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import gradio as gr | |
import subprocess | |
import os | |
def process_video(video_path, prompt): | |
output_folder="noise_warp_output_folder" | |
output_video="output.mp4" | |
device="cuda" | |
num_steps=5 | |
try: | |
# Step 1: Warp the noise | |
warp_command = [ | |
"python", "make_warped_noise.py", video_path, | |
"--output_folder", output_folder | |
] | |
subprocess.run(warp_command, check=True) | |
# Step 2: Run inference | |
inference_command = [ | |
"python", "cut_and_drag_inference.py", output_folder, | |
"--prompt", prompt, | |
"--output_mp4_path", output_video, | |
"--device", device, | |
"--num_inference_steps", str(num_steps) | |
] | |
subprocess.run(inference_command, check=True) | |
# Return the path to the output video | |
return output_video | |
except subprocess.CalledProcessError as e: | |
raise gr.Error(f"An error occurred: {str(e)}") | |
with gr.Blocks() as demo: | |
with gr.Column(): | |
gr.Markdown("# Go-With-The-Flow") | |
with gr.Row(): | |
with gr.Column(): | |
input_video = gr.Video(label="Input Video") | |
prompt = gr.Textbox(label="Prompt") | |
submit_btn = gr.Button("Submit") | |
with gr.Column(): | |
output_video = gr.Video(label="Result") | |
submit_btn.click( | |
fn = process_video, | |
inputs = [input_video, prompt], | |
outputs = [output_video] | |
) | |
demo.queue().launch(show_api=False) |