Refactor detection handling by separating DetectionWorker and integrating it into MainWindow

app/camera.py

@@ -50,38 +50,20 @@ def rotate_frame(frame: np.ndarray, degrees: int) -> np.ndarray:
 
 class CameraWorker(QThread):
     frame_ready = Signal(object)
-    detection_ready = Signal(object)
     camera_error = Signal(str)
 
     def __init__(self, config: dict[str, Any], app_config: Any) -> None:
         super().__init__()
         self.config = config
         self.app_config = app_config
-        self.pipeline = DetectionPipeline(config, app_config)
         self._running = threading.Event()
         self._running.set()
-        self._detecting = False
-        self._accepted = False
-        self._frame_count = 0
         self._capture: cv2.VideoCapture | None = None
         self._lock = threading.Lock()
 
     def stop(self) -> None:
         self._running.clear()
 
-    @Slot()
-    def start_detection(self) -> None:
-        with self._lock:
-            self._detecting = True
-            self._accepted = False
-            self._frame_count = 0
-
-    @Slot()
-    def accept_detection(self) -> None:
-        with self._lock:
-            self._detecting = False
-            self._accepted = True
-
     @Slot(dict)
     def update_camera_config(self, camera_config: dict[str, Any]) -> None:
         with self._lock:
@@ -115,7 +97,6 @@ class CameraWorker(QThread):
                     rotation_degrees = int(self.config["camera"].get("rotation_degrees", 0))
                 frame = rotate_frame(frame, rotation_degrees)
                 self.frame_ready.emit(frame)
-                self._maybe_detect(frame)
         finally:
             capture.release()
             self._capture = None
@@ -131,15 +112,53 @@ class CameraWorker(QThread):
                 continue
             capture.set(CV_CAP_PROPS[name], float(value))
 
-    def _maybe_detect(self, frame: np.ndarray) -> None:
+
+class DetectionWorker(QThread):
+    detection_ready = Signal(object)
+
+    def __init__(self, config: dict[str, Any], app_config: Any) -> None:
+        super().__init__()
+        self.config = config
+        self.app_config = app_config
+        self.pipeline: DetectionPipeline | None = None
+        self._running = threading.Event()
+        self._running.set()
+        self._pending = threading.Event()
+        self._lock = threading.Lock()
+        self._pending_frame: np.ndarray | None = None
+        self._busy = False
+
+    def stop(self) -> None:
+        self._running.clear()
+        self._pending.set()
+
+    def request_detection(self, frame: np.ndarray) -> bool:
         with self._lock:
-            detecting = self._detecting and not self._accepted
-            frame_stride = max(1, int(self.config["detection"].get("frame_stride", 5)))
-            self._frame_count += 1
-            should_detect = detecting and self._frame_count % frame_stride == 0
+            if self._busy or self._pending_frame is not None:
+                return False
+            self._pending_frame = frame.copy()
+            self._pending.set()
+            return True
 
-        if not should_detect:
-            return
+    def run(self) -> None:
+        while self._running.is_set():
+            self._pending.wait(0.2)
+            if not self._running.is_set():
+                break
 
-        result: DetectionResult = self.pipeline.process(frame)
-        self.detection_ready.emit(result)
+            with self._lock:
+                frame = self._pending_frame
+                self._pending_frame = None
+                self._pending.clear()
+                if frame is None:
+                    continue
+                self._busy = True
+
+            try:
+                if self.pipeline is None:
+                    self.pipeline = DetectionPipeline(self.config, self.app_config)
+                result: DetectionResult = self.pipeline.process(frame)
+                self.detection_ready.emit(result)
+            finally:
+                with self._lock:
+                    self._busy = False