Passe de Frigate polling à GetAiState Reolink + LPR ONNX local
- Remplace la source Frigate par l'API GetAiState de la caméra Reolink - Capture RTSP en temps réel (~20s) quand véhicule détecté, garde la meilleure frame - LPR avec YOLOv9 (détection plaque) + PaddleOCR v4 (lecture texte) via ONNX - Modèles partagés avec Frigate (volume local ./models/) - Cooldown 60s entre événements pour éviter les doublons Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
perco
co-authored by
Claude Sonnet 4.6
Claude Sonnet 4.6
parent
f6422b0e7e
commit
65b74ce46d
+132
-62
@@ -1,94 +1,164 @@
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import os
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import time
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import uuid
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import logging
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import requests
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import shutil
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from database import event_exists, insert_event
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from analyzer import extract_dominant_color
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import cv2
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import numpy as np
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from urllib.parse import quote
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from database import insert_event
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from analyzer import extract_dominant_color_from_frame
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from lpr import PlateAnalyzer
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log = logging.getLogger("watcher")
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FRIGATE_URL = os.environ.get("FRIGATE_URL", "http://frigate:5000")
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CAMERA_URL = os.environ.get("CAMERA_URL", "http://192.168.1.44")
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CAMERA_USER = os.environ.get("CAMERA_USER", "admin")
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CAMERA_PASS = os.environ.get("CAMERA_PASS", "")
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CAMERA_RTSP = os.environ.get("CAMERA_RTSP", "")
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CAMERA_NAME = os.environ.get("CAMERA_NAME", "portail")
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SNAPSHOTS_DIR = os.environ.get("SNAPSHOTS_DIR", "/data/snapshots")
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POLL_INTERVAL = int(os.environ.get("POLL_INTERVAL", "30"))
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POLL_INTERVAL = float(os.environ.get("POLL_INTERVAL", "2"))
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CAPTURE_DURATION = int(os.environ.get("CAPTURE_DURATION", "20"))
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COOLDOWN = int(os.environ.get("COOLDOWN", "60"))
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_token: str | None = None
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_token_time = 0.0
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_last_event_time = 0.0
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_analyzer: PlateAnalyzer | None = None
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def fetch_new_events() -> list[dict]:
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def _rtsp_url() -> str:
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if CAMERA_RTSP:
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return CAMERA_RTSP
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host = CAMERA_URL.replace("http://", "").replace("https://", "").split(":")[0]
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return f"rtsp://{quote(CAMERA_USER, safe='')}:{quote(CAMERA_PASS, safe='')}@{host}/h264Preview_01_main"
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def _login() -> str | None:
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global _token, _token_time
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if _token and (time.time() - _token_time) < 3000:
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return _token
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try:
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resp = requests.get(
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f"{FRIGATE_URL}/api/events",
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params={"labels": "car", "has_snapshot": "1", "limit": "50"},
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timeout=10
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resp = requests.post(
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f"{CAMERA_URL}/api.cgi?cmd=Login",
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json=[{"cmd": "Login", "param": {"User": {"userName": CAMERA_USER, "password": CAMERA_PASS}}}],
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timeout=5,
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)
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resp.raise_for_status()
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return resp.json()
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data = resp.json()
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if data[0]["code"] == 0:
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_token = data[0]["value"]["Token"]["name"]
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_token_time = time.time()
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log.debug("Camera login OK")
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return _token
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except Exception as e:
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log.warning(f"Frigate fetch error: {e}")
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return []
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log.warning(f"Login error: {e}")
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return None
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def download_snapshot(event_id: str, dest_path: str) -> bool:
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def _get_ai_state() -> dict | None:
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token = _login()
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if not token:
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return None
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try:
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resp = requests.get(
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f"{FRIGATE_URL}/api/events/{event_id}/snapshot.jpg",
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params={"bbox": "1", "crop": "1", "quality": "95"},
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timeout=15, stream=True
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resp = requests.post(
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f"{CAMERA_URL}/api.cgi?cmd=GetAiState&token={token}",
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json=[{"cmd": "GetAiState", "action": 0, "param": {"channel": 0}}],
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timeout=5,
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)
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resp.raise_for_status()
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with open(dest_path, "wb") as f:
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shutil.copyfileobj(resp.raw, f)
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return True
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data = resp.json()
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if data[0]["code"] == 0:
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return data[0]["value"]
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except Exception as e:
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log.warning(f"Snapshot download error for {event_id}: {e}")
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return False
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log.warning(f"GetAiState error: {e}")
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return None
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def process_event(ev: dict):
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event_id = ev.get("id", "")
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if not event_id or event_exists(event_id):
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def _frame_score(frame: np.ndarray, plates: list) -> float:
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"""Score a frame: prefer large, high-confidence plates. Fallback to sharpness."""
