) + if not name: + self._send_json({"ok": False, "error": "missing name"}, 400) + return + dbp = Path(config.UPLOAD_DB) + if dbp.exists(): + try: + d = json.loads(dbp.read_text()) + except Exception: + d = {} + else: + d = {} + # clear uploaded marker + entry = d.get(name, {}) + entry["uploaded"] = False + d[name] = entry + try: + dbp.write_text(json.dumps(d, indent=2)) + self._send_json({"ok": True, "requeued": name}) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + # Replay management endpoints + if path == "/api/replays": + try: + items = _list_replays() + self._send_json({"ok": True, "replays": [it["name"] for it in items], "items": items}) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + if path == "/api/replay_record_status": + self._send_json({"ok": True, "status": _read_recorder_state()}) + return + + if path == "/api/replay_test_status": + self._send_json({"ok": True, "status": _read_replay_test_state()}) + return + + if path == "/api/replay_record_start": + try: + if _read_mode() != "manual": + self._send_json({"ok": False, "error": "replay recording is allowed only in manual mode"}, 409) + return + name = _normalize_replay_name(q.get("name", [""])[0]) + seconds = float(q.get("seconds", ["15"])[0]) + if seconds <= 0: + self._send_json({"ok": False, "error": "seconds must be positive"}, 400) + return + cur = _read_recorder_state() + if cur.get("running"): + self._send_json({"ok": False, "error": "recorder already running", "status": cur}, 409) + return + preview_path = _resolve_replay_path(name) + preview_path.parent.mkdir(parents=True, exist_ok=True) + if preview_path.exists(): + self._send_json({"ok": False, "error": "replay already exists"}, 409) + return + preview_output = str(preview_path) + _set_recorder_state( + running=True, + ok=False, + error="", + name=name, + seconds=float(seconds), + output=preview_output, + returncode=None, + started_at=time.time(), + finished_at=0.0, + stdout_tail=[], + ) + threading.Thread(target=_run_replay_recorder, args=(name, seconds), daemon=True).start() + self._send_json({"ok": True, "status": _read_recorder_state()}) + except ValueError as e: + self._send_json({"ok": False, "error": str(e)}, 400) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + if path == "/api/test_replay": + try: + if _read_mode() != "manual": + self._send_json({"ok": False, "error": "replay test is allowed only in manual mode"}, 409) + return + if replay_test_func is None: + self._send_json({"ok": False, "error": "replay test is unavailable in this runtime"}, 503) + return + name = _normalize_replay_name(q.get("name", [""])[0]) + candidate = _resolve_replay_path(name) + if not candidate.exists(): + self._send_json({"ok": False, "error": "replay not found"}, 404) + return + cur = _read_replay_test_state() + if cur.get("running"): + self._send_json({"ok": False, "error": "replay test already running", "status": cur}, 409) + return + _set_replay_test_state( + running=True, + ok=False, + error="", + name=name, + result="", + started_at=time.time(), + finished_at=0.0, + ) + threading.Thread(target=_run_replay_test, args=(name, replay_test_func), daemon=True).start() + self._send_json({"ok": True, "status": _read_replay_test_state()}) + except ValueError as e: + self._send_json({"ok": False, "error": str(e)}, 400) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + if path == "/api/delete_replay": + try: + name = q.get("name", [""])[0] + candidate = _resolve_replay_path(name) + if not candidate.exists(): + self._send_json({"ok": False, "error": "replay not found"}, 404) + return + active_name = _read_active_replay_name() + rel = str(candidate.resolve().relative_to(config.DATA_DIR)).replace("\\", "/") + if rel == active_name: + self._send_json({"ok": False, "error": "cannot delete the active replay"}, 409) + return + if _is_greeting_replay(rel): + self._send_json({"ok": False, "error": "cannot delete the configured AI greeting replay"}, 409) + return + candidate.unlink() + self._send_json({"ok": True, "deleted": rel}) + except ValueError as e: + self._send_json({"ok": False, "error": str(e)}, 400) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + if path == "/api/rename_replay": + try: + old_name = q.get("old", [""])[0] + new_name = q.get("new", [""])[0] + old_candidate = _resolve_replay_path(old_name) + if not old_candidate.exists(): + self._send_json({"ok": False, "error": "replay not found"}, 404) + return + old_rel = str(old_candidate.resolve().relative_to(config.DATA_DIR)).replace("\\", "/") + old_parent = Path(old_rel).parent + default_parent = None if str(old_parent) == "." else old_parent.as_posix() + new_rel = _normalize_replay_name(new_name, default_parent=default_parent) + new_candidate = _resolve_replay_path(new_rel) + if new_candidate.exists(): + self._send_json({"ok": False, "error": "target replay already exists"}, 409) + return + new_candidate.parent.mkdir(parents=True, exist_ok=True) + old_candidate.rename(new_candidate) + _update_replay_references_after_rename(old_rel, new_rel, new_candidate) + self._send_json({"ok": True, "old": old_rel, "new": new_rel}) + except ValueError as e: + self._send_json({"ok": False, "error": str(e)}, 400) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + if path == "/api/download_replay": + try: + name = q.get("name", [""])[0] + candidate = _resolve_replay_path(name) + if not candidate.exists(): + self._send_json({"ok": False, "error": "replay not found"}, 404) + return + data = candidate.read_bytes() + self.send_response(200) + self.send_header("Content-Type", "application/json; charset=utf-8") + self.send_header("Content-Length", str(len(data))) + self.send_header("Content-Disposition", f'attachment; filename="{candidate.name}"') + self.end_headers() + self.wfile.write(data) + except ValueError as e: + self._send_json({"ok": False, "error": str(e)}, 400) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + if path == "/api/scripts": + try: + scripts_dir = DATA_SCRIPTS_DIR + scripts_dir.mkdir(parents=True, exist_ok=True) + files = [ + p.name + for p in sorted(scripts_dir.iterdir()) + if p.is_file() and p.suffix.lower() in (".txt", ".json", ".jsonl") + ] + self._send_json({"ok": True, "scripts": files}) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + if path == "/api/script_content": + # return raw text of a script by name (in Scripts/) + name = q.get('name', [None])[0] + if not name: + self._send_json({"ok": False, "error": "missing name"}, 400) + return + try: + scripts_dir = DATA_SCRIPTS_DIR + candidate = (scripts_dir / _safe_name(name)).resolve() + try: + candidate.relative_to(scripts_dir) + except Exception: + self._send_json({"ok": False, "error": "invalid path"}, 400) + return + if not candidate.exists(): + self._send_json({"ok": False, "error": "not found"}, 404) + return + txt = candidate.read_text(encoding='utf-8') + self._send_json({"ok": True, "script": txt}) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + if path == "/api/get_replay": + try: + cur = _read_active_replay_name() + self._send_json({"ok": True, "replay": cur}) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + if path == "/api/sanad_script": + try: + txt = _read_text_file(config.SANAD_SCRIPT_FILE) or "" + self._send_json({"ok": True, "script": txt}) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + if path == "/api/set_replay": + # set via ?name=filename.jsonl + name = q.get("name", [""])[0] + if not name: + self._send_json({"ok": False, "error": "missing name"}, 400) + return + try: + candidate = _resolve_replay_path(name) + except ValueError as e: + self._send_json({"ok": False, "error": str(e)}, 400) + return + if not candidate.exists(): + self._send_json({"ok": False, "error": "replay not found"}, 404) + return + integrity = replay_file_integrity(candidate) + if not integrity.get("ok"): + self._send_json( + {"ok": False, "error": "invalid replay file", "integrity": integrity}, + 400, + ) + return + try: + rel_name = str(candidate.resolve().relative_to(config.DATA_DIR)).replace("\\", "/") + config.write_selected_replay_name(rel_name) + config.REPLAY_FILE = candidate + resp = {"ok": True, "set": rel_name} + if not integrity.get("trigger_ok", False): + resp["warning"] = "replay has no trigger markers; timed capture fallback will be used" + resp["integrity"] = integrity + self._send_json(resp) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + # MJPEG preview stream + if path == "/preview.mjpg": + self.send_response(200) + self.send_header("Content-Type", "multipart/x-mixed-replace; boundary=--frame") + self.end_headers() + try: + while True: + frame = _get_preview_frame() + if frame is None: + time.sleep(0.1) + continue + cv2 = _get_cv2() + ret, jpg = cv2.imencode('.jpg', frame, [int(cv2.IMWRITE_JPEG_QUALITY), 65]) + if not ret: + time.sleep(0.05) + continue + data = jpg.tobytes() + self.wfile.write(b"--frame\r\n") + self.wfile.write(b"Content-Type: image/jpeg\r\n") + self.wfile.write(f"Content-Length: {len(data)}\r\n\r\n".encode('utf-8')) + self.wfile.write(data) + self.wfile.write(b"\r\n") + self.wfile.flush() + # small throttle + time.sleep(0.08) + except Exception as e: + record_error( + "photo_server", + "preview_stream", + e, + {"client": self.client_address[0] if self.client_address else "unknown"}, + ) + return + + + # Gallery page: serve gallery.html (client JS renders cards) + if path == "/": + tpl = _read_text_file(GALLERY_HTML) + if tpl is None: + self.send_response(404) + self.end_headers() + return + html = tpl.replace("{{PHOTOS_DIR}}", str(folder)) + # leave PHOTO_CARDS and MODE_TOGGLE for client-side JS to populate + self._send_text(html, 200, "text/html; charset=utf-8") + return + + # Otherwise: serve static files from photos/ (download/open) + return super().do_GET() + + def do_POST(self): + parsed = urllib.parse.urlparse(self.path) + path = parsed.path + # Only used to update sanad script content currently + if path == "/api/sanad_script": + try: + length = int(self.headers.get('Content-Length', '0')) + body = self.rfile.read(length) if length else b"" + # accept raw text or JSON {"script": "..."} + try: + payload = json.loads(body.decode('utf-8')) + script = payload.get('script', '') + except Exception: + script = body.decode('utf-8') + # write to SANAD_SCRIPT_FILE + try: + config.SANAD_SCRIPT_FILE.write_text(script, encoding='utf-8') + self._send_json({"ok": True, "written": True}) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + if path == "/api/audio_prompt_record": + try: + length = int(self.headers.get("Content-Length", "0")) + body = self.rfile.read(length) if length else b"" + payload = json.loads(body.decode("utf-8")) if body else {} + if not isinstance(payload, dict): + self._send_json({"ok": False, "error": "invalid payload"}, 400) + return + key = str(payload.get("key", "") or "").strip() + text = str(payload.get("text", "") or "").strip() + filename = str(payload.get("filename", "") or "").strip() + if not key: + self._send_json({"ok": False, "error": "missing key"}, 400) + return + if not text: + self._send_json({"ok": False, "error": "missing text"}, 400) + return + cur = _read_audio_prompt_record_state() + if cur.get("running"): + self._send_json({"ok": False, "error": "audio prompt recorder already running", "status": cur}, 409) + return + default_filename = audio_prompts.prompt_filename(key) + _set_audio_prompt_record_state( + running=True, + key=key, + filename=filename or default_filename, + text=text, + ok=False, + error="", + started_at=time.time(), + finished_at=0.0, + result={}, + ) + threading.Thread( + target=_run_audio_prompt_record, + args=(key, text, filename or default_filename), + daemon=True, + ).start() + self._send_json({"ok": True, "status": _read_audio_prompt_record_state()}) + except (ValueError, KeyError) as e: + self._send_json({"ok": False, "error": str(e)}, 400) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + if path == "/api/upload_person": + try: + form = cgi.FieldStorage( + fp=self.rfile, + headers=self.headers, + environ={ + "REQUEST_METHOD": "POST", + "CONTENT_TYPE": self.headers.get("Content-Type", ""), + }, + ) + if "file" not in form: + self._send_json({"ok": False, "error": "missing file"}, 400) + return + file_item = form["file"] + if not getattr(file_item, "file", None): + self._send_json({"ok": False, "error": "missing file payload"}, 400) + return + data = file_item.file.read() + if not data: + self._send_json({"ok": False, "error": "empty upload"}, 400) + return + person_id = str(form.getfirst("person_id", "") or "").strip() + filename = str(getattr(file_item, "filename", "") or "") + result = people_registry.import_person_photo(data, filename=filename, person_id=person_id) + ok = bool(result.get("ok", False)) + self._send_json(result, 200 if ok else 400) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + if path == "/api/upload_audio_prompt": + try: + form = cgi.FieldStorage( + fp=self.rfile, + headers=self.headers, + environ={ + "REQUEST_METHOD": "POST", + "CONTENT_TYPE": self.headers.get("Content-Type", ""), + }, + ) + key = str(form.getfirst("key", "") or "").strip() + if not key: + self._send_json({"ok": False, "error": "missing key"}, 400) + return + if "file" not in form: + self._send_json({"ok": False, "error": "missing file"}, 400) + return + file_item = form["file"] + if not getattr(file_item, "file", None): + self._send_json({"ok": False, "error": "missing file payload"}, 400) + return + data = file_item.file.read() + if not data: + self._send_json({"ok": False, "error": "empty upload"}, 400) + return + filename = str(form.getfirst("filename", "") or getattr(file_item, "filename", "") or "") + result = audio_prompts.save_audio_prompt(key, data, filename) + self._send_json(result, 200 if bool(result.get("ok")) else 400) + except (KeyError, ValueError) as e: + self._send_json({"ok": False, "error": str(e)}, 400) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + if path == "/api/upload_replay": + try: + form = cgi.FieldStorage( + fp=self.rfile, + headers=self.headers, + environ={ + "REQUEST_METHOD": "POST", + "CONTENT_TYPE": self.headers.get("Content-Type", ""), + }, + ) + if "file" not in form: + self._send_json({"ok": False, "error": "missing file"}, 400) + return + file_item = form["file"] + if not getattr(file_item, "file", None): + self._send_json({"ok": False, "error": "missing file payload"}, 400) + return + raw_name = form.getfirst("name", "") or getattr(file_item, "filename", "") or "uploaded_replay.jsonl" + rel_name = _normalize_replay_name(raw_name) + candidate = _resolve_replay_path(rel_name) + if candidate.exists(): + self._send_json({"ok": False, "error": "replay already exists"}, 409) + return + candidate.parent.mkdir(parents=True, exist_ok=True) + data = file_item.file.read() + if not data: + self._send_json({"ok": False, "error": "empty upload"}, 400) + return + candidate.write_bytes(data) + integrity = replay_file_integrity(candidate) + if not integrity.get("ok"): + try: + candidate.unlink() + except Exception: + pass + self._send_json({"ok": False, "error": "invalid replay file", "integrity": integrity}, 400) + return + self._send_json({"ok": True, "saved": rel_name, "integrity": integrity}) + except ValueError as e: + self._send_json({"ok": False, "error": str(e)}, 400) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + # Upload / manage SANAD scripts + if path == "/api/upload_script": + try: + # Accept JSON {"filename": "name.txt", "script": "..."