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| import gradio as gr | |
| from generate import generate | |
| def infer(prompt, steps, guidance, frames): | |
| gif_path = generate(prompt, num_frames=frames, steps=steps, guidance=guidance) | |
| return gif_path | |
| with gr.Blocks() as demo: | |
| gr.Markdown("# π AnimateDiff Generator\nEnter a text prompt and get an animated GIF.") | |
| with gr.Row(): | |
| with gr.Column(): | |
| prompt = gr.Textbox(label="Prompt", placeholder="Describe your animation...") | |
| steps = gr.Slider(10, 100, value=25, step=1, label="Inference Steps") | |
| guidance = gr.Slider(1, 15, value=7.5, step=0.5, label="Guidance Scale") | |
| frames = gr.Slider(8, 32, value=16, step=1, label="Number of Frames") | |
| btn = gr.Button("Generate") | |
| with gr.Column(): | |
| output = gr.Video(label="Generated Animation") | |
| btn.click(fn=infer, inputs=[prompt, steps, guidance, frames], outputs=output) | |
| if __name__ == "__main__": | |
| demo.launch() | |