fix warping

app.py

@@ -220,6 +220,7 @@ def stabilize_video_using_csv(video_file, csv_file, zoom=1.0, vertical_only=Fals
         if not ret:
             break
         
+        # Apply zoom by resizing and then center-cropping
         if zoom != 1.0:
             zoomed_frame = cv2.resize(frame, None, fx=zoom, fy=zoom, interpolation=cv2.INTER_LINEAR)
             zoomed_h, zoomed_w = zoomed_frame.shape[:2]
@@ -232,6 +233,7 @@ def stabilize_video_using_csv(video_file, csv_file, zoom=1.0, vertical_only=Fals
             dx = 0  # Only vertical stabilization.
         transform = np.array([[1, 0, dx],
                               [0, 1, dy]], dtype=np.float32)
+        # Use BORDER_REPLICATE to avoid black borders
         stabilized_frame = cv2.warpAffine(frame, transform, (width, height), borderMode=cv2.BORDER_REPLICATE)
         
         out.write(stabilized_frame)
@@ -252,7 +254,7 @@ def process_video_ai(video_file, zoom, vertical_only, compress_mode, target_widt
     Gradio interface function:
       - Optionally compresses the video if compress_mode is True, resizing it to the chosen resolution.
       - Generates motion data from the (possibly compressed) video.
-      - If auto_zoom is enabled, computes the optimal zoom level based on the maximum cumulative translation so that no black borders appear.
+      - If auto_zoom is enabled, computes the optimal zoom level based on the maximum cumulative displacements.
       - Stabilizes the video based on the generated motion data.
       - If vertical_only is True, only vertical stabilization is applied.
     
@@ -285,26 +287,23 @@ def process_video_ai(video_file, zoom, vertical_only, compress_mode, target_widt
         csv_file = generate_motion_csv(video_file, progress=progress, progress_offset=motion_offset, progress_scale=motion_scale)
         gr.Info("Motion CSV generated successfully.")
         
-        # If auto zoom is enabled, compute the optimal zoom factor.
+        # Auto Zoom Mode: compute the optimal zoom factor to avoid black borders.
         if auto_zoom:
             gr.Info("Auto Zoom Mode enabled. Computing optimal zoom factor...")
             motion_data = read_motion_csv(csv_file)
-            dx_list = [abs(v[0]) for v in motion_data.values()]
-            dy_list = [abs(v[1]) for v in motion_data.values()]
-            max_dx = max(dx_list) if dx_list else 0
-            max_dy = max(dy_list) if dy_list else 0
+            # Compute separate left/right and top/bottom displacements.
+            left_disp = abs(min(v[0] for v in motion_data.values()))
+            right_disp = max(v[0] for v in motion_data.values())
+            top_disp = abs(min(v[1] for v in motion_data.values()))
+            bottom_disp = max(v[1] for v in motion_data.values())
             cap = cv2.VideoCapture(video_file)
             width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
             height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
             cap.release()
-            if width - 2*max_dx > 0:
-                zoom_x = width / (width - 2*max_dx)
-            else:
-                zoom_x = 1.0
-            if height - 2*max_dy > 0:
-                zoom_y = height / (height - 2*max_dy)
-            else:
-                zoom_y = 1.0
+            safe_width = width - (left_disp + right_disp)
+            safe_height = height - (top_disp + bottom_disp)
+            zoom_x = width / safe_width if safe_width > 0 else 1.0
+            zoom_y = height / safe_height if safe_height > 0 else 1.0
             auto_zoom_factor = max(1.0, zoom_x, zoom_y)
             gr.Info(f"Auto zoom factor computed: {auto_zoom_factor:.2f}")
             zoom = auto_zoom_factor