Update app.py

app.py

@@ -80,12 +80,29 @@ def stitch_rgbd_videos(
             if blur > 0:
                 kernel_size = int(blur * 20) * 2 + 1  # Ensures an odd kernel size.
                 depth_vis = cv2.GaussianBlur(depth_vis, (kernel_size, kernel_size), 0)
+            
             # Resize the depth visualization to match the full-resolution RGB frame.
             H_full, W_full = rgb_full.shape[:2]
             depth_vis_resized = cv2.resize(depth_vis, (W_full, H_full))
-            # Concatenate the full-resolution RGB frame (left) and the resized depth visualization (right).
-            stitched = cv2.hconcat([rgb_full, depth_vis_resized])
+            
+            # Ensure both images have 3 channels.
+            if len(rgb_full.shape) == 2:
+                rgb_full = cv2.cvtColor(rgb_full, cv2.COLOR_GRAY2BGR)
+            if len(depth_vis_resized.shape) == 2:
+                depth_vis_resized = cv2.cvtColor(depth_vis_resized, cv2.COLOR_GRAY2BGR)
+            
+            # Ensure same data type.
+            if rgb_full.dtype != depth_vis_resized.dtype:
+                depth_vis_resized = depth_vis_resized.astype(rgb_full.dtype)
+            
+            # Ensure images are contiguous in memory.
+            rgb_full = np.ascontiguousarray(rgb_full)
+            depth_vis_resized = np.ascontiguousarray(depth_vis_resized)
+            
+            # Now safely concatenate.
+            stitched = cv2.hconcat([rgb_full, depth_vis_resized])            
             stitched_frames.append(stitched)
+            
         stitched_frames = np.array(stitched_frames)
         # Use only the first 20 characters of the base name for the output filename and append '_RGBD.mp4'
         base_name = os.path.splitext(video_name)[0]