Don't use region for state classification models

frigate/data_processing/real_time/custom_classification.py

@@ -229,30 +229,34 @@ class CustomStateClassificationProcessor(RealTimeProcessorApi):
         if not should_run:
             return
 
-        x, y, x2, y2 = calculate_region(
-            frame.shape,
-            crop[0],
-            crop[1],
-            crop[2],
-            crop[3],
-            224,
-            1.0,
-        )
-
         rgb = cv2.cvtColor(frame, cv2.COLOR_YUV2RGB_I420)
-        frame = rgb[
+        height, width = rgb.shape[:2]
-            y:y2,
-            x:x2,
-        ]
 
-        if frame.shape != (224, 224):
+        # Convert normalized crop coordinates to pixel values
-            try:
+        x1 = int(camera_config.crop[0] * width)
-                resized_frame = cv2.resize(frame, (224, 224))
+        y1 = int(camera_config.crop[1] * height)
-            except Exception:
+        x2 = int(camera_config.crop[2] * width)
-                logger.warning("Failed to resize image for state classification")
+        y2 = int(camera_config.crop[3] * height)
-                return
+
-        else:
+        # Clip coordinates to frame boundaries
-            resized_frame = frame
+        x1 = max(0, min(x1, width))
+        y1 = max(0, min(y1, height))
+        x2 = max(0, min(x2, width))
+        y2 = max(0, min(y2, height))
+
+        if x2 <= x1 or y2 <= y1:
+            logger.warning(
+                f"Invalid crop coordinates for {camera}: [{x1}, {y1}, {x2}, {y2}]"
+            )
+            return
+
+        frame = rgb[y1:y2, x1:x2]
+
+        try:
+            resized_frame = cv2.resize(frame, (224, 224))
+        except Exception:
+            logger.warning("Failed to resize image for state classification")
+            return
 
         if self.interpreter is None:
             # When interpreter is None, always save (score is 0.0, which is < 1.0)