} or raw text with ?filename=... + length = int(self.headers.get('Content-Length', '0')) + body = self.rfile.read(length) if length else b"" + try: + payload = json.loads(body.decode('utf-8')) + filename = payload.get('filename') + script = payload.get('script', '') + except Exception: + filename = urllib.parse.parse_qs(parsed.query).get('filename', [None])[0] + script = body.decode('utf-8') + if not filename: + self._send_json({"ok": False, "error": "missing filename"}, 400) + return + scripts_dir = DATA_SCRIPTS_DIR + scripts_dir.mkdir(parents=True, exist_ok=True) + target = (scripts_dir / _safe_name(filename)).resolve() + try: + target.relative_to(scripts_dir) + except Exception: + self._send_json({"ok": False, "error": "invalid filename"}, 400) + return + target.write_text(script, encoding='utf-8') + self._send_json({"ok": True, "saved": target.name}) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + if path == "/api/delete_script": + try: + length = int(self.headers.get('Content-Length', '0')) + body = self.rfile.read(length) if length else b"" + try: + payload = json.loads(body.decode('utf-8')) + name = payload.get('name') + except Exception: + # allow raw name in body + name = body.decode('utf-8').strip() + if not name: + self._send_json({"ok": False, "error": "missing name"}, 400) + return + scripts_dir = DATA_SCRIPTS_DIR + target = (scripts_dir / _safe_name(name)).resolve() + try: + target.relative_to(scripts_dir) + except Exception: + self._send_json({"ok": False, "error": "invalid path"}, 400) + return + if not target.exists(): + self._send_json({"ok": False, "error": "not found"}, 404) + return + target.unlink() + self._send_json({"ok": True, "deleted": name}) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + if path == "/api/set_sanad_script": + # Accept ?name=filename or JSON {"name":"..."} + try: + qs = urllib.parse.parse_qs(parsed.query) + name = qs.get('name', [None])[0] + if not name: + length = int(self.headers.get('Content-Length', '0')) + body = self.rfile.read(length) if length else b"" + try: + payload = json.loads(body.decode('utf-8')) + name = payload.get('name') + except Exception: + name = None + if not name: + self._send_json({"ok": False, "error": "missing name"}, 400) + return + scripts_dir = DATA_SCRIPTS_DIR + candidate = (scripts_dir / _safe_name(name)).resolve() + try: + candidate.relative_to(scripts_dir) + except Exception: + self._send_json({"ok": False, "error": "invalid script path"}, 400) + return + if not candidate.exists(): + self._send_json({"ok": False, "error": "script not found"}, 404) + return + # copy contents into SANAD_SCRIPT_FILE + try: + txt = candidate.read_text(encoding='utf-8') + config.SANAD_SCRIPT_FILE.write_text(txt, encoding='utf-8') + self._send_json({"ok": True, "set": candidate.name}) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + except Exception as e: + self._send_json({"ok": False, "error": str(e)}, 500) + return + + # fallback + self.send_response(404) + self.end_headers() + + try: + ThreadingHTTPServer.allow_reuse_address = True + httpd = ThreadingHTTPServer((bind, port), Handler) + except OSError as e: + _log(lg, f"โŒ Photo server failed: {e}", "error") + # Assume another server already running + _log(lg, f"๐Ÿ–ผ๏ธ Phone gallery (existing): {url}", "info") + return url + + def _serve(): + try: + httpd.serve_forever() + except Exception: + pass + + t = threading.Thread(target=_serve, daemon=True) + t.start() + + + _log(lg, f"๐Ÿ–ผ๏ธ Photo server serving {folder} on {url}", "info") + return url + + +# ============================================================ +# CLI mode (optional) +# ============================================================ +if __name__ == "__main__": + photos = Path(os.environ.get("PHOTOS_DIR", str(DEFAULT_PHOTOS_DIR))).resolve() + port = int(os.environ.get("PHOTO_SERVER_PORT", "8080")) + start_photo_server(photos, port=port) + print("Server running. Press Ctrl+C to stop.") + try: + while True: + time.sleep(3600) + except KeyboardInterrupt: + pass diff --git a/Server/uploader.py b/Server/uploader.py new file mode 100644 index 0000000..1dca172 --- /dev/null +++ b/Server/uploader.py @@ -0,0 +1,167 @@ +""" +uploader.py + +Daemon that watches the photos folder for new files and uploads them +via HTTP POST (default) or S3 (optional, requires boto3). Implements +retry with exponential backoff and stores upload state in a small JSON DB. +""" +import threading +import time +import json +from pathlib import Path +from typing import Dict +import requests +import logging +try: + import boto3 + _HAS_BOTO3 = True +except Exception: + _HAS_BOTO3 = False + +from Core.Logger import Logs +from Core import settings as config + +sanad_logger = Logs() +sanad_logger.LogEngine("G1_Logs", "uploader") + + +class UploadDaemon: + def __init__(self, photos_dir: Path = config.PHOTOS_DIR, poll_s: float = 2.0): + self.photos_dir = Path(photos_dir) + self.poll_s = float(poll_s) + self._stop = threading.Event() + self._thread = None + self._db_path = Path(config.UPLOAD_DB) + self._state = self._load_db() + + def _load_db(self) -> Dict[str, Dict]: + try: + if self._db_path.exists(): + return json.loads(self._db_path.read_text()) + except Exception: + pass + return {} + + def _save_db(self): + try: + self._db_path.write_text(json.dumps(self._state, indent=2)) + except Exception as e: + sanad_logger.print_and_log(f"Failed to write upload db: {e}", "warning") + + def start(self): + if self._thread and self._thread.is_alive(): + return + self._stop.clear() + self._thread = threading.Thread(target=self._run, daemon=True) + self._thread.start() + sanad_logger.print_and_log("๐Ÿ“ค Upload daemon started.", "info") + + def stop(self): + self._stop.set() + if self._thread: + self._thread.join(timeout=1.0) + + def _should_upload(self, path: Path) -> bool: + s = self._state.get(str(path), {}) + return not s.get("uploaded", False) + + def _mark_uploaded(self, path: Path, info: Dict): + self._state[str(path)] = {"uploaded": True, "info": info, "ts": time.time()} + self._save_db() + + def _upload_http(self, path: Path) -> Dict: + url = config.UPLOAD_URL + if not url: + raise RuntimeError("UPLOAD_URL is not configured") + with open(path, "rb") as f: + r = requests.post(url, files={"file": f}, timeout=30) + r.raise_for_status() + return {"status": "ok", "resp": r.text} + + def _upload_s3(self, path: Path) -> Dict: + if not _HAS_BOTO3: + raise RuntimeError("boto3 not installed; install it to use S3 uploads") + bucket = config.UPLOAD_S3_BUCKET + if not bucket: + raise RuntimeError("UPLOAD_S3_BUCKET not configured") + + # Build client using provided keys or default env/iam + kwargs = {} + if config.UPLOAD_S3_KEY and config.UPLOAD_S3_SECRET: + kwargs["aws_access_key_id"] = config.UPLOAD_S3_KEY + kwargs["aws_secret_access_key"] = config.UPLOAD_S3_SECRET + if config.UPLOAD_S3_REGION: + kwargs["region_name"] = config.UPLOAD_S3_REGION + + s3 = boto3.client("s3", **kwargs) + key = path.name + try: + s3.upload_file(str(path), bucket, key) + return {"status": "ok", "bucket": bucket, "key": key} + except Exception: + raise + + def _run(self): + # If upload destination is not configured, keep daemon alive but idle. + if config.UPLOAD_METHOD == "http" and not str(config.UPLOAD_URL or "").strip(): + sanad_logger.print_and_log("๐Ÿ“ค Upload daemon idle: UPLOAD_URL is not configured.", "warning") + while not self._stop.is_set(): + time.sleep(max(2.0, self.poll_s)) + return + if config.UPLOAD_METHOD == "s3" and not str(config.UPLOAD_S3_BUCKET or "").strip(): + sanad_logger.print_and_log("๐Ÿ“ค Upload daemon idle: UPLOAD_S3_BUCKET is not configured.", "warning") + while not self._stop.is_set(): + time.sleep(max(2.0, self.poll_s)) + return + + while not self._stop.is_set(): + try: + for p in sorted(self.photos_dir.glob("**/*")): + if not p.is_file(): + continue + if not self._should_upload(p): + continue + + # Exponential backoff per-file + attempts = 0 + backoff = 1.0 + success = False + while attempts < 5 and not success and not self._stop.is_set(): + try: + sanad_logger.print_and_log(f"Uploading {p} (attempt {attempts+1})", "info") + if config.UPLOAD_METHOD == "http": + info = self._upload_http(p) + elif config.UPLOAD_METHOD == "s3": + info = self._upload_s3(p) + else: + raise NotImplementedError("UPLOAD_METHOD not implemented by daemon") + self._mark_uploaded(p, info) + sanad_logger.print_and_log(f"Uploaded {p}", "info") + success = True + except Exception as e: + attempts += 1 + sanad_logger.print_and_log(f"Upload failed ({e}), backoff {backoff}s", "warning") + time.sleep(backoff) + backoff = min(30.0, backoff * 2) + + time.sleep(self.poll_s) + except Exception as e: + sanad_logger.print_and_log(f"Upload loop error: {e}", "error") + time.sleep(5.0) + + +def start_uploader(photos_dir: Path = config.PHOTOS_DIR) -> UploadDaemon: + d = UploadDaemon(photos_dir) + d.start() + return d + + +if __name__ == "__main__": + logging.basicConfig(level=logging.INFO) + d = UploadDaemon() + d.start() + try: + while True: + time.sleep(1) + except KeyboardInterrupt: + d.stop() diff --git a/Web/direct_camera.css b/Web/direct_camera.css new file mode 100644 index 0000000..d45c41c --- /dev/null +++ b/Web/direct_camera.css @@ -0,0 +1,162 @@ +:root { + --bg: #eef2e9; + --panel: #f9fbf6; + --ink: #162015; + --muted: #5f6f5f; + --accent: #205f4a; + --line: #c9d4c4; + --danger: #8a2d24; +} + +* { + box-sizing: border-box; +} + +body { + margin: 0; + font-family: Georgia, "Times New Roman", serif; + background: linear-gradient(180deg, #f4f1e7 0%, var(--bg) 100%); + color: var(--ink); +} + +.wrap { + max-width: 1280px; + margin: 0 auto; + padding: 24px; +} + +.top { + display: grid; + grid-template-columns: 1.1fr 0.9fr; + gap: 24px; + align-items: start; +} + +.panel { + background: rgba(249, 251, 246, 0.94); + border: 1px solid var(--line); + border-radius: 18px; + padding: 18px; + box-shadow: 0 12px 30px rgba(22, 32, 21, 0.08); +} + +.panel-space { + margin-top: 24px; +} + +h1, +h2 { + margin: 0 0 12px; +} + +.actions { + display: flex; + flex-wrap: wrap; + gap: 10px; + margin: 12px 0 0; +} + +button, +.btn { + appearance: none; + border: 1px solid var(--accent); + background: var(--accent); + color: white; + padding: 10px 14px; + border-radius: 999px; + cursor: pointer; + font: inherit; + text-decoration: none; + display: inline-block; +} + +button.secondary, +.btn.secondary { + background: white; + color: var(--accent); +} + +button.danger, +.btn.danger { + background: white; + color: var(--danger); + border-color: var(--danger); +} + +select, +input[type="number"] { + appearance: none; + border: 1px solid var(--line); + background: white; + color: var(--ink); + padding: 10px 12px; + border-radius: 999px; + font: inherit; + min-width: 100px; +} + +.meta { + color: var(--muted); + margin: 6px 0; +} + +.preview { + width: 100%; + aspect-ratio: 4 / 3; + object-fit: cover; + border-radius: 14px; + background: #dbe3d6; + border: 1px solid var(--line); +} + +.status { + margin-top: 12px; + padding: 10px 12px; + border-radius: 12px; + background: #edf5eb; + border: 1px solid var(--line); + color: var(--muted); + white-space: pre-wrap; +} + +.grid { + display: grid; + grid-template-columns: repeat(auto-fill, minmax(220px, 1fr)); + gap: 18px; + margin-top: 20px; +} + +.card { + background: rgba(255, 255, 255, 0.78); + border: 1px solid var(--line); + border-radius: 16px; + padding: 12px; +} + +.thumb { + width: 100%; + aspect-ratio: 4 / 3; + object-fit: cover; + border-radius: 12px; + border: 1px solid var(--line); + background: #dde6d9; +} + +.name { + margin-top: 10px; + font-weight: 700; + overflow-wrap: anywhere; +} + +.row { + display: flex; + gap: 8px; + flex-wrap: wrap; + margin-top: 10px; +} + +@media (max-width: 900px) { + .top { + grid-template-columns: 1fr; + } +} diff --git a/Web/direct_camera.html b/Web/direct_camera.html new file mode 100644 index 0000000..b030957 --- /dev/null +++ b/Web/direct_camera.html @@ -0,0 +1,56 @@ + + + + + + Direct Camera Service + + + +
+
+
+

