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import gradio as gr |
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import os |
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from glob import glob |
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from diffusers.utils import load_image |
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import spaces |
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from panna import SVD |
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model = SVD() |
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example_files = [] |
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root_url = "https://huggingface.co/spaces/multimodalart/stable-video-diffusion/resolve/main/images" |
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examples = ["disaster_meme.png", "distracted_meme.png", "hide_meme.png", "success_meme.png", "willy_meme.png", "wink_meme.png"] |
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for example in examples: |
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load_image(f"{root_url}/{example}").save(example) |
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tmp_output_dir = "outputs" |
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os.makedirs(tmp_output_dir, exist_ok=True) |
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title = ("# [Stable Video Diffusion](ttps://huggingface.co/stabilityai/stable-video-diffusion-img2vid-xt)\n" |
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"The demo is part of [panna](https://github.com/abacws-abacus/panna) project.") |
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@spaces.GPU(duration=120) |
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def infer(init_image, motion_bucket_id, noise_aug_strength, decode_chunk_size, fps, seed): |
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base_count = len(glob(os.path.join(tmp_output_dir, "*.mp4"))) |
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video_path = os.path.join(tmp_output_dir, f"{base_count:06d}.mp4") |
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frames = model.image2video( |
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[init_image], |
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motion_bucket_id=motion_bucket_id, |
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noise_aug_strength=noise_aug_strength, |
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decode_chunk_size=decode_chunk_size, |
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fps=fps, |
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seed=seed |
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) |
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model.export(frames[0], video_path, fps) |
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return video_path |
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with gr.Blocks() as demo: |
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gr.Markdown(title) |
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with gr.Row(): |
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with gr.Column(): |
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image = gr.Image(label="Upload your image", type="pil") |
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run_button = gr.Button("Generate", scale=0) |
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video = gr.Video() |
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with gr.Accordion("Advanced options", open=False): |
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seed = gr.Slider(label="Seed", minimum=0, maximum=1_000_000, step=1, value=0) |
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motion_bucket_id = gr.Slider(label="Motion bucket id", minimum=1, maximum=255, step=1, value=127) |
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noise_aug_strength = gr.Slider(label="Noise Strength", minimum=0, maximum=1, step=0.01, value=0.02) |
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fps = gr.Slider(label="Frames per second", minimum=5, maximum=30, step=1, value=6) |
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decode_chunk_size = gr.Slider(label="Frames per second", minimum=1, maximum=10, step=1, value=2) |
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run_button.click( |
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fn=infer, |
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inputs=[image, motion_bucket_id, noise_aug_strength, decode_chunk_size, fps, seed], |
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outputs=[video] |
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) |
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gr.Examples( |
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fn=infer, |
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examples=examples, |
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inputs=image, |
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outputs=[video] |
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) |
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demo.launch() |
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