Integrate YOLOv8 detection and pet ID into camera worker

vigilar/camera/worker.py

@@ -22,6 +22,9 @@ from vigilar.camera.recorder import AdaptiveRecorder
 from vigilar.camera.ring_buffer import RingBuffer
 from vigilar.config import CameraConfig, MQTTConfig, RemoteConfig
 from vigilar.constants import Topics
+from vigilar.detection.yolo import YOLODetector
+from vigilar.detection.pet_id import PetIDClassifier
+from vigilar.detection.wildlife import classify_wildlife_threat
 
 log = logging.getLogger(__name__)
 
@@ -46,6 +49,7 @@ def run_camera_worker(
     recordings_dir: str,
     hls_dir: str,
     remote_cfg: RemoteConfig | None = None,
+    pets_cfg: "PetsConfig | None" = None,
 ) -> None:
     """Main entry point for a camera worker process."""
     camera_id = camera_cfg.id
@@ -107,6 +111,21 @@ def run_camera_worker(
             bitrate_kbps=remote_cfg.remote_hls_bitrate_kbps,
         )
 
+    # Object detection (YOLOv8 unified detector)
+    yolo_detector = None
+    pet_classifier = None
+    if pets_cfg and pets_cfg.enabled:
+        yolo_detector = YOLODetector(
+            model_path=pets_cfg.model_path,
+            confidence_threshold=pets_cfg.confidence_threshold,
+        )
+        if pets_cfg.pet_id_enabled:
+            pet_classifier = PetIDClassifier(
+                model_path=pets_cfg.pet_id_model_path,
+                high_threshold=pets_cfg.pet_id_threshold,
+                low_threshold=pets_cfg.pet_id_low_confidence,
+            )
+
     state = CameraState()
     shutdown = False
 
@@ -243,6 +262,49 @@ def run_camera_worker(
                 if state.frame_count % idle_skip_factor == 0:
                     recorder.write_frame(frame)
 
+        # Run object detection on motion frames
+        if state.motion_active and yolo_detector and yolo_detector.is_loaded:
+            detections = yolo_detector.detect(frame)
+            for det in detections:
+                category = YOLODetector.classify(det)
+                if category == "domestic_animal":
+                    # Crop for pet ID
+                    x, y, w, h = det.bbox
+                    crop = frame[max(0, y):y + h, max(0, x):x + w]
+                    pet_result = None
+                    if pet_classifier and pet_classifier.is_loaded and crop.size > 0:
+                        pet_result = pet_classifier.identify(crop, species=det.class_name)
+
+                    payload = {
+                        "species": det.class_name,
+                        "confidence": round(det.confidence, 3),
+                        "camera_location": camera_cfg.location,
+                    }
+                    if pet_result and pet_result.is_identified:
+                        payload["pet_id"] = pet_result.pet_id
+                        payload["pet_name"] = pet_result.pet_name
+                        payload["pet_confidence"] = round(pet_result.confidence, 3)
+                        bus.publish_event(
+                            Topics.pet_location(pet_result.pet_name.lower()),
+                            camera_id=camera_id,
+                            camera_location=camera_cfg.location,
+                        )
+
+                    bus.publish_event(Topics.camera_pet_detected(camera_id), **payload)
+
+                elif category == "wildlife" and pets_cfg:
+                    frame_area = frame.shape[0] * frame.shape[1]
+                    threat_level, species = classify_wildlife_threat(
+                        det, pets_cfg.wildlife, frame_area,
+                    )
+                    bus.publish_event(
+                        Topics.camera_wildlife_detected(camera_id),
+                        species=species,
+                        threat_level=threat_level,
+                        confidence=round(det.confidence, 3),
+                        camera_location=camera_cfg.location,
+                    )
+
         # Heartbeat every 10 seconds
         if now - last_heartbeat >= 10:
             last_heartbeat = now