Upload app.py

app.py

@@ -67,7 +67,7 @@ extractor_vit = ViTExtractor('dinov2_vitb14', stride=14, device=device)
 # ─── Feature extraction ──────────────────────────────────────────
 def get_processed_features_dino(num_patches, img,use_dummy):
     batch = extractor_vit.preprocess_pil(img)
-    features_dino = extractor_vit.extract_descriptors(batch.cuda(), layer=11, facet='token') \
+    features_dino = extractor_vit.extract_descriptors(batch.to(extractor_vit.device), layer=11, facet='token') \
                                     .permute(0,1,3,2) \
                                     .reshape(1, -1, num_patches, num_patches)
     # Project + normalize
@@ -197,7 +197,7 @@ with gr.Blocks() as demo:
                              
     Welcome to the DIY-SC demo!
     Upload two images and select a keypoint in the source image. This demo will compute and visualize the feature similarity map and a corresponding point in the target image.
-    You can choose between the DIY-SC (DINOv2) and a DINOv2 feature extractor.
+    You can choose between the DIY-SC (DINOv2) or the DINOv2 feature extractor.
     """)
 
     # Image upload / display components