Update sam_module.py

sam_module.py

@@ -334,20 +334,6 @@ def create_sam_mask(self, image, bbox_coords, mode):
 
             num_masks = outputs.pred_masks.shape[2]
             
-            # Sammlung der Masken
-            all_masks = []
-            
-            for i in range(num_masks):
-                single_mask = outputs.pred_masks[:, :, i, :, :]
-                resized_mask = F.interpolate(
-                    single_mask,
-                    size=(image.height, image.width),
-                    mode='bilinear',
-                    align_corners=False
-                ).squeeze()
-                
-                mask_np = resized_mask.sigmoid().cpu().numpy()
-                all_masks.append(mask_np)
 
             # BBox-Information für Heuristik
             bbox_center = ((x1 + x2) // 2, (y1 + y2) // 2)
@@ -358,7 +344,7 @@ def create_sam_mask(self, image, bbox_coords, mode):
             best_score = -1
             
             # Alle 3 Masken analysieren (OHNE sie alle zu skalieren!)
-            for i in range(3):
+            for i in range(num_masks):
                 # Maske in Original-SAM-Größe (256x256) analysieren
                 mask_256 = outputs.pred_masks[:, :, i, :, :]
                 mask_np_256 = mask_256.sigmoid().squeeze().cpu().numpy()