Update processing/video/video_processor.py

processing/video/video_processor.py

@@ -53,13 +53,25 @@ def process_frame(self, frame: np.ndarray, background: np.ndarray) -> Dict[str,
         predictor = None
         try:
             sam2_model = self.models.get_sam2()
-            # FIX: Check that predictor is not None, not just that attribute exists
-            if sam2_model and sam2_model.loaded and sam2_model.predictor is not None:
-                predictor = sam2_model.predictor
-            else:
-                self.log.warning("SAM2 predictor is None or not loaded")
+            # Check if we have a working SAM2 predictor
+            # SAM2ImagePredictor has set_image and predict methods
+            if sam2_model is not None:
+                # Check if it's wrapped (has .predictor attribute)
+                if hasattr(sam2_model, 'predictor'):
+                    predictor = sam2_model.predictor
+                # Or if it IS the predictor (has set_image method)
+                elif hasattr(sam2_model, 'set_image'):
+                    predictor = sam2_model
+                # Or if it's a dict with model and processor (from transformers)
+                elif isinstance(sam2_model, dict) and 'model' in sam2_model:
+                    # For now, we can't use this format easily
+                    self.log.warning("SAM2 loaded as dict format, not directly usable")
+                    predictor = None
+                
+            if predictor is None:
+                self.log.debug("SAM2 predictor not available, will use fallback")
         except Exception as e:
-            self.log.warning(f"SAM2 predictor unavailable, using fallback: {e}")
+            self.log.warning(f"SAM2 predictor unavailable: {e}")
 
         # 1) segment
         mask = segment_person_hq(frame, predictor, fallback_enabled=True)
@@ -68,10 +80,11 @@ def process_frame(self, frame: np.ndarray, background: np.ndarray) -> Dict[str,
         matanyone = None
         try:
             matanyone_model = self.models.get_matanyone()
-            if matanyone_model and matanyone_model.loaded:
+            # Just check if we have a MatAnyone model at all
+            if matanyone_model is not None:
                 matanyone = matanyone_model
         except Exception as e:
-            self.log.warning(f"MatAnyone unavailable, using OpenCV refinement: {e}")
+            self.log.warning(f"MatAnyone unavailable: {e}")
 
         mask_refined = refine_mask_hq(frame, mask, matanyone, fallback_enabled=True)