| import gradio as gr |
| from model import Model |
|
|
| def create_demo(model: Model): |
|
|
| examples = [ |
| ["__assets__/canny_videos_edge/butterfly.mp4", "white butterfly, a high-quality, detailed, and professional photo"], |
| ["__assets__/canny_videos_edge/deer.mp4", "oil painting of a deer, a high-quality, detailed, and professional photo"], |
| ["__assets__/canny_videos_edge/fox.mp4", "wild red fox is walking on the grass, a high-quality, detailed, and professional photo"], |
| ["__assets__/canny_videos_edge/girl_dancing.mp4", "oil painting of a girl dancing close-up, masterpiece, a high-quality, detailed, and professional photo"], |
| ["__assets__/canny_videos_edge/girl_turning.mp4", "oil painting of a beautiful girl, a high-quality, detailed, and professional photo"], |
| ["__assets__/canny_videos_edge/halloween.mp4", "beautiful girl halloween style, a high-quality, detailed, and professional photo"], |
| ["__assets__/canny_videos_edge/santa.mp4", "a santa claus, a high-quality, detailed, and professional photo"], |
| ] |
|
|
| with gr.Blocks() as demo: |
| with gr.Row(): |
| gr.Markdown('## Text and Canny-Edge Conditional Video Generation') |
| with gr.Row(): |
| gr.HTML( |
| """ |
| <div style="text-align: left; auto;"> |
| <h2 style="font-weight: 450; font-size: 1rem; margin: 0rem"> |
| Description: For performance purposes, our current preview release supports any input videos but caps output videos to no longer than 15 seconds and the input videos are scaled down before processing. |
| </h3> |
| </div> |
| """) |
|
|
| with gr.Row(): |
| with gr.Column(): |
| input_video = gr.Video(label="Input Video",source='upload', format="mp4", visible=True).style(height="auto") |
| with gr.Column(): |
| prompt = gr.Textbox(label='Prompt') |
| run_button = gr.Button(label='Run') |
| with gr.Column(): |
| result = gr.Video(label="Generated Video").style(height="auto") |
|
|
| inputs = [ |
| input_video, |
| prompt, |
| ] |
|
|
| gr.Examples(examples=examples, |
| inputs=inputs, |
| outputs=result, |
| fn=model.process_controlnet_canny, |
| cache_examples = True, |
| run_on_click=False, |
| ) |
|
|
| run_button.click(fn=model.process_controlnet_canny, |
| inputs=inputs, |
| outputs=result,) |
| return demo |
|
|