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app.py
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@@ -135,7 +135,7 @@ if __name__ == "__main__":
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['results/dolly_zoom/source.mp4','A firefighter standing in front of a burning forest captured with a dolly zoom.','camera','dolly_zoom/checkpoint'],
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['results/orbit_shot/source.mp4','A micro graden with orbit shot','camera','orbit_shot/checkpoint'],
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['results/walk/source.mp4', 'A elephant walking in desert', 'object', 'walk/checkpoint'],
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['results/santa_dance/source.mp4','A skeleton in suit is dancing with his hands','object','santa_dance/checkpoint'],
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['results/car_turn/source.mp4','A toy train chugs around a roundabout tree','object','car_turn/checkpoint'],
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['results/train_ride/source.mp4','A motorbike driving in a forest','object','train_ride/checkpoint'],
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@@ -186,6 +186,7 @@ if __name__ == "__main__":
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</script>
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""",
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) as demo:
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gr.Markdown(
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"""
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# Motion Inversion for Video Customization
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@@ -225,5 +226,10 @@ if __name__ == "__main__":
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checkpoint_dropdown.change(fn=update_preview_video, inputs=checkpoint_dropdown, outputs=preview_video)
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inference_button.click(inference_model, inputs=[text_input, checkpoint_dropdown,inference_steps,motion_type, seed], outputs=output_video)
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output_video.change(fn=update_generated_prompt, inputs=[text_input], outputs=generated_prompt)
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['results/dolly_zoom/source.mp4','A firefighter standing in front of a burning forest captured with a dolly zoom.','camera','dolly_zoom/checkpoint'],
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['results/orbit_shot/source.mp4','A micro graden with orbit shot','camera','orbit_shot/checkpoint'],
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# ['results/walk/source.mp4', 'A elephant walking in desert', 'object', 'walk/checkpoint'],
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['results/santa_dance/source.mp4','A skeleton in suit is dancing with his hands','object','santa_dance/checkpoint'],
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['results/car_turn/source.mp4','A toy train chugs around a roundabout tree','object','car_turn/checkpoint'],
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['results/train_ride/source.mp4','A motorbike driving in a forest','object','train_ride/checkpoint'],
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</script>
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""",
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) as demo:
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gr.Markdown(
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"""
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# Motion Inversion for Video Customization
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checkpoint_dropdown.change(fn=update_preview_video, inputs=checkpoint_dropdown, outputs=preview_video)
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inference_button.click(inference_model, inputs=[text_input, checkpoint_dropdown,inference_steps,motion_type, seed], outputs=output_video)
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output_video.change(fn=update_generated_prompt, inputs=[text_input], outputs=generated_prompt)
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demo.queue(
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api_open=False,
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).launch(
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server_name="0.0.0.0",
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server_port=7860,
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)
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