Direct Camera Service

+
Main camera service. No teleimager. Direct RealSense/OpenCV camera access only.
+ preview +
+ + + Download All +
+
Loading...
+
+ +
+

Camera

+
Sample captures are saved in photos/samples/.
+
+ + + + + +
+
Choose a preset or enter width, height, and fps manually. The stream will reopen with the new settings.
+
Checking camera...
+
+
+ +
+

Samples

+ +
+
+ + + + diff --git a/Web/direct_camera.js b/Web/direct_camera.js new file mode 100644 index 0000000..c00f4a8 --- /dev/null +++ b/Web/direct_camera.js @@ -0,0 +1,127 @@ +(function () { + function restartPreview() { + const img = document.getElementById("preview_img"); + if (!img) { + return; + } + img.src = `/preview.mjpg?t=${Date.now()}`; + } + + function setResolutionInputs(width, height, fps) { + document.getElementById("width_input").value = String(width || ""); + document.getElementById("height_input").value = String(height || ""); + document.getElementById("fps_input").value = String(fps || ""); + const preset = `${width}x${height}@${fps}`; + const sel = document.getElementById("resolution_select"); + const hasPreset = Array.from(sel.options).some((opt) => opt.value === preset); + sel.value = hasPreset ? preset : ""; + } + + async function api(path) { + const response = await fetch(path); + if (!response.ok) { + throw new Error(await response.text()); + } + return response.json(); + } + + function fmtBytes(n) { + if (n < 1024) { + return `${n} B`; + } + if (n < 1024 * 1024) { + return `${(n / 1024).toFixed(1)} KB`; + } + return `${(n / (1024 * 1024)).toFixed(1)} MB`; + } + + async function refreshAll() { + const [health, photos] = await Promise.all([api("/api/health"), api("/api/photos")]); + const camera = health.camera || {}; + const widthInput = document.getElementById("width_input"); + if (widthInput.dataset.initialized !== "1") { + setResolutionInputs(camera.requested_width, camera.requested_height, camera.requested_fps); + widthInput.dataset.initialized = "1"; + } + + document.getElementById("status").textContent = camera.ok + ? `Camera OK\nSource: ${camera.source}\nBackend: ${camera.backend}\nActive: ${camera.profile || "-"}\nRequested: ${camera.requested_profile}\nPreferred RS Serial: ${camera.preferred_realsense_serial || "-"}\nConfig RS Serial: ${camera.config_realsense_serial || "-"}\nFallback RS Serial: ${camera.configured_realsense_serial || "-"}\nActive RS Serial: ${camera.realsense_serial || "-"}\nSamples: ${photos.items.length}` + : `Camera not ready\nSource: ${camera.source}\nRequested: ${camera.requested_profile}\nPreferred RS Serial: ${camera.preferred_realsense_serial || "-"}\nConfig RS Serial: ${camera.config_realsense_serial || "-"}\nFallback RS Serial: ${camera.configured_realsense_serial || "-"}\nActive RS Serial: ${camera.realsense_serial || "-"}\nError: ${camera.last_error || "-"}`; + + document.getElementById("camera_status").textContent = JSON.stringify(health, null, 2); + + const gallery = document.getElementById("gallery"); + gallery.innerHTML = ""; + for (const item of photos.items) { + const card = document.createElement("article"); + card.className = "card"; + card.innerHTML = ` + +
${item.name}
+
${fmtBytes(item.size)}
+
+ Download + +
+ `; + gallery.appendChild(card); + } + + gallery.querySelectorAll("button.danger").forEach((btn) => { + btn.addEventListener("click", async () => { + const { name } = btn.dataset; + await api(`/api/delete?name=${encodeURIComponent(name)}`); + await refreshAll(); + }); + }); + } + + document.getElementById("capture_btn").addEventListener("click", async () => { + const status = document.getElementById("status"); + status.textContent = "Capturing..."; + try { + const resp = await api("/api/capture"); + status.textContent = `Saved: ${resp.name}`; + await refreshAll(); + } catch (e) { + status.textContent = `Capture failed\n${e.message}`; + } + }); + + document.getElementById("resolution_select").addEventListener("change", (e) => { + const value = e.target.value; + const match = value.match(/^(\d+)x(\d+)@(\d+)$/); + if (!match) { + return; + } + setResolutionInputs(Number(match[1]), Number(match[2]), Number(match[3])); + }); + + document.getElementById("apply_resolution_btn").addEventListener("click", async () => { + const width = Number(document.getElementById("width_input").value); + const height = Number(document.getElementById("height_input").value); + const fps = Number(document.getElementById("fps_input").value); + const status = document.getElementById("status"); + status.textContent = `Applying resolution ${width}x${height}@${fps}...`; + try { + const resp = await api( + `/api/set_resolution?width=${encodeURIComponent(width)}&height=${encodeURIComponent(height)}&fps=${encodeURIComponent(fps)}` + ); + const camera = resp.camera || {}; + setResolutionInputs(camera.requested_width, camera.requested_height, camera.requested_fps); + restartPreview(); + await refreshAll(); + } catch (e) { + status.textContent = `Resolution change failed\n${e.message}`; + } + }); + + document.getElementById("refresh_btn").addEventListener("click", refreshAll); + + refreshAll().catch((e) => { + document.getElementById("status").textContent = String(e); + }); + setInterval(() => { + refreshAll().catch(() => {}); + }, 10000); +})(); diff --git a/Web/gallery.html b/Web/gallery.html new file mode 100644 index 0000000..de03f8d --- /dev/null +++ b/Web/gallery.html @@ -0,0 +1,98 @@ + + + + + + Pixibot Photo Console + + + +
+
+
+
SP
+
+
AI Photographer
+
Pixibot Photo Console
+
+
+
+ + + + +
+
+ +
+
Photos folder: {{PHOTOS_DIR}}
+
Dashboard and camera controls stay live across mode switches.
+
+ +
+
+
+
+ + +
+
+ + + + + + + + diff --git a/Web/gallery.js b/Web/gallery.js new file mode 100644 index 0000000..02edac8 --- /dev/null +++ b/Web/gallery.js @@ -0,0 +1,1654 @@ +window.__previewEnabled = false; +window.__dashboardPoll = null; +window.__cameraSourcesCache = null; +window.__runtimeMode = "manual"; +window.__peoplePollCounter = 0; +window.__audioPromptLibrary = []; + +const RESOLUTION_PRESETS = [ + [1920, 1080, 30], + [1920, 1080, 15], + [1280, 720, 30], + [1280, 720, 15], + [960, 540, 30], + [960, 540, 15], + [848, 480, 60], + [848, 480, 30], + [640, 480, 60], + [640, 480, 30], + [640, 480, 15], + [424, 240, 60], + [424, 240, 30], +]; + +async function apiGet(path) { + const response = await fetch(path); + const raw = await response.text(); + let data = null; + try { + data = raw ? JSON.parse(raw) : null; + } catch (_e) { + if (!response.ok) { + throw new Error(raw || `HTTP ${response.status}`); + } + return raw; + } + if (!response.ok) { + throw new Error((data && (data.error || data.result)) || raw || `HTTP ${response.status}`); + } + return data; +} + +async function apiPostFormData(path, formData) { + const response = await fetch(path, { method: "POST", body: formData }); + const raw = await response.text(); + let data = null; + try { + data = raw ? JSON.parse(raw) : null; + } catch (_e) { + if (!response.ok) { + throw new Error(raw || `HTTP ${response.status}`); + } + return raw; + } + if (!response.ok) { + throw new Error((data && (data.error || data.result)) || raw || `HTTP ${response.status}`); + } + return data; +} + +async function apiPostJson(path, payload) { + const response = await fetch(path, { + method: "POST", + headers: { "Content-Type": "application/json" }, + body: JSON.stringify(payload || {}), + }); + const raw = await response.text(); + let data = null; + try { + data = raw ? JSON.parse(raw) : null; + } catch (_e) { + if (!response.ok) { + throw new Error(raw || `HTTP ${response.status}`); + } + return raw; + } + if (!response.ok) { + throw new Error((data && (data.error || data.result)) || raw || `HTTP ${response.status}`); + } + return data; +} + +function el(tag, cls, html) { + const node = document.createElement(tag); + if (cls) node.className = cls; + if (html !== undefined) node.innerHTML = html; + return node; +} + +function escapeHtml(text) { + return String(text || "") + .replace(/&/g, "&") + .replace(//g, ">") + .replace(/"/g, """) + .replace(/'/g, "'"); +} + +function formatSize(n) { + if (n < 1024) return `${n} B`; + if (n < 1024 * 1024) return `${(n / 1024).toFixed(1)} KB`; + return `${(n / (1024 * 1024)).toFixed(1)} MB`; +} + +function fmtNum(v, digits = 2) { + const n = Number(v); + if (Number.isNaN(n)) return "-"; + return n.toFixed(digits); +} + +function formatTime(ts) { + const n = Number(ts); + if (!Number.isFinite(n) || n <= 0) return "-"; + try { + return new Date(n * 1000).toLocaleString(); + } catch (_e) { + return "-"; + } +} + +function cameraStatusLines(camera) { + return [ + `Camera OK`, + `Source: ${camera.source || "-"}`, + `Backend: ${camera.backend || "-"}`, + `Active: ${camera.profile || "-"}`, + `Requested: ${camera.requested_profile || "-"}`, + `Preferred RS Serial: ${camera.preferred_realsense_serial || "-"}`, + `Active RS Serial: ${camera.realsense_serial || "-"}`, + ].join("\n"); +} + +function setPreviewEnabled(enabled) { + window.__previewEnabled = !!enabled; + const btn = document.getElementById("toggle_preview"); + const img = document.getElementById("live_preview"); + const placeholder = document.getElementById("preview_placeholder"); + const hint = document.getElementById("preview_hint"); + if (btn) btn.textContent = window.__previewEnabled ? "Hide Live Camera" : "Show Live Camera"; + if (!img) return; + if (window.__previewEnabled) { + img.style.display = "block"; + img.src = `/preview.mjpg?t=${Date.now()}`; + if (placeholder) placeholder.style.display = "none"; + if (hint) hint.textContent = "Live preview is running through the shared direct camera service."; + } else { + img.removeAttribute("src"); + img.src = ""; + img.style.display = "none"; + if (placeholder) placeholder.style.display = "grid"; + if (hint) hint.textContent = "Live preview is off. Turn it on only when needed."; + } +} + +function restartPreview() { + if (!window.__previewEnabled) return; + const img = document.getElementById("live_preview"); + if (!img) return; + img.src = `/preview.mjpg?t=${Date.now()}`; +} + +function setResolutionInputs(width, height, fps) { + const widthInput = document.getElementById("width_input"); + const heightInput = document.getElementById("height_input"); + const fpsInput = document.getElementById("fps_input"); + const presetSelect = document.getElementById("resolution_select"); + if (widthInput) widthInput.value = String(width || ""); + if (heightInput) heightInput.value = String(height || ""); + if (fpsInput) fpsInput.value = String(fps || ""); + if (presetSelect) { + const preset = `${width}x${height}@${fps}`; + const hasPreset = Array.from(presetSelect.options).some((opt) => opt.value === preset); + presetSelect.value = hasPreset ? preset : ""; + } +} + +function renderResolutionOptions() { + return [ + '', + ...RESOLUTION_PRESETS.map(([w, h, fps]) => ``), + ].join(""); +} + +function renderSourceOptions(cameraSources) { + const options = (cameraSources && cameraSources.options) || []; + if (!options.length) { + return ''; + } + return options + .map((item) => ``) + .join(""); +} + +function renderCameraInventory(cameraSources, camera) { + const lines = []; + const preferred = String((cameraSources && cameraSources.preferred_realsense_serial) || (camera && camera.preferred_realsense_serial) || "").trim(); + const active = String((camera && camera.realsense_serial) || "").trim(); + const activeSource = String((camera && camera.source) || "").trim(); + + if (preferred) { + lines.push(`Preferred RealSense: ${preferred}`); + } + if (active) { + lines.push(`Active RealSense: ${active}`); + } + + const rsDevices = (cameraSources && cameraSources.realsense_devices) || []; + if (rsDevices.length) { + lines.push("RealSense devices:"); + for (const item of rsDevices) { + const serial = String(item.serial || "").trim() || "-"; + const name = String(item.name || "Intel RealSense").trim(); + const tags = []; + if (item.is_preferred) tags.push("default"); + if (item.is_active) tags.push("live"); + lines.push(`- ${name} [${serial}]${tags.length ? ` (${tags.join(", ")})` : ""}`); + } + } + + const videoDevices = (cameraSources && cameraSources.video_devices) || []; + if (videoDevices.length) { + lines.push("Video nodes:"); + for (const item of videoDevices) { + const name = String(item.name || "").trim(); + const label = String(item.value || item.label || "").trim(); + const suffix = label === activeSource ? " (live)" : ""; + lines.push(`- ${label}${name ? ` :: ${name}` : ""}${suffix}`); + } + } + + return lines.join("\n") || "No camera inventory available."; +} + +function personImageUrl(personId, kind) { + return `/api/person_image?id=${encodeURIComponent(personId)}&kind=${encodeURIComponent(kind)}&t=${Date.now()}`; +} + +function renderPeopleCards(items) { + if (!items.length) { + return '
