Update app.py

app.py

@@ -24,7 +24,8 @@ def convert_mp4_to_frames(video_path, duration=3):
     fps = video.get(cv2.CAP_PROP_FPS)
 
     # Calculate the number of frames to extract
-    num_frames = int(fps * duration)
+    # Note: we cannot go beyond 3 seconds on the large A10G
+    num_frames = int(fps * min(duration, 3))
 
     frames = []
     frame_count = 0
@@ -61,8 +62,8 @@ def infer(prompt, video_in, denoise_strength, duration, secret_token: str = '')
         
     negative_prompt = "text, watermark, copyright, blurry, cropped, noisy, pixelated, nsfw"
 
-    # we cannot go beyond 3 seconds on the large A10G
-    video = convert_mp4_to_frames(video_in, min(duration, 3))
+
+    video = convert_mp4_to_frames(video_in, duration)
     video_resized = [Image.fromarray(frame).resize((1024, 576)) for frame in video]
     video_frames = pipe_xl(prompt, negative_prompt=negative_prompt, video=video_resized, strength=denoise_strength).frames
     video_path = export_to_video(video_frames, output_video_path="xl_result.mp4")
@@ -84,7 +85,7 @@ with gr.Blocks() as demo:
         video_result = gr.Video(label="Video Output", elem_id="video-output")
 
     submit_btn.click(fn=infer,
-                    inputs=[prompt_in, video_in, denoise_strength, secret_token],
+                    inputs=[prompt_in, video_in, denoise_strength, duration, secret_token],
                     outputs=[video_result],
                     api_name="zero_xl"
                     )