Create pipelines/video_matting_pipeline.py

pipelines/video_matting_pipeline.py

@@ -0,0 +1,41 @@
+# Add import at the top
+from models.wrappers.matanyone_wrapper import MatAnyOneWrapper
+
+# In your __init__ method, initialize MatAnyone
+def __init__(self, ...):
+    # ... existing SAM2 initialization ...
+    
+    # Add MatAnyone initialization
+    if self.use_matanyone:
+        from matanyone.inference_core import InferenceCore  # Or wherever it's located
+        matanyone_core = InferenceCore(...)  # Initialize with your config
+        self.matanyone = MatAnyOneWrapper(matanyone_core, device=self.device)
+    
+# In your process_frame or segment_frame method
+def process_frame(self, frame, ...):
+    # ... existing SAM2 processing ...
+    
+    # Add MatAnyone refinement after SAM2
+    if self.use_matanyone and sam2_mask is not None:
+        # Convert SAM2 output to tensor if needed
+        mask_tensor = self._prepare_mask_tensor(sam2_mask)
+        image_tensor = self._prepare_image_tensor(frame)
+        
+        # Load component masks if available
+        components = None
+        if self.component_paths:
+            components = {
+                'hair': self._load_component('hair', frame_idx),
+                'edge': self._load_component('edge', frame_idx),
+                # ... other components
+            }
+        
+        # Refine with MatAnyone
+        refined_mask = self.matanyone.step(
+            image_tensor,
+            mask_tensor,
+            components=components
+        )
+        
+        # Convert back to numpy if needed
+        final_mask = refined_mask.cpu().numpy().squeeze()