No people enrolled yet.
'; + } + return items.map((person) => { + const personId = String(person.person_id || ""); + const title = escapeHtml(person.display_name || person.short_id || personId || "guest"); + const meta = [ + `ID: ${escapeHtml(person.short_id || personId || "-")}`, + `Created: ${escapeHtml(person.created_date || "-")}`, + `Seen: ${person.times_seen ?? 0}`, + `Samples: ${person.sample_count ?? 0}`, + `Last Seen: ${escapeHtml(formatTime(person.last_seen_at || 0))}`, + ].join("\n"); + return ` +
+
+ ${title} face + ${title} scene +
+
+
${title}
+
${meta}
+
+ Download + + +
+
+
+ `; + }).join(""); +} + +function selectedCameraSerial(source, cameraSources, camera) { + const src = String(source || "").trim(); + if (src.startsWith("realsense:")) { + return src.split(":", 2)[1] || ""; + } + if (src === "realsense") { + return String((camera && camera.realsense_serial) || (cameraSources && cameraSources.preferred_realsense_serial) || "").trim(); + } + const devices = (cameraSources && cameraSources.realsense_devices) || []; + const exact = devices.find((item) => item.value === src); + return String((exact && exact.serial) || "").trim(); +} + +function formatPromptKeyLabel(key) { + return String(key || "") + .split("_") + .filter(Boolean) + .map((part) => part.charAt(0).toUpperCase() + part.slice(1)) + .join(" "); +} + +function promptFilenameForKey(key) { + const item = (window.__audioPromptLibrary || []).find((entry) => entry.key === key); + return item ? String(item.filename || `${key}.wav`) : `${key}.wav`; +} + +function promptTextForKey(key) { + const item = (window.__audioPromptLibrary || []).find((entry) => entry.key === key); + return item ? String(item.text || "") : ""; +} + +function populateAudioPromptRecorder(prompts) { + window.__audioPromptLibrary = Array.isArray(prompts) ? prompts.slice() : []; + const keySelect = document.getElementById("audio_prompt_record_key"); + const filenameInput = document.getElementById("audio_prompt_record_filename"); + const textArea = document.getElementById("audio_prompt_record_text"); + if (!keySelect || !filenameInput || !textArea) return; + + const previousKey = keySelect.value; + keySelect.innerHTML = (window.__audioPromptLibrary || []) + .map((item) => ``) + .join(""); + if (previousKey && (window.__audioPromptLibrary || []).some((item) => item.key === previousKey)) { + keySelect.value = previousKey; + } + const activeKey = keySelect.value || ((window.__audioPromptLibrary[0] && window.__audioPromptLibrary[0].key) || ""); + if (activeKey) { + keySelect.value = activeKey; + if (!filenameInput.value || filenameInput.dataset.autofill !== "0") { + filenameInput.value = promptFilenameForKey(activeKey); + filenameInput.dataset.autofill = "1"; + } + if (!textArea.value || textArea.dataset.autofill !== "0") { + textArea.value = promptTextForKey(activeKey); + textArea.dataset.autofill = "1"; + } + } +} + +async function refreshAudioPromptRecordStatus() { + const status = document.getElementById("audio_prompt_record_status_box"); + if (!status) return; + try { + const res = await apiGet("/api/audio_prompt_record_status"); + const s = res.status || {}; + if (s.running) { + status.textContent = [ + `Recording prompt: ${s.key || "-"}`, + `Filename: ${s.filename || "-"}`, + `Started: ${formatTime(s.started_at || 0)}`, + "Status: generating Gemini audio and recording speaker output...", + ].join("\n"); + return; + } + if (s.finished_at) { + if (s.ok) { + const result = s.result || {}; + status.textContent = [ + `Recorded prompt: ${result.key || s.key || "-"}`, + `Saved speaker file: ${result.filename || s.filename || "-"}`, + `Saved raw file: ${result.raw_filename || "-"}`, + `Finished: ${formatTime(s.finished_at || 0)}`, + ].join("\n"); + } else { + status.textContent = [ + `Prompt recording failed for ${s.key || "-"}`, + `Finished: ${formatTime(s.finished_at || 0)}`, + `${s.error || "Unknown error"}`, + ].join("\n"); + } + return; + } + status.textContent = "Prompt recorder idle."; + } catch (e) { + status.textContent = `Prompt recorder unavailable\n${e.message}`; + } +} + +function renderAudioPromptCards(items) { + if (!items.length) { + return '
No audio prompt keys available.
'; + } + return items.map((item) => { + const exists = !!item.exists; + const key = String(item.key || ""); + const filename = String(item.filename || ""); + return ` +
+
+
+
${escapeHtml(formatPromptKeyLabel(key))}
+
${escapeHtml(key)}
+
+
+ ${exists ? "uploaded" : "missing"} +
+
+
${escapeHtml(item.text || "")}
+
+ File: ${escapeHtml(filename || "-")}
+ Size: ${formatSize(item.size || 0)}
+ Raw: ${item.raw_exists ? escapeHtml(item.raw_filename || "-") : "missing"}
+ Updated: ${formatTime(item.mtime || 0)} +
+
+ + + ${exists ? `Download` : ""} + +
+
+ `; + }).join(""); +} + +async function refreshAudioPromptPanel() { + const list = document.getElementById("audio_prompt_list"); + const status = document.getElementById("audio_prompt_status_box"); + const modeToggle = document.getElementById("audio_prompt_mode_toggle"); + const toggle = document.getElementById("audio_prompt_fallback_toggle"); + const fileInput = document.getElementById("audio_prompt_upload_file"); + if (!list || !status || !toggle || !fileInput || !modeToggle) return; + try { + const res = await apiGet("/api/audio_prompts"); + const prompts = res.prompts || []; + const promptMode = String(res.mode || "audio").trim().toLowerCase() === "gemini" ? "gemini" : "audio"; + const fallbackToGemini = !!res.fallback_to_gemini; + const available = prompts.filter((item) => item.exists).length; + modeToggle.dataset.mode = promptMode; + modeToggle.textContent = promptMode === "gemini" ? "Situation Speech: GEMINI" : "Situation Speech: AUDIO"; + toggle.dataset.enabled = fallbackToGemini ? "1" : "0"; + toggle.textContent = fallbackToGemini ? "Gemini Fallback: ON" : "Gemini Fallback: OFF"; + populateAudioPromptRecorder(prompts); + status.textContent = [ + `Prompt folder: ${res.dir || "AI_Photographer/Data/Audio"}`, + `Available clips: ${available} / ${prompts.length}`, + `Fixed AI situation speech: ${promptMode.toUpperCase()}`, + `Missing-clip Gemini fallback: ${fallbackToGemini ? "ON" : "OFF"}`, + promptMode === "audio" + ? "Recorded audio is the default for AI situations such as greeting on detection, photo request, countdown, refusal, retake, and thank-you. After those fixed prompts finish, normal Gemini conversation continues." + : "Gemini is currently speaking the fixed AI situation prompts directly. General Gemini conversation remains available before and after the photo flow." + ].join("\n"); + list.innerHTML = renderAudioPromptCards(prompts); + + list.querySelectorAll(".audio-prompt-upload").forEach((btn) => { + btn.addEventListener("click", () => { + fileInput.dataset.key = btn.dataset.key || ""; + fileInput.dataset.filename = btn.dataset.filename || ""; + fileInput.click(); + }); + }); + list.querySelectorAll(".audio-prompt-record").forEach((btn) => { + btn.addEventListener("click", () => { + const key = btn.dataset.key || ""; + const keySelect = document.getElementById("audio_prompt_record_key"); + const filenameInput = document.getElementById("audio_prompt_record_filename"); + const textArea = document.getElementById("audio_prompt_record_text"); + if (keySelect) keySelect.value = key; + if (filenameInput) { + filenameInput.value = promptFilenameForKey(key); + filenameInput.dataset.autofill = "1"; + } + if (textArea) { + textArea.value = promptTextForKey(key); + textArea.dataset.autofill = "1"; + textArea.focus(); + } + }); + }); + list.querySelectorAll(".audio-prompt-delete").forEach((btn) => { + btn.addEventListener("click", async () => { + const key = btn.dataset.key || ""; + if (!key) return; + if (!confirm(`Delete audio prompt clip for ${key}?`)) return; + await apiGet(`/api/delete_audio_prompt?key=${encodeURIComponent(key)}`); + await refreshAudioPromptPanel(); + await refreshAudioPromptRecordStatus(); + }); + }); + } catch (e) { + status.textContent = `Audio prompt library unavailable\n${e.message}`; + list.innerHTML = ""; + toggle.textContent = "Gemini Fallback"; + delete toggle.dataset.enabled; + } +} + +function bindTopActions() { + const topStatus = document.getElementById("top_status"); + const topCapture = document.getElementById("top_capture"); + const topTest = document.getElementById("top_test"); + const topFix = document.getElementById("top_fix"); + + if (topStatus) { + topStatus.onclick = () => window.open("/api/status", "_blank", "noopener"); + } + if (topCapture) { + topCapture.onclick = async () => { + try { + const res = await apiGet("/api/capture"); + alert(`Captured:\n${res.result || res.path || "OK"}`); + await renderPhotos(); + } catch (e) { + alert(`Capture failed: ${e.message}`); + } + }; + } + if (topTest) { + topTest.onclick = async () => { + try { + const res = await apiGet("/api/test"); + alert(JSON.stringify(res, null, 2)); + } catch (e) { + alert(`Camera test failed: ${e.message}`); + } + }; + } + if (topFix) { + topFix.onclick = async () => { + if (!confirm("Run the camera fix flow?")) return; + try { + const res = await apiGet("/api/fix"); + alert(JSON.stringify(res, null, 2)); + } catch (e) { + alert(`Fix failed: ${e.message}`); + } + }; + } +} + +async function refreshAutonomousPanel() { + const panel = document.getElementById("auto_state_panel"); + if (!panel) return; + try { + const r = await apiGet("/api/autonomous_state"); + if (!r.ok) { + panel.innerHTML = "Autonomous state unavailable"; + return; + } + const s = r.state || {}; + panel.innerHTML = ` +
+
State${escapeHtml(s.state || "IDLE")}
+
Session${s.session_id ?? 0}
+
Detector${escapeHtml((s.detector_backend || "normal").toUpperCase())}
+
YOLO Runtime${escapeHtml((s.yolo_runtime || "-").toUpperCase())}
+
AI Blocked${s.ai_blocked ? "Yes" : "No"}
+
Block Reason${escapeHtml(s.ai_block_reason || "-")}
+
People${s.person_count ?? 0}
+
Faces${s.face_count ?? 0}
+
Group${s.group_detected ? `Yes (${s.group_size ?? 0})` : "No"}
+
Intent${s.intent_detected ? "Yes" : "No"}
+
Depth${s.depth_m == null ? "-" : fmtNum(s.depth_m, 2)}
+
Approach${fmtNum(s.approach_speed_mps || 0, 2)} m/s
+
Guest${escapeHtml(s.recognized_person_label || "-")}
+
Known Guest${s.recognized_person_known ? "Yes" : "No"}
+
Match${s.recognized_person_match_score ? fmtNum(s.recognized_person_match_score, 2) : "-"}
+
+ `; + } catch (_e) { + panel.innerHTML = "Autonomous state unavailable"; + } +} + +async function refreshAiReadinessPanel() { + const panel = document.getElementById("ai_readiness_panel"); + if (!panel) return; + try { + const data = await apiGet("/api/ai_readiness"); + panel.innerHTML = ` +
+
Ready${data.ok ? "Yes" : "No"}
+
Backend${escapeHtml((data.backend || "normal").toUpperCase())}
+
