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Create app.py
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app.py
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import gradio as gr
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from modelscope.pipelines import pipeline
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from modelscope.outputs import OutputKeys
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pipe = pipeline(task='image-to-video', model='damo/Image-to-Video', model_revision='v1.1.0')
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def infer (audio_in):
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# IMG_PATH: your image path (url or local file)
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IMG_PATH = audio_in
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output_video_path = pipe(IMG_PATH, output_video='output.mp4')[OutputKeys.OUTPUT_VIDEO]
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print(output_video_path)
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return output_video_path
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css="""
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#col-container {
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max-width: 780px;
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margin-left: auto;
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margin-right: auto;
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}
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img[src*='#center'] {
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display: block;
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margin: auto;
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}
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.footer {
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margin-bottom: 45px;
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margin-top: 10px;
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text-align: center;
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border-bottom: 1px solid #e5e5e5;
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}
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.footer > p {
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font-size: .8rem;
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display: inline-block;
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padding: 0 10px;
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transform: translateY(10px);
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background: white;
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}
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.dark .footer {
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border-color: #303030;
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}
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.dark .footer > p {
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background: #0b0f19;
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}
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"""
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with gr.Blocks(css=css) as demo:
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with gr.Column(elem_id="col-container"):
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gr.Markdown("""
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<h1 style="text-align: center;">
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MS Image2Video
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</h1>
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[![Duplicate this Space](https://huggingface.co/datasets/huggingface/badges/raw/main/duplicate-this-space-sm.svg#center)](https://huggingface.co/spaces/fffiloni/MS-Image2Video-cloning?duplicate=true)
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""")
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image_in = gr.Image(
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label = "Source Image",
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source = "upload",
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type = "filepath"
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)
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submit_btn = gr.Button(
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"Submit"
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)
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video_out = gr.Video(
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label = "Video Result"
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)
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gr.HTML("""
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<div class="footer">
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<p>
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MS-Image2Video Demo by 🤗 <a href="https://twitter.com/fffiloni" target="_blank">Sylvain Filoni</a>
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</p>
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</div>
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""")
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submit_btn.click(
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fn = infer,
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inputs = [
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audio_in
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],
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outputs = [
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video_out
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]
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)
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demo.queue(max_size=20).launch()
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