Update sam_module.py

sam_module.py

@@ -65,6 +65,21 @@ def create_sam_mask(self, image, bbox_coords, mode):
             num_masks = outputs.pred_masks.shape[2]
             print(f"   SAM lieferte {num_masks} verschiedene Masken")  
 
+            # ✅ WICHTIG: Sammlung aller Masken hinzufügen (fehlt in Ihrem Code!)
+            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_center = ((x1 + x2) // 2, (y1 + y2) // 2)
             bbox_area = (x2 - x1) * (y2 - y1)
@@ -319,6 +334,21 @@ def create_sam_mask(self, image, bbox_coords, mode):
                 print(f"   Anzahl der Vorhersagemasken: {outputs.pred_masks.shape[2]}")
 
             num_masks = outputs.pred_masks.shape[2]
+
+            # ✅ WICHTIG: Sammlung aller Masken hinzufügen (fehlt in Ihrem Code!)
+            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