Runtime${escapeHtml((data.yolo_runtime || "-").toUpperCase())}
+
YOLO Loaded${data.yolo_loaded ? "Yes" : "No"}
+
Person Model${data.person_model_ok ? "Yes" : "No"}
+
Face Model${data.face_model_ok ? "Yes" : "No"}
+
Strict Required${data.strict_required ? "Yes" : "No"}
+
Block Reason${escapeHtml(data.block_reason || "-")}
+
+ `; + } catch (_e) { + panel.innerHTML = "AI readiness unavailable"; + } +} + +async function refreshRuntimeHealthPanel() { + const panel = document.getElementById("runtime_health_panel"); + if (!panel) return; + try { + const r = await apiGet("/api/runtime_health"); + if (!r.ok) { + panel.innerHTML = "Runtime health unavailable"; + return; + } + const h = r.health || {}; + panel.innerHTML = ` +
+
WS${h.ws_connected ? "Connected" : "Down"}
+
WS State${escapeHtml(h.ws_state || "-")}
+
Mic Enabled${h.mic_enabled ? "Yes" : "No"}
+
Mic${escapeHtml(h.mic_state || "-")}
+
Speaker${escapeHtml(h.speaker_state || "-")}
+
Gate${h.audio_gate_open ? "Open" : "Closed"}
+
Mic Restarts${h.mic_restarts ?? 0}
+
Speaker Restarts${h.speaker_restarts ?? 0}
+
WS Restarts${h.ws_restarts ?? 0}
+
Last WS Error${escapeHtml(h.ws_last_error || "-")}
+
+ `; + } catch (_e) { + panel.innerHTML = "Runtime health unavailable"; + } +} + +async function renderPeople() { + const list = document.getElementById("people_list"); + const status = document.getElementById("people_status_box"); + if (!list || !status) return; + try { + const res = await apiGet("/api/people"); + const people = res.people || []; + status.textContent = people.length + ? `Registered guests: ${people.length}\nReturning guests are recognized from saved face samples in photos/people/.` + : "No people enrolled yet. AI mode will create a guest profile the first time a single face is confirmed."; + list.innerHTML = renderPeopleCards(people); + list.querySelectorAll(".person-delete").forEach((btn) => { + btn.addEventListener("click", async () => { + const personId = btn.dataset.id || ""; + if (!personId) return; + if (!confirm(`Delete person ${personId}?`)) return; + await apiGet(`/api/delete_person?id=${encodeURIComponent(personId)}`); + await renderPeople(); + }); + }); + list.querySelectorAll(".person-add-photo").forEach((btn) => { + btn.addEventListener("click", () => { + const personId = btn.dataset.id || ""; + const input = document.getElementById("people_upload_file"); + if (!input) return; + input.dataset.personId = personId; + input.click(); + }); + }); + } catch (e) { + status.textContent = `People registry unavailable\n${e.message}`; + list.innerHTML = ""; + } +} + +async function refreshCameraPanel() { + const statusBox = document.getElementById("camera_status_box"); + const infoPanel = document.getElementById("camera_info_panel"); + const chipRow = document.getElementById("camera_chip_row"); + const selector = document.getElementById("camera_source_select"); + const sourceMeta = document.getElementById("camera_source_meta"); + const inventoryBox = document.getElementById("camera_inventory_box"); + if (!statusBox || !infoPanel || !chipRow) return; + + try { + const [health, cameraSources] = await Promise.all([ + apiGet("/api/camera_health"), + selector && !window.__cameraSourcesCache ? apiGet("/api/camera_sources") : Promise.resolve(window.__cameraSourcesCache || null), + ]); + + if (cameraSources && cameraSources.ok) { + window.__cameraSourcesCache = cameraSources; + if (selector) { + const currentValue = selector.dataset.initialized === "1" + ? (selector.value || cameraSources.selected_source || "realsense") + : (cameraSources.selected_source || "realsense"); + selector.innerHTML = renderSourceOptions(cameraSources); + selector.value = currentValue; + if (!selector.value) selector.value = cameraSources.selected_source || "realsense"; + selector.dataset.initialized = "1"; + } + if (sourceMeta) { + const rsCount = (cameraSources.realsense_devices || []).length; + const vidCount = (cameraSources.video_devices || []).length; + const activeLabel = (cameraSources.active_device && cameraSources.active_device.label) || cameraSources.active_source || "-"; + sourceMeta.textContent = `Preferred RS: ${cameraSources.preferred_realsense_serial || "-"} | Active: ${activeLabel} | RealSense devices: ${rsCount} | Video nodes: ${vidCount}`; + } + } + + const camera = (health && health.camera) || {}; + statusBox.textContent = camera.ok ? cameraStatusLines(camera) : `Camera not ready\nSource: ${camera.source || "-"}\nRequested: ${camera.requested_profile || "-"}\nError: ${camera.last_error || "-"}`; + chipRow.innerHTML = ` +
Requested${escapeHtml(camera.requested_source || camera.source || "-")}
+
Backend${escapeHtml(camera.backend || "-")}
+
Active Profile${escapeHtml(camera.profile || "-")}
+
Frame Time${escapeHtml(formatTime(camera.frame_time))}
+ `; + infoPanel.textContent = JSON.stringify(health, null, 2); + if (inventoryBox) { + inventoryBox.textContent = renderCameraInventory(cameraSources, camera); + } + + const widthInput = document.getElementById("width_input"); + if (widthInput && widthInput.dataset.initialized !== "1") { + setResolutionInputs(camera.requested_width, camera.requested_height, camera.requested_fps); + widthInput.dataset.initialized = "1"; + } + } catch (e) { + statusBox.textContent = `Camera service unavailable\n${e.message}`; + infoPanel.textContent = JSON.stringify({ ok: false, error: e.message }, null, 2); + chipRow.innerHTML = ""; + if (inventoryBox) inventoryBox.textContent = "Camera inventory unavailable."; + } +} + +function renderReplayList(items, opts = {}) { + const manualMode = !!opts.manualMode; + const testRunning = !!opts.testRunning; + if (!items.length) { + return '
No replay files found.
'; + } + return items.map((item) => { + const tags = []; + if (item.active) tags.push('active'); + if (item.greeting) tags.push('greeting'); + if (!item.trigger_ok) tags.push('triggerless'); + return ` +
+
+
${escapeHtml(item.name)}
+
${formatSize(item.size || 0)} ยท ${formatTime(item.mtime || 0)}
+
+
${tags.join("")}
+
+ + + + Download + +
+
+ `; + }).join(""); +} + +function renderReplayRecordStatus(status) { + if (!status || !status.started_at) { + return "Recorder idle."; + } + if (status.running) { + return `Recording ${status.name || "-"} for ${status.seconds || 0}s...\nOutput: ${status.output || "-"}`; + } + if (status.ok) { + return `Recording saved\n${status.output || "-"}\nFinished: ${formatTime(status.finished_at || 0)}`; + } + return `Recorder error\n${status.error || "-"}${(status.output ? `\nOutput: ${status.output}` : "")}`; +} + +function renderReplayTestStatus(status) { + if (!status || !status.started_at) { + return "Replay test idle."; + } + if (status.running) { + return `Testing replay\n${status.name || "-"}`; + } + if (status.ok) { + return `Replay test complete\n${status.result || status.name || "-"}`; + } + return `Replay test error\n${status.error || "-"}`; +} + +async function refreshReplayPanel() { + const selector = document.getElementById("replay_select"); + const activeNote = document.getElementById("replay_active_note"); + const list = document.getElementById("replay_manager_list"); + const status = document.getElementById("replay_record_status"); + const testStatus = document.getElementById("replay_test_status"); + const greetingSelect = document.getElementById("opt_greeting_replay_file"); + try { + const [replayResp, activeResp, recordResp, testResp] = await Promise.all([ + apiGet("/api/replays"), + apiGet("/api/get_replay"), + apiGet("/api/replay_record_status").catch(() => ({ ok: false, status: {} })), + apiGet("/api/replay_test_status").catch(() => ({ ok: false, status: {} })), + ]); + const items = replayResp.items || []; + const activeReplay = activeResp.replay || ""; + const replayTest = testResp.status || {}; + const manualMode = window.__runtimeMode === "manual"; + + if (selector) { + selector.innerHTML = items.map((item) => ``).join(""); + selector.value = activeReplay || (items[0] && items[0].name) || ""; + } + if (activeNote) { + activeNote.textContent = activeReplay + ? `Active replay: ${activeReplay}. Manual R2+X and AI photo capture use this replay when AI capture replay is enabled. Replay recording and replay test are manual-mode only.` + : "No active replay selected."; + } + if (list) { + list.innerHTML = renderReplayList(items, { manualMode, testRunning: !!replayTest.running }); + list.querySelectorAll(".replay-test").forEach((btn) => { + btn.addEventListener("click", async () => { + const name = btn.dataset.name || ""; + await apiGet(`/api/test_replay?name=${encodeURIComponent(name)}`); + await refreshReplayPanel(); + }); + }); + list.querySelectorAll(".replay-use").forEach((btn) => { + btn.addEventListener("click", async () => { + await apiGet(`/api/set_replay?name=${encodeURIComponent(btn.dataset.name || "")}`); + await refreshReplayPanel(); + }); + }); + list.querySelectorAll(".replay-rename").forEach((btn) => { + btn.addEventListener("click", async () => { + const oldName = btn.dataset.name || ""; + const currentLeaf = oldName.split("/").pop() || oldName; + const nextName = window.prompt("Rename replay", currentLeaf); + if (!nextName || !nextName.trim()) return; + await apiGet( + `/api/rename_replay?old=${encodeURIComponent(oldName)}&new=${encodeURIComponent(nextName.trim())}` + ); + await refreshReplayPanel(); + }); + }); + list.querySelectorAll(".replay-delete").forEach((btn) => { + btn.addEventListener("click", async () => { + const name = btn.dataset.name || ""; + if (!confirm(`Delete replay ${name}?`)) return; + await apiGet(`/api/delete_replay?name=${encodeURIComponent(name)}`); + await refreshReplayPanel(); + }); + }); + } + if (status) { + status.textContent = renderReplayRecordStatus(recordResp.status || {}); + } + if (testStatus) { + testStatus.textContent = renderReplayTestStatus(replayTest); + } + if (greetingSelect) { + const current = greetingSelect.dataset.current || greetingSelect.value; + greetingSelect.innerHTML = items.map((item) => ``).join(""); + if (current) greetingSelect.value = current; + if (!greetingSelect.value && items.length) greetingSelect.value = items[0].name; + delete greetingSelect.dataset.current; + } + } catch (e) { + if (activeNote) activeNote.textContent = `Replay inventory unavailable: ${e.message}`; + if (list) list.innerHTML = ""; + if (status) status.textContent = `Recorder unavailable\n${e.message}`; + if (testStatus) testStatus.textContent = `Replay test unavailable\n${e.message}`; + } +} + +async function renderControls() { + const ctrl = document.getElementById("controls"); + const [modeResp, micResp, cameraSources] = await Promise.all([ + apiGet("/api/mode"), + apiGet("/api/mic"), + apiGet("/api/camera_sources").catch(() => ({ ok: false, options: [] })), + ]); + + window.__cameraSourcesCache = cameraSources && cameraSources.ok ? cameraSources : null; + + const mode = modeResp.mode || "manual"; + window.__runtimeMode = mode; + const modePolicy = modeResp.policy || {}; + const micEnabled = !!(micResp.options && micResp.options.mic_enabled); + + let backend = "normal"; + let strictLocked = false; + let aiOptions = { + hard_target_lock_enabled: true, + retake_prompt_enabled: true, + autonomous_greeting_replay_enabled: true, + autonomous_greeting_replay_file: "right_hand_up.jsonl", + autonomous_capture_replay_enabled: true, + face_recognition_enabled: true, + face_recognition_threshold: 0.88, + active_replay: "photo_G3.jsonl", + }; + let aiReadinessMarkup = ""; + let aiOptionsMarkup = ""; + if (mode === "ai") { + try { + const bj = await apiGet("/api/detector_backend"); + backend = bj.backend || "normal"; + strictLocked = !!bj.locked; + } catch (_e) {} + + try { + const oj = await apiGet("/api/ai_options"); + if (oj && oj.ok && oj.options) aiOptions = oj.options; + } catch (_e) {} + + aiReadinessMarkup = ` +
+
+
+
AI Vision
+

