Update app.py

app.py

@@ -135,6 +135,53 @@ with tempfile.TemporaryDirectory() as tmpdir:
         src_image = gr.State()
         src_depth = gr.State()
 
+        def normalize_disp(disp):
+            return (disp - disp.min()) / (disp.max() - disp.min())
+
+        # Callbacks
+        @spaces.GPU()        
+        def cb_mde(image_file: str):
+            if not image_file:
+                # Return None if no image is provided (e.g., when file is cleared).
+                return None, None, None, None
+
+            image = crop(Image.open(image_file).convert('RGB'))  # Load image using PIL
+            image = image.resize((IMAGE_SIZE, IMAGE_SIZE))
+
+            image_bgr = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
+
+            dam2 = get_dam2_model()
+            depth_dam2 = dam2.infer_image(image_bgr)
+            depth = torch.tensor(depth_dam2).unsqueeze(0).unsqueeze(0).float()
+
+            depth_image = cv2.applyColorMap((normalize_disp(depth_dam2) * 255).astype(np.uint8), cv2.COLORMAP_JET)
+
+            return image, depth_image, image, depth
+
+        @spaces.GPU()
+        def cb_generate(image, depth: Tensor, scale_factor):
+            norm_disp = normalize_disp(depth.cuda())
+            disp = norm_disp * scale_factor / 100 * IMAGE_SIZE
+
+            genstereo = get_genstereo_model()
+            fusion_model = get_fusion_model()
+
+            renders = genstereo(
+                src_image=image,
+                src_disparity=disp,
+                ratio=None,
+            )
+            warped = (renders['warped'] + 1) / 2
+            
+            synthesized = renders['synthesized']
+            mask = renders['mask']
+            fusion_image = fusion_model(synthesized.float(), warped.float(), mask.float())
+
+            warped_pil = to_pil_image(warped[0])
+            fusion_pil = to_pil_image(fusion_image[0])
+
+            return warped_pil, fusion_pil
+
         # Blocks.
         gr.Markdown(
             """
@@ -191,53 +238,6 @@ with tempfile.TemporaryDirectory() as tmpdir:
                 label='Generated Right', type='pil', interactive=False
             )
 
-        def normalize_disp(disp):
-            return (disp - disp.min()) / (disp.max() - disp.min())
-
-        # Callbacks
-        @spaces.GPU()        
-        def cb_mde(image_file: str):
-            if not image_file:
-                # Return None if no image is provided (e.g., when file is cleared).
-                return None, None, None, None
-
-            image = crop(Image.open(image_file).convert('RGB'))  # Load image using PIL
-            image = image.resize((IMAGE_SIZE, IMAGE_SIZE))
-
-            image_bgr = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
-
-            dam2 = get_dam2_model()
-            depth_dam2 = dam2.infer_image(image_bgr)
-            depth = torch.tensor(depth_dam2).unsqueeze(0).unsqueeze(0).float()
-
-            depth_image = cv2.applyColorMap((normalize_disp(depth_dam2) * 255).astype(np.uint8), cv2.COLORMAP_JET)
-
-            return image, depth_image, image, depth
-
-        @spaces.GPU()
-        def cb_generate(image, depth: Tensor, scale_factor):
-            norm_disp = normalize_disp(depth.cuda())
-            disp = norm_disp * scale_factor / 100 * IMAGE_SIZE
-
-            genstereo = get_genstereo_model()
-            fusion_model = get_fusion_model()
-
-            renders = genstereo(
-                src_image=image,
-                src_disparity=disp,
-                ratio=None,
-            )
-            warped = (renders['warped'] + 1) / 2
-            
-            synthesized = renders['synthesized']
-            mask = renders['mask']
-            fusion_image = fusion_model(synthesized.float(), warped.float(), mask.float())
-
-            warped_pil = to_pil_image(warped[0])
-            fusion_pil = to_pil_image(fusion_image[0])
-
-            return warped_pil, fusion_pil
-
         # Events
         file.change(
             fn=cb_mde,