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if plates:
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x1, y1, x2, y2, conf = plates[0]
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return (x2 - x1) * (y2 - y1) * conf
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gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
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return cv2.Laplacian(gray, cv2.CV_64F).var() * 0.001
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def _capture_best_frame() -> np.ndarray | None:
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url = _rtsp_url()
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log.info(f"Capturing RTSP for {CAPTURE_DURATION}s...")
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cap = cv2.VideoCapture(url)
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if not cap.isOpened():
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log.error("Cannot open RTSP stream")
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return None
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best_frame: np.ndarray | None = None
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best_score = -1.0
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start = time.time()
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try:
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while time.time() - start < CAPTURE_DURATION:
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ret, frame = cap.read()
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if not ret:
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log.warning("RTSP read failed, retrying...")
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time.sleep(0.5)
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continue
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plates = _analyzer.detect_plates(frame) if _analyzer else []
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score = _frame_score(frame, plates)
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if score > best_score:
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best_score = score
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best_frame = frame.copy()
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time.sleep(0.8)
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finally:
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cap.release()
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log.info(f"Capture done. Best frame score: {best_score:.2f}")
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return best_frame
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def _process_event():
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frame = _capture_best_frame()
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if frame is None:
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log.warning("No frame captured")
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return
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camera = ev.get("camera", "unknown")
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start_time = int(ev.get("start_time", time.time()))
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# Plate from Frigate LPR
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plate = None
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data = ev.get("data", {})
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if data.get("sub_label"):
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plate = data["sub_label"]
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if isinstance(plate, list):
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plate = plate[0] if plate else None
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# Download snapshot
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event_id = str(uuid.uuid4())
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snapshot_file = f"{event_id}.jpg"
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snapshot_path = os.path.join(SNAPSHOTS_DIR, snapshot_file)
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if not download_snapshot(event_id, snapshot_path):
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return
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cv2.imwrite(snapshot_path, frame, [cv2.IMWRITE_JPEG_QUALITY, 90])
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# Extract color from vehicle bounding box
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bbox = None
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if ev.get("box"):
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b = ev["box"]
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bbox = {"x": b[0], "y": b[1], "width": b[2] - b[0], "height": b[3] - b[1]}
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elif data.get("box"):
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b = data["box"]
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if len(b) == 4:
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bbox = {"x": b[0], "y": b[1], "width": b[2] - b[0], "height": b[3] - b[1]}
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plate, conf = "", 0.0
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if _analyzer:
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plate, conf = _analyzer.read_plate(frame)
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hex_color, color_name = extract_dominant_color(snapshot_path, bbox)
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log.info(f"LPR: plate={plate!r} conf={conf:.2f}")
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insert_event(event_id, camera, start_time, f"snapshots/{snapshot_file}",
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plate, hex_color, color_name)
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log.info(f"Processed event {event_id} | plate={plate} | color={color_name} | camera={camera}")
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hex_color, color_name = extract_dominant_color_from_frame(frame)
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insert_event(
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event_id, CAMERA_NAME, int(time.time()),
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f"snapshots/{snapshot_file}", plate or None, hex_color, color_name,
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)
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log.info(f"Stored: {event_id} | plate={plate} | color={color_name}")
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def run_watcher():
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log.info(f"Watcher started — polling Frigate every {POLL_INTERVAL}s")
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global _last_event_time, _analyzer
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log.info("Loading plate analyzer...")
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_analyzer = PlateAnalyzer()
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log.info(f"Watcher started — polling {CAMERA_URL} every {POLL_INTERVAL}s")
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while True:
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events = fetch_new_events()
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for ev in events:
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try:
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process_event(ev)
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except Exception as e:
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log.error(f"Error processing event: {e}")
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try:
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state = _get_ai_state()
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if state:
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vehicle = state.get("vehicle", {})
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if vehicle.get("alarm_state") == 1:
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now = time.time()
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if now - _last_event_time > COOLDOWN:
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_last_event_time = now
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log.info("Vehicle detected! Triggering capture...")
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_process_event()
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except Exception as e:
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log.error(f"Watcher loop error: {e}", exc_info=True)
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time.sleep(POLL_INTERVAL)
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