Detection Backend

+
+
+
+ + +
+ ${strictLocked ? '
Strict AI profile active: backend is locked to YOLO in AI mode.
' : ""} +
Loading AI readiness...
+
+ `; + + aiOptionsMarkup = ` +
+
+
+
AI Session
+

Session Options

+
+
+
+ + + + + +
+
+ + + +
+
AI welcomes approaching guests, asks if they want a photo, guides them into frame, and captures using the active replay when enabled. Returning-guest recognition stores samples in photos/people/. Active replay: ${escapeHtml(aiOptions.active_replay || "-")}.
+
+ `; + } + + const recorderMarkup = mode === "manual" + ? ` +
+
+
+
Recorder
+

Record New Replay

+
+
+
+ + + +
+
Recorded files are saved directly in Data/G1 and become available in the active replay selector.
+
Recorder idle.
+
+ ` + : ` +
+
+
+
Recorder
+

Manual Mode Only

+
+
+
Replay recording and replay test are disabled outside manual mode. Replay selection, rename, upload, download, and delete remain available.
+
Recorder idle.
+
+ `; + + ctrl.innerHTML = ` +
+
+
+
+
+
Runtime Mode
+

${escapeHtml(mode.toUpperCase())}

+
+
+
+ + +
+
${escapeHtml(modePolicy.description || "")}
+
+ +
+
+
+
Gemini Mic
+

${micEnabled ? "Microphone ON" : "Microphone OFF"}

+
+
+
+ +
+
Microphone audio can stay on in both modes. Manual mode still disables mapped photo commands and AI detection.
+
+
+ +
+
+
+
Camera Console
+

Live Camera

+
+
+
+
+
+
Live preview is off.
Use the toggle below when you need a live camera feed.
+ live preview +
+
+ + + +
+
Live preview is off. Turn it on only when needed.
+
+
Loading camera status...
+
+
+
+ + + +
+
Loading available camera sources...
+ 
Loading camera inventory...
+
+ + + + + +
+
Use a preset or enter width, height, and fps manually. The direct camera service will reopen with the requested settings.
+ 
Checking camera...
+
+
+
+ +
+
+
+
+
Replay
+

Capture Motion

+
+
+
+ + +
+
Loading replay status...
+
+ + ${recorderMarkup} +
+ +
+
+
+
Replay Files
+

Replay Inventory

+
+
+
+ + +
+
Replay test idle.
+
+
+ +
+
+
+
AI Voice Assets
+

Audio Prompt Library

+
+
+ + +
+
+
Upload prerecorded WAV clips for fixed AI situation prompts. In audio mode, AI detection, confirmation, countdown, retake, and thank-you situations use these clips first. Gemini can be switched back on for those same situations from the dashboard.
+
Loading audio prompt library...
+
+
+ + + +
+ +
Prompt recorder idle.
+
+ +
+
+ +
+
+
+
Actions
+

Operator Actions

+
+
+
+ + + + + + +
+
+ + ${aiReadinessMarkup} + ${aiOptionsMarkup} + +
+
+
+
+
AI State
+

