map size error correction

app.py

@@ -228,7 +228,23 @@ def process_image(image, model_choice="GLPN (Recommended)", visualization_type="
         pad = 16
         output = predicted_depth.squeeze().cpu().numpy() * 1000.0
         output = output[pad:-pad, pad:-pad]
-        image = image.crop((pad, pad, image.width - pad, image.height - pad))
+        image_cropped = image.crop((pad, pad, image.width - pad, image.height - pad))
+        
+        # Ensure depth and image have same dimensions
+        depth_height, depth_width = output.shape
+        img_width, img_height = image_cropped.size
+        
+        print(f"After crop - Depth shape: {output.shape}, Image size: {image_cropped.size}")
+        
+        # Resize depth to match image if needed
+        if depth_height != img_height or depth_width != img_width:
+            print(f"Resizing depth from ({depth_height}, {depth_width}) to ({img_height}, {img_width})")
+            from scipy import ndimage
+            zoom_factors = (img_height / depth_height, img_width / depth_width)
+            output = ndimage.zoom(output, zoom_factors, order=1)
+            print(f"Depth resized to: {output.shape}")
+        
+        image = image_cropped
         
         # STEP 3: Create depth visualization
         print("Step 3: Creating depth visualization...")
@@ -252,9 +268,19 @@ def process_image(image, model_choice="GLPN (Recommended)", visualization_type="
         # STEP 4: Create point cloud
         print("Step 4: Generating point cloud...")
         width, height = image.size
+        
+        # Ensure depth map matches image size exactly
+        if output.shape != (height, width):
+            print(f"Final check - resizing depth from {output.shape} to ({height}, {width})")
+            from scipy import ndimage
+            zoom_factors = (height / output.shape[0], width / output.shape[1])
+            output = ndimage.zoom(output, zoom_factors, order=1)
+        
         depth_image = (output * 255 / np.max(output)).astype(np.uint8)
         image_array = np.array(image)
         
+        print(f"Creating RGBD - Image: {image_array.shape}, Depth: {depth_image.shape}")
+        
         depth_o3d = o3d.geometry.Image(depth_image)
         image_o3d = o3d.geometry.Image(image_array)
         rgbd_image = o3d.geometry.RGBDImage.create_from_color_and_depth(