Update app.py

app.py

@@ -170,33 +170,29 @@ def infer(image, width=1024, height=1024, overlap_width=18, num_inference_steps=
 
     yield background, cnet_image
 
-def interpolate_frames(frame1, frame2, num_intermediate_frames):
+def interpolate_frames(larger_frame, smaller_frame, num_intermediate_frames):
     """
-    Interpolate between two frames by gradually zooming out from frame2 to frame1.
+    Create intermediate frames for a smooth zoom-in effect from the larger frame to the smaller frame.
     """
-    frame1 = np.array(frame1)
-    frame2 = np.array(frame2)
-    h, w = frame1.shape[:2]
+    larger_frame = np.array(larger_frame)
+    smaller_frame = np.array(smaller_frame)
+    h, w = larger_frame.shape[:2]
     frames = []
 
     for i in range(num_intermediate_frames + 2):
         progress = i / (num_intermediate_frames + 1)
-        # Calculate the size of the inner frame
-        inner_h = int(h * (1 - progress))
-        inner_w = int(w * (1 - progress))
+        # Calculate the size of the frame to crop from the larger image
+        crop_h = int(h * (1 - progress) + smaller_frame.shape[0] * progress)
+        crop_w = int(w * (1 - progress) + smaller_frame.shape[1] * progress)
         
-        # Crop the center of frame2
-        start_y = (h - inner_h) // 2
-        start_x = (w - inner_w) // 2
-        cropped = frame2[start_y:start_y+inner_h, start_x:start_x+inner_w]
+        # Crop the center of the larger frame
+        start_y = (h - crop_h) // 2
+        start_x = (w - crop_w) // 2
+        cropped = larger_frame[start_y:start_y+crop_h, start_x:start_x+crop_w]
         
-        # Resize the cropped image to full size
-        interpolated = Image.fromarray(cropped).resize((w, h), Image.LANCZOS)
-        interpolated = np.array(interpolated)
-        
-        # Blend with frame1
-        blended = (1 - progress) * frame1 + progress * interpolated
-        frames.append(Image.fromarray(blended.astype(np.uint8)))
+        # Resize the cropped image to match the smaller frame's size
+        interpolated = Image.fromarray(cropped).resize(smaller_frame.shape[:2][::-1], Image.LANCZOS)
+        frames.append(interpolated)
 
     return frames
 
@@ -221,7 +217,7 @@ def create_video_from_images(image_list, fps=4):
 @spaces.GPU(duration=70)
 def loop_outpainting(image, width=1024, height=1024, overlap_width=18, num_inference_steps=8, 
                      resize_option="custom", custom_resize_size=768, prompt_input=None, 
-                     alignment="Middle", num_iterations=8, fps=6, num_interpolation_frames=5,
+                     alignment="Middle", num_iterations=18, fps=6, num_interpolation_frames=5,
                      progress=gr.Progress()):
     image_list = [image]
     current_image = image
@@ -233,18 +229,29 @@ def loop_outpainting(image, width=1024, height=1024, overlap_width=18, num_infer
             pass  # Process all steps
         
         new_image = step_result[1]  # Get the final image from the last step
-        
-        # Interpolate between current_image and new_image
-        interpolated_frames = interpolate_frames(current_image, new_image, num_interpolation_frames)
-        image_list.extend(interpolated_frames)
+        image_list.append(new_image)
         
         # Use new image as input for next iteration
         current_image = new_image
 
-    # Create video from image list
-    video_path = create_video_from_images(image_list, fps)
-    return video_path
+    # Reverse the image list to create a zoom-in effect
+    reverse_image_list = image_list[::-1]
+    
+    # Create interpolated frames
+    final_frame_list = []
+    for i in range(len(reverse_image_list) - 1):
+        larger_frame = reverse_image_list[i]
+        smaller_frame = reverse_image_list[i + 1]
+        interpolated_frames = create_zoom_in_frames(larger_frame, smaller_frame, num_interpolation_frames)
+        final_frame_list.extend(interpolated_frames)
+    
+    # Add the last frame
+    final_frame_list.append(reverse_image_list[-1])
 
+    # Create video from the final frame list
+    video_path = create_video_from_images(final_frame_list, fps)
+    return video_path
+    
 loop_outpainting.zerogpu = True
 
 def clear_result():