Autonomous State

+
+
+
Loading...
+
+ +
+
+
+
Runtime
+

Runtime Health

+
+
+
Loading...
+
+
+
+ `; + + if (mode === "ai") { + setTimeout(() => { + const bSel = document.getElementById("det_backend_select"); + const bBtn = document.getElementById("det_backend_set"); + if (bSel) { + bSel.value = backend; + if (strictLocked) { + bSel.disabled = true; + bSel.value = "yolo"; + } + } + if (bBtn && strictLocked) { + bBtn.disabled = true; + } + const greetingSel = document.getElementById("opt_greeting_replay_file"); + if (greetingSel) { + greetingSel.dataset.current = aiOptions.autonomous_greeting_replay_file || ""; + } + }, 0); + } + + document.getElementById("mode_select").value = mode; + + document.getElementById("mode_set").addEventListener("click", async () => { + const sel = document.getElementById("mode_select").value; + await apiGet(`/api/set_mode?mode=${encodeURIComponent(sel)}`); + await renderControls(); + await renderPhotos(); + }); + + document.getElementById("mic_toggle").addEventListener("click", async () => { + const nextEnabled = micEnabled ? 0 : 1; + await apiGet(`/api/set_mic?enabled=${nextEnabled}`); + await renderControls(); + }); + + const replaySet = document.getElementById("replay_set"); + if (replaySet) { + replaySet.addEventListener("click", async () => { + const name = encodeURIComponent(document.getElementById("replay_select").value); + await apiGet(`/api/set_replay?name=${name}`); + await refreshReplayPanel(); + }); + } + + const replayRecordStart = document.getElementById("replay_record_start"); + if (replayRecordStart) { + replayRecordStart.addEventListener("click", async () => { + const name = (document.getElementById("replay_record_name").value || "").trim(); + const seconds = Number(document.getElementById("replay_record_seconds").value || "15"); + if (!name) { + alert("Enter a replay file name first."); + return; + } + await apiGet(`/api/replay_record_start?name=${encodeURIComponent(name)}&seconds=${encodeURIComponent(seconds)}`); + await refreshReplayPanel(); + }); + } + + const replayUploadBtn = document.getElementById("replay_upload_btn"); + const replayUploadFile = document.getElementById("replay_upload_file"); + if (replayUploadBtn && replayUploadFile) { + replayUploadBtn.addEventListener("click", () => replayUploadFile.click()); + replayUploadFile.addEventListener("change", async () => { + const file = replayUploadFile.files && replayUploadFile.files[0]; + if (!file) return; + const requestedName = window.prompt("Replay name", file.name) || file.name; + const form = new FormData(); + form.append("file", file, file.name); + form.append("name", requestedName); + try { + await apiPostFormData("/api/upload_replay", form); + await refreshReplayPanel(); + } catch (e) { + alert(`Replay upload failed: ${e.message}`); + } finally { + replayUploadFile.value = ""; + } + }); + } + + const audioPromptUploadFile = document.getElementById("audio_prompt_upload_file"); + const audioPromptModeToggle = document.getElementById("audio_prompt_mode_toggle"); + const audioPromptFallbackToggle = document.getElementById("audio_prompt_fallback_toggle"); + const audioPromptRecordKey = document.getElementById("audio_prompt_record_key"); + const audioPromptRecordFilename = document.getElementById("audio_prompt_record_filename"); + const audioPromptRecordText = document.getElementById("audio_prompt_record_text"); + const audioPromptRecordStart = document.getElementById("audio_prompt_record_start"); + if (audioPromptUploadFile) { + audioPromptUploadFile.addEventListener("change", async () => { + const file = audioPromptUploadFile.files && audioPromptUploadFile.files[0]; + const key = audioPromptUploadFile.dataset.key || ""; + if (!file || !key) return; + const defaultName = audioPromptUploadFile.dataset.filename || `${key}.wav`; + const requestedName = window.prompt("Audio filename", defaultName) || defaultName; + const form = new FormData(); + form.append("key", key); + form.append("file", file, file.name); + form.append("filename", requestedName); + try { + await apiPostFormData("/api/upload_audio_prompt", form); + await refreshAudioPromptPanel(); + } catch (e) { + alert(`Audio prompt upload failed: ${e.message}`); + } finally { + audioPromptUploadFile.value = ""; + delete audioPromptUploadFile.dataset.key; + delete audioPromptUploadFile.dataset.filename; + } + }); + } + if (audioPromptModeToggle) { + audioPromptModeToggle.addEventListener("click", async () => { + const current = String(audioPromptModeToggle.dataset.mode || "audio").trim().toLowerCase(); + const next = current === "gemini" ? "audio" : "gemini"; + await apiGet(`/api/set_audio_prompt_mode?mode=${encodeURIComponent(next)}`); + await refreshAudioPromptPanel(); + }); + } + if (audioPromptFallbackToggle) { + audioPromptFallbackToggle.addEventListener("click", async () => { + const current = audioPromptFallbackToggle.dataset.enabled === "1"; + await apiGet(`/api/set_audio_prompt_fallback?enabled=${current ? 0 : 1}`); + await refreshAudioPromptPanel(); + }); + } + if (audioPromptRecordKey && audioPromptRecordFilename && audioPromptRecordText) { + audioPromptRecordKey.addEventListener("change", () => { + const key = audioPromptRecordKey.value || ""; + audioPromptRecordFilename.value = promptFilenameForKey(key); + audioPromptRecordFilename.dataset.autofill = "1"; + audioPromptRecordText.value = promptTextForKey(key); + audioPromptRecordText.dataset.autofill = "1"; + }); + audioPromptRecordFilename.addEventListener("input", () => { + audioPromptRecordFilename.dataset.autofill = "0"; + }); + audioPromptRecordText.addEventListener("input", () => { + audioPromptRecordText.dataset.autofill = "0"; + }); + } + if (audioPromptRecordStart && audioPromptRecordKey && audioPromptRecordFilename && audioPromptRecordText) { + audioPromptRecordStart.addEventListener("click", async () => { + const key = (audioPromptRecordKey.value || "").trim(); + const filename = (audioPromptRecordFilename.value || "").trim(); + const text = (audioPromptRecordText.value || "").trim(); + if (!key) { + alert("Select a prompt key first."); + return; + } + if (!text) { + alert("Prompt text is required."); + return; + } + try { + await apiPostJson("/api/audio_prompt_record", { key, filename, text }); + await refreshAudioPromptRecordStatus(); + } catch (e) { + alert(`Prompt recording failed: ${e.message}`); + } + }); + } + + const peopleUploadBtn = document.getElementById("people_upload_btn"); + const peopleUploadFile = document.getElementById("people_upload_file"); + const peopleResetBtn = document.getElementById("people_reset_btn"); + if (peopleUploadBtn && peopleUploadFile) { + peopleUploadBtn.addEventListener("click", () => { + peopleUploadFile.dataset.personId = ""; + peopleUploadFile.click(); + }); + peopleUploadFile.addEventListener("change", async () => { + const file = peopleUploadFile.files && peopleUploadFile.files[0]; + if (!file) return; + const form = new FormData(); + form.append("file", file, file.name); + if (peopleUploadFile.dataset.personId) { + form.append("person_id", peopleUploadFile.dataset.personId); + } + try { + await apiPostFormData("/api/upload_person", form); + await renderPeople(); + } catch (e) { + alert(`People upload failed: ${e.message}`); + } finally { + peopleUploadFile.value = ""; + delete peopleUploadFile.dataset.personId; + } + }); + } + if (peopleResetBtn) { + peopleResetBtn.addEventListener("click", async () => { + if (!confirm("Delete all saved people profiles?")) return; + await apiGet("/api/reset_people"); + await renderPeople(); + }); + } + + document.getElementById("req_photo").addEventListener("click", async () => { + await apiGet("/api/request_photo"); + }); + document.getElementById("clear_photos").addEventListener("click", async () => { + if (!confirm("Delete ALL photos?")) return; + await apiGet("/api/clear_photos"); + await renderPhotos(); + }); + document.getElementById("download_zip").addEventListener("click", async () => { + const r = await apiGet("/api/download_zip"); + if (r.ok) window.location = `/${r.archive}`; + }); + document.getElementById("upload_now").addEventListener("click", async () => { + await apiGet("/api/upload_now"); + }); + document.getElementById("scripts_fix_check").addEventListener("click", async () => { + const r = await apiGet("/api/run_scripts_fix?mode=--check"); + alert(`RealSense check:\n${(r.stdout || []).join("\n") || "true"}`); + }); + document.getElementById("scripts_fix_run").addEventListener("click", async () => { + if (!confirm("Run RealSense fix script?")) return; + const r = await apiGet("/api/run_scripts_fix?mode=--fix"); + alert(`Fix output:\n${(r.stdout || []).join("\n")}`); + }); + + document.getElementById("toggle_preview").addEventListener("click", () => { + setPreviewEnabled(!window.__previewEnabled); + }); + document.getElementById("camera_refresh_btn").addEventListener("click", async () => { + window.__cameraSourcesCache = null; + await refreshCameraPanel(); + restartPreview(); + }); + document.getElementById("capture_now_btn").addEventListener("click", async () => { + const statusBox = document.getElementById("camera_status_box"); + statusBox.textContent = "Capturing..."; + try { + const resp = await apiGet("/api/capture"); + statusBox.textContent = `Saved\n${resp.result || "OK"}`; + await renderPhotos(); + await refreshCameraPanel(); + } catch (e) { + statusBox.textContent = `Capture failed\n${e.message}`; + } + }); + document.getElementById("camera_apply_btn").addEventListener("click", async () => { + const selector = document.getElementById("camera_source_select"); + const statusBox = document.getElementById("camera_status_box"); + const source = selector.value; + statusBox.textContent = `Switching camera to ${source}...`; + try { + await apiGet(`/api/set_camera_source?source=${encodeURIComponent(source)}`); + restartPreview(); + await refreshCameraPanel(); + } catch (e) { + statusBox.textContent = `Camera switch failed\n${e.message}`; + } + }); + document.getElementById("camera_save_default_btn").addEventListener("click", async () => { + const selector = document.getElementById("camera_source_select"); + const statusBox = document.getElementById("camera_status_box"); + const camera = ((await apiGet("/api/camera_health")).camera) || {}; + const cameraSources = window.__cameraSourcesCache || await apiGet("/api/camera_sources"); + const serial = selectedCameraSerial(selector.value, cameraSources, camera); + if (!serial) { + statusBox.textContent = "Default camera save failed\nSelect a RealSense source first."; + return; + } + statusBox.textContent = `Saving preferred camera ${serial}...`; + try { + await apiGet(`/api/set_preferred_camera?serial=${encodeURIComponent(serial)}`); + window.__cameraSourcesCache = null; + await refreshCameraPanel(); + statusBox.textContent = `Preferred camera saved\n${serial}`; + } catch (e) { + statusBox.textContent = `Default camera save failed\n${e.message}`; + } + }); + document.getElementById("resolution_select").addEventListener("change", (e) => { + const value = e.target.value; + const match = value.match(/^(\d+)x(\d+)@(\d+)$/); + if (!match) return; + setResolutionInputs(Number(match[1]), Number(match[2]), Number(match[3])); + }); + document.getElementById("apply_resolution_btn").addEventListener("click", async () => { + const width = Number(document.getElementById("width_input").value); + const height = Number(document.getElementById("height_input").value); + const fps = Number(document.getElementById("fps_input").value); + const statusBox = document.getElementById("camera_status_box"); + statusBox.textContent = `Applying resolution ${width}x${height}@${fps}...`; + try { + const resp = await apiGet(`/api/set_camera_resolution?width=${encodeURIComponent(width)}&height=${encodeURIComponent(height)}&fps=${encodeURIComponent(fps)}`); + const camera = resp.camera || {}; + setResolutionInputs(camera.requested_width, camera.requested_height, camera.requested_fps); + restartPreview(); + await refreshCameraPanel(); + } catch (e) { + statusBox.textContent = `Resolution change failed\n${e.message}`; + } + }); + + if (mode === "ai") { + const backendButton = document.getElementById("det_backend_set"); + if (backendButton) { + backendButton.addEventListener("click", async () => { + const v = document.getElementById("det_backend_select").value || "normal"; + try { + await apiGet(`/api/set_detector_backend?backend=${encodeURIComponent(v)}`); + await renderControls(); + } catch (e) { + alert(e.message); + } + }); + } + const aiSave = document.getElementById("opt_ai_save"); + if (aiSave) { + aiSave.addEventListener("click", async () => { + const hard = document.getElementById("opt_hard_lock").checked ? 1 : 0; + const retake = document.getElementById("opt_retake_prompt").checked ? 1 : 0; + const greetEnabled = document.getElementById("opt_greeting_replay").checked ? 1 : 0; + const greetFile = document.getElementById("opt_greeting_replay_file").value || ""; + const captureReplay = document.getElementById("opt_capture_replay").checked ? 1 : 0; + const faceRecognition = document.getElementById("opt_face_recognition").checked ? 1 : 0; + const faceThreshold = document.getElementById("opt_face_threshold").value || "0.88"; + try { + await apiGet( + `/api/set_ai_options?hard_target_lock_enabled=${hard}&retake_prompt_enabled=${retake}` + + `&autonomous_greeting_replay_enabled=${greetEnabled}` + + `&autonomous_greeting_replay_file=${encodeURIComponent(greetFile)}` + + `&autonomous_capture_replay_enabled=${captureReplay}` + + `&face_recognition_enabled=${faceRecognition}` + + `&face_recognition_threshold=${encodeURIComponent(faceThreshold)}` + ); + await renderControls(); + } catch (e) { + alert(e.message); + } + }); + } + } + + setPreviewEnabled(window.__previewEnabled); + await refreshCameraPanel(); + await refreshReplayPanel(); + await refreshAudioPromptPanel(); + await refreshAudioPromptRecordStatus(); + await refreshAutonomousPanel(); + await refreshAiReadinessPanel(); + await refreshRuntimeHealthPanel(); + await renderPeople(); + + if (window.__dashboardPoll) clearInterval(window.__dashboardPoll); + window.__peoplePollCounter = 0; + window.__dashboardPoll = setInterval(async () => { + await refreshCameraPanel().catch(() => {}); + await refreshReplayPanel().catch(() => {}); + await refreshAutonomousPanel().catch(() => {}); + await refreshAiReadinessPanel().catch(() => {}); + await refreshRuntimeHealthPanel().catch(() => {}); + window.__peoplePollCounter += 1; + if (window.__peoplePollCounter % 4 === 0) { + await renderPeople().catch(() => {}); + } + if (window.__peoplePollCounter % 8 === 0) { + await refreshAudioPromptPanel().catch(() => {}); + } + await refreshAudioPromptRecordStatus().catch(() => {}); + }, 1500); +} + +async function renderPhotos() { + const list = document.getElementById("list"); + if (!list) return; + list.innerHTML = ""; + const res = await apiGet("/api/photos"); + const photos = res.photos || []; + if (!photos.length) { + list.innerHTML = '
No photos yet.
'; + return; + } + for (const photo of photos) { + const card = el("article", "card"); + card.innerHTML = ` + ${escapeHtml(photo.name)} +
+
${escapeHtml(photo.name)}
+
${formatSize(photo.size || 0)}
${formatTime(photo.mtime || 0)}
+
+ Open + Delete + Reupload +
+
+ `; + card.querySelector(".thumb").addEventListener("click", () => openPreview(photo.name)); + list.appendChild(card); + } + + document.querySelectorAll("a.del").forEach((anchor) => { + anchor.addEventListener("click", async (ev) => { + ev.preventDefault(); + const name = anchor.getAttribute("data-name"); + if (!confirm("Delete this photo?")) return; + await apiGet(`/api/delete?name=${name}`); + await renderPhotos(); + }); + }); +} + +function openPreview(name) { + const modal = document.getElementById("preview_modal"); + const img = document.getElementById("modal_img"); + const actions = document.getElementById("modal_actions"); + img.src = `/${encodeURIComponent(name)}`; + actions.innerHTML = ` + Open / Download + Reupload + Delete + `; + document.getElementById("modal_delete").addEventListener("click", async (ev) => { + ev.preventDefault(); + if (!confirm("Delete this photo?")) return; + await apiGet(`/api/delete?name=${encodeURIComponent(name)}`); + closeModal(); + await renderPhotos(); + }); + modal.style.display = "flex"; +} + +function closeModal() { + const modal = document.getElementById("preview_modal"); + if (modal) modal.style.display = "none"; +} + +window.addEventListener("load", () => { + bindTopActions(); + const modalClose = document.getElementById("modal_close"); + if (modalClose) modalClose.addEventListener("click", closeModal); + renderControls().catch((e) => { + const ctrl = document.getElementById("controls"); + if (ctrl) ctrl.innerHTML = `
Dashboard load failed\n${escapeHtml(e.message)}
`; + }); + renderPhotos().catch(() => {}); +}); + +window.addEventListener("beforeunload", () => { + if (window.__dashboardPoll) clearInterval(window.__dashboardPoll); + if (window.__previewEnabled) setPreviewEnabled(false); +}); + +async function openScriptsModal() { + const modal = document.getElementById("scripts_modal"); + const list = document.getElementById("scripts_list"); + const editor = document.getElementById("script_editor"); + const fname = document.getElementById("script_filename"); + list.innerHTML = "Loading..."; + try { + const r = await apiGet("/api/scripts"); + if ((r.scripts || []).length === 0) { + list.innerHTML = "No scripts"; + } else { + list.innerHTML = ""; + r.scripts.forEach((s) => { + const row = document.createElement("div"); + row.className = "script-row"; + row.innerHTML = `${escapeHtml(s)}   `; + list.appendChild(row); + }); + list.querySelectorAll("button").forEach((btn) => { + btn.addEventListener("click", async () => { + const act = btn.getAttribute("data-act"); + const name = btn.getAttribute("data-name"); + if (act === "set") { + await fetch("/api/set_sanad_script", { method: "POST", headers: { "Content-Type": "application/json" }, body: JSON.stringify({ name }) }); + alert(`Set as active: ${name}`); + } else if (act === "del") { + if (!confirm(`Delete script ${name}?`)) return; + await fetch("/api/delete_script", { method: "POST", headers: { "Content-Type": "application/json" }, body: JSON.stringify({ name }) }); + await openScriptsModal(); + } else if (act === "edit") { + const r = await apiGet(`/api/script_content?name=${encodeURIComponent(name)}`); + if (r.ok) { + editor.value = r.script || ""; + fname.value = name; + } + } + }); + }); + } + } catch (_e) { + list.innerHTML = "Error"; + } + + try { + const a = await apiGet("/api/sanad_script"); + if (a.ok) editor.value = a.script || ""; + } catch (_e) {} + + document.getElementById("scripts_modal_close").onclick = () => { + modal.style.display = "none"; + }; + document.getElementById("script_upload").onclick = async () => { + const name = fname.value.trim(); + const script = editor.value || ""; + if (!name) { + alert("Enter filename"); + return; + } + await fetch("/api/upload_script", { method: "POST", headers: { "Content-Type": "application/json" }, body: JSON.stringify({ filename: name, script }) }); + await openScriptsModal(); + }; + document.getElementById("script_save").onclick = async () => { + await fetch("/api/sanad_script", { method: "POST", headers: { "Content-Type": "application/json" }, body: JSON.stringify({ script: editor.value || "" }) }); + alert("Saved active SANAD script"); + }; + + modal.style.display = "flex"; +} diff --git a/Web/style.css b/Web/style.css new file mode 100644 index 0000000..21fb02a --- /dev/null +++ b/Web/style.css @@ -0,0 +1,730 @@ +:root { + --bg: #efe8db; + --bg-accent: #d7e0d4; + --panel: rgba(249, 248, 244, 0.96); + --panel-strong: #fbfaf7; + --ink: #1c241f; + --muted: #5f675d; + --line: rgba(38, 58, 44, 0.14); + --line-strong: rgba(32, 58, 44, 0.24); + --accent: #255f4a; + --accent-2: #8f3b24; + --soft: #ecf3ec; + --warn: #8b3120; + --shadow: 0 22px 50px rgba(24, 34, 26, 0.10); +} + +* { + box-sizing: border-box; +} + +body { + margin: 0; + color: var(--ink); + background: + radial-gradient(circle at top left, rgba(143, 59, 36, 0.08), transparent 28%), + radial-gradient(circle at top right, rgba(37, 95, 74, 0.10), transparent 34%), + linear-gradient(180deg, #f4efe4 0%, var(--bg) 46%, #e6ede5 100%); + font-family: "Trebuchet MS", "Gill Sans", "Segoe UI", sans-serif; +} + +button, +input, +select, +textarea { + font: inherit; +} + +code, +pre, +.meta-code { + font-family: "IBM Plex Mono", "SFMono-Regular", Consolas, monospace; +} + +.page-shell { + max-width: 1560px; + margin: 0 auto; + padding: 22px 22px 40px; +} + +.topbar { + display: flex; + justify-content: space-between; + align-items: center; + gap: 16px; + padding: 18px 20px; + border: 1px solid var(--line); + border-radius: 24px; + background: linear-gradient(180deg, rgba(255,255,255,0.72), rgba(249,248,244,0.95)); + box-shadow: var(--shadow); +} + +.brand-block { + display: flex; + align-items: center; + gap: 14px; +} + +.brand-mark { + width: 54px; + height: 54px; + border-radius: 18px; + display: grid; + place-items: center; + background: linear-gradient(135deg, #214f40, #547a62); + color: #f8fbf8; + font-weight: 800; + letter-spacing: 0.08em; +} + +.eyebrow, +.panel-eyebrow, +.section-eyebrow { + text-transform: uppercase; + letter-spacing: 0.16em; + font-size: 11px; + color: var(--muted); +} + +.title { + font-family: Georgia, "Times New Roman", serif; + font-size: 32px; + font-weight: 700; +} + +.top-actions { + display: flex; + flex-wrap: wrap; + justify-content: flex-end; + gap: 10px; +} + +.btn, +.btn-secondary, +.btn-small, +.btn-danger { + appearance: none; + border-radius: 999px; + border: 1px solid var(--line-strong); + padding: 11px 16px; + cursor: pointer; + transition: transform 0.14s ease, box-shadow 0.14s ease, background 0.14s ease; + text-decoration: none; + display: inline-flex; + align-items: center; + justify-content: center; + gap: 8px; +} + +.btn:hover, +.btn-secondary:hover, +.btn-small:hover, +.btn-danger:hover, +button:hover { + transform: translateY(-1px); +} + +.btn.primary, +button.primary, +.top-actions .btn.primary { + background: var(--accent); + color: #fff; + border-color: var(--accent); + box-shadow: 0 12px 24px rgba(37, 95, 74, 0.22); +} + +.btn.ghost, +.btn-secondary, +button.ghost { + background: rgba(255,255,255,0.82); + color: var(--accent); +} + +.btn.danger, +.btn-danger, +button.danger { + background: rgba(255,255,255,0.82); + color: var(--warn); + border-color: rgba(139, 49, 32, 0.3); +} + +.meta-strip { + display: flex; + flex-wrap: wrap; + gap: 12px; + margin: 16px 0 20px; +} + +.meta-pill { + background: rgba(255,255,255,0.7); + border: 1px solid var(--line); + color: var(--muted); + padding: 10px 14px; + border-radius: 999px; +} + +.dashboard-layout { + display: grid; + grid-template-columns: minmax(0, 1.5fr) minmax(320px, 0.9fr); + gap: 22px; + align-items: start; +} + +.dashboard-main, +.dashboard-side { + min-width: 0; +} + +.dashboard-side { + display: grid; + gap: 22px; +} + +.dashboard-stack, +.status-grid, +.control-grid, +.camera-grid { + display: grid; + gap: 18px; +} + +.control-grid { + grid-template-columns: repeat(2, minmax(0, 1fr)); +} + +.camera-grid { + grid-template-columns: minmax(0, 1.25fr) minmax(320px, 0.95fr); +} + +.status-grid { + grid-template-columns: repeat(2, minmax(0, 1fr)); +} + +.panel { + background: var(--panel); + border: 1px solid var(--line); + border-radius: 24px; + padding: 18px; + box-shadow: var(--shadow); + min-width: 0; +} + +.panel.strong { + background: linear-gradient(180deg, rgba(255,255,255,0.88), var(--panel-strong)); +} + +.panel-header { + display: flex; + justify-content: space-between; + align-items: flex-start; + gap: 12px; + margin-bottom: 12px; +} + +.panel-header h2, +.panel-header h3, +.panel h4, +.panel h3 { + margin: 0; + font-family: Georgia, "Times New Roman", serif; +} + +.panel-copy, +.meta, +.subtle { + color: var(--muted); +} + +.preview-shell { + position: relative; + overflow: hidden; + border-radius: 20px; + border: 1px solid var(--line); + background: + radial-gradient(circle at top left, rgba(37,95,74,0.12), transparent 28%), + linear-gradient(180deg, #dde8df 0%, #cfd9cc 100%); +} + +.preview-shell::after { + content: ""; + position: absolute; + inset: 0; + background: linear-gradient(180deg, transparent 0%, rgba(18, 28, 22, 0.10) 100%); + pointer-events: none; +} + +.camera-preview { + width: 100%; + display: none; + aspect-ratio: 4 / 3; + object-fit: cover; + background: #d6ded3; +} + +.preview-placeholder { + display: grid; + place-items: center; + aspect-ratio: 4 / 3; + color: var(--muted); + text-align: center; + padding: 20px; +} + +.preview-toolbar, +.inline-actions, +.action-row, +.resolution-row, +.selector-row { + display: flex; + flex-wrap: wrap; + gap: 10px; + align-items: center; +} + +.selector-row select, +.resolution-row select, +.selector-row input, +.resolution-row input { + min-width: 110px; + max-width: 100%; +} + +select, +input, +textarea { + appearance: none; + border: 1px solid var(--line-strong); + border-radius: 999px; + padding: 11px 14px; + background: rgba(255,255,255,0.9); + color: var(--ink); +} + +textarea.script-editor { + width: 100%; + height: 260px; + margin-top: 6px; + border-radius: 18px; + font-family: "IBM Plex Mono", Consolas, monospace; +} + +.status-box, +.info-box, +.raw-box { + margin-top: 12px; + padding: 14px; + border-radius: 18px; + border: 1px solid var(--line); + background: linear-gradient(180deg, rgba(255,255,255,0.62), rgba(236,243,236,0.92)); +} + +.status-box { + white-space: pre-wrap; +} + +.raw-box { + white-space: pre-wrap; + overflow: auto; + max-height: 260px; +} + +.info-grid { + display: grid; + grid-template-columns: repeat(2, minmax(0, 1fr)); + gap: 10px 14px; +} + +.stat-line { + display: flex; + justify-content: space-between; + gap: 12px; + color: var(--muted); + padding-bottom: 6px; + border-bottom: 1px dashed rgba(38, 58, 44, 0.12); +} + +.stat-line b { + color: var(--ink); + text-align: right; +} + +.chip-row { + display: flex; + flex-wrap: wrap; + gap: 8px; + margin-top: 10px; +} + +.chip { + display: inline-flex; + align-items: center; + gap: 8px; + border-radius: 999px; + padding: 8px 12px; + background: rgba(255,255,255,0.78); + border: 1px solid var(--line); + color: var(--muted); +} + +.chip strong { + color: var(--ink); +} + +.replay-list { + display: grid; + gap: 12px; +} + +.audio-prompt-grid { + display: grid; + grid-template-columns: repeat(auto-fill, minmax(280px, 1fr)); + gap: 14px; +} + +.audio-prompt-recorder { + display: grid; + gap: 12px; + padding: 14px; + margin: 14px 0; + border-radius: 18px; + border: 1px solid var(--line); + background: rgba(255,255,255,0.58); +} + +.audio-prompt-card { + display: grid; + gap: 12px; + padding: 16px; + border-radius: 20px; + border: 1px solid var(--line); + background: rgba(255,255,255,0.74); + box-shadow: 0 12px 24px rgba(24, 34, 26, 0.06); +} + +.audio-prompt-card.ready { + background: linear-gradient(180deg, rgba(236,243,236,0.98), rgba(255,255,255,0.92)); +} + +.audio-prompt-head { + display: flex; + justify-content: space-between; + gap: 12px; + align-items: flex-start; +} + +.audio-prompt-title { + font-weight: 800; + font-size: 15px; +} + +.audio-prompt-key { + margin-top: 4px; + color: var(--muted); + font-size: 12px; + font-family: "IBM Plex Mono", "SFMono-Regular", Consolas, monospace; +} + +.audio-prompt-text { + padding: 12px 14px; + border-radius: 16px; + background: rgba(255,255,255,0.84); + border: 1px dashed rgba(38, 58, 44, 0.14); + color: var(--ink); + line-height: 1.45; +} + +.audio-prompt-meta { + color: var(--muted); + font-size: 13px; + line-height: 1.5; +} + +.audio-prompt-actions { + display: flex; + flex-wrap: wrap; + gap: 8px; +} + +.audio-prompt-actions .btn { + padding: 8px 12px; + font-size: 13px; +} + +.prompt-editor { + width: 100%; + min-height: 112px; + resize: vertical; + border-radius: 18px; + border: 1px solid var(--line-strong); + padding: 12px 14px; + background: rgba(255,255,255,0.88); + color: var(--ink); +} + +.replay-row { + display: grid; + grid-template-columns: minmax(0, 1fr) auto auto; + gap: 12px; + align-items: center; + padding: 14px 16px; + border-radius: 18px; + border: 1px solid var(--line); + background: rgba(255,255,255,0.72); +} + +.replay-row.active { + border-color: rgba(37, 95, 74, 0.32); + background: linear-gradient(180deg, rgba(236,243,236,0.98), rgba(255,255,255,0.92)); +} + +.replay-main { + min-width: 0; +} + +.replay-title { + font-weight: 700; + overflow-wrap: anywhere; +} + +.replay-meta { + margin-top: 4px; + color: var(--muted); + font-size: 13px; +} + +.replay-tags, +.replay-row-actions { + display: flex; + flex-wrap: wrap; + gap: 8px; + align-items: center; + justify-content: flex-end; +} + +.replay-tag { + display: inline-flex; + align-items: center; + border-radius: 999px; + padding: 6px 10px; + font-size: 12px; + line-height: 1; + background: rgba(255,255,255,0.9); + border: 1px solid var(--line); + color: var(--muted); +} + +.replay-tag.active { + background: rgba(37, 95, 74, 0.12); + border-color: rgba(37, 95, 74, 0.28); + color: var(--accent); +} + +.replay-tag.warn { + background: rgba(139, 49, 32, 0.08); + border-color: rgba(139, 49, 32, 0.24); + color: var(--warn); +} + +.cards-grid { + display: grid; + grid-template-columns: repeat(auto-fill, minmax(230px, 1fr)); + gap: 16px; +} + +.people-grid { + display: grid; + gap: 14px; + grid-template-columns: repeat(auto-fill, minmax(250px, 1fr)); +} + +.person-card { + background: linear-gradient(180deg, rgba(255,255,255,0.78), rgba(236,243,236,0.94)); + border: 1px solid var(--line); + border-radius: 22px; + overflow: hidden; + box-shadow: 0 12px 26px rgba(24, 34, 26, 0.08); +} + +.person-card-head { + display: grid; + grid-template-columns: 1fr 1fr; + gap: 1px; + background: rgba(38, 58, 44, 0.08); +} + +.person-card-head img { + width: 100%; + aspect-ratio: 1 / 1; + object-fit: cover; + display: block; + background: #d7dfd5; +} + +.person-card-body { + padding: 14px; + display: grid; + gap: 10px; +} + +.person-title { + font-weight: 800; + font-size: 15px; + line-height: 1.3; + overflow-wrap: anywhere; +} + +.person-meta { + color: var(--muted); + font-size: 13px; + white-space: pre-wrap; +} + +.person-actions { + display: flex; + flex-wrap: wrap; + gap: 8px; +} + +.person-actions .btn, +.person-actions .btn-secondary, +.person-actions .btn-danger { + padding: 8px 12px; + font-size: 13px; +} + +.card { + background: rgba(255,255,255,0.72); + border: 1px solid var(--line); + border-radius: 20px; + overflow: hidden; + box-shadow: 0 12px 24px rgba(24, 34, 26, 0.07); +} + +.card .thumb { + width: 100%; + aspect-ratio: 4 / 3; + object-fit: cover; + display: block; + cursor: pointer; + background: #d7dfd5; +} + +.card-body { + padding: 14px; +} + +.card .name { + font-weight: 700; + font-size: 14px; + overflow-wrap: anywhere; +} + +.photo-meta { + margin-top: 8px; + color: var(--muted); + font-size: 13px; +} + +.actions, +.modal-actions { + display: flex; + flex-wrap: wrap; + gap: 10px; + margin-top: 12px; +} + +.actions a, +.modal-actions a { + color: var(--accent); + text-decoration: none; +} + +.modal { + position: fixed; + inset: 0; + display: flex; + align-items: center; + justify-content: center; + padding: 20px; + background: rgba(10, 18, 13, 0.62); + backdrop-filter: blur(8px); +} + +.modal-content { + position: relative; + width: min(960px, 100%); + max-height: 92vh; + overflow: auto; + background: #fbfaf7; + border-radius: 24px; + padding: 18px; + box-shadow: 0 30px 60px rgba(0,0,0,0.24); +} + +.modal-content img { + width: 100%; + border-radius: 18px; +} + +.modal-wide { + width: min(1000px, 100%); +} + +.modal-close { + position: absolute; + top: 14px; + right: 14px; + width: 38px; + height: 38px; + border-radius: 50%; + border: 1px solid var(--line); + background: rgba(255,255,255,0.92); + cursor: pointer; +} + +.script-row { + display: block; +} + +@media (max-width: 1180px) { + .dashboard-layout, + .camera-grid { + grid-template-columns: 1fr; + } +} + +@media (max-width: 860px) { + .topbar, + .panel-header, + .selector-row, + .resolution-row, + .preview-toolbar, + .action-row, + .top-actions { + flex-direction: column; + align-items: stretch; + } + + .control-grid, + .status-grid, + .info-grid { + grid-template-columns: 1fr; + } + + .page-shell { + padding: 14px 14px 28px; + } + + .title { + font-size: 24px; + } + + .replay-row { + grid-template-columns: 1fr; + } + + .replay-tags, + .replay-row-actions { + justify-content: flex-start; + } +} diff --git a/requirements.txt b/requirements.txt new file mode 100644 index 0000000..2c360f9 --- /dev/null +++ b/requirements.txt @@ -0,0 +1,10 @@ +requests>=2.31.0 +boto3>=1.34.0 +websockets>=12.0 +pyzmq>=25.1.0 +Pillow>=10.0.0 +numpy>=1.24.0 +opencv-python>=4.8.0 +ultralytics>=8.3.0 +PyAudio>=0.2.13 +google-generativeai>=0.8.0