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| # Copyright 2023 ByteDance and/or its affiliates. | |
| # | |
| # Copyright (2023) MagicAnimate Authors | |
| # | |
| # ByteDance, its affiliates and licensors retain all intellectual | |
| # property and proprietary rights in and to this material, related | |
| # documentation and any modifications thereto. Any use, reproduction, | |
| # disclosure or distribution of this material and related documentation | |
| # without an express license agreement from ByteDance or | |
| # its affiliates is strictly prohibited. | |
| import argparse | |
| import imageio | |
| import numpy as np | |
| import gradio as gr | |
| from PIL import Image | |
| from subprocess import PIPE, run | |
| from demo.animate import MagicAnimate | |
| animator = MagicAnimate() | |
| def animate(reference_image, motion_sequence_state, seed, steps, guidance_scale): | |
| return animator(reference_image, motion_sequence_state, seed, steps, guidance_scale) | |
| with gr.Blocks() as demo: | |
| gr.HTML( | |
| """ | |
| <div style="text-align: center; max-width: 1200px; margin: 20px auto;"> | |
| <h1 style="font-weight: 800; font-size: 2rem; margin: 0rem"> | |
| MagicAnimate: Temporally Consistent Human Image Animation | |
| </h1> | |
| <br> | |
| <h2 style="font-weight: 450; font-size: 1rem; margin: 0rem"> | |
| <a href="https://showlab.github.io/magicanimate">Project page</a> | | |
| <a href="https://github.com/magic-research/magic-animate"> GitHub </a> | | |
| <a href="https://arxiv.org/abs/2311.16498"> arXiv </a> | |
| </h2> | |
| </div> | |
| """) | |
| animation = gr.Video(format="mp4", label="Animation Results", autoplay=True) | |
| with gr.Row(): | |
| reference_image = gr.Image(label="Reference Image") | |
| motion_sequence = gr.Video(format="mp4", label="Motion Sequence") | |
| with gr.Column(): | |
| random_seed = gr.Textbox(label="Random seed", value=1, info="default: -1") | |
| sampling_steps = gr.Textbox(label="Sampling steps", value=25, info="default: 25") | |
| guidance_scale = gr.Textbox(label="Guidance scale", value=7.5, info="default: 7.5") | |
| submit = gr.Button("Animate") | |
| def read_video(video): | |
| size = int(size) | |
| reader = imageio.get_reader(video) | |
| fps = reader.get_meta_data()['fps'] | |
| assert fps == 25.0, f'Expected video fps: 25, but {fps} fps found' | |
| return video | |
| def read_image(image, size=512): | |
| return np.array(Image.fromarray(image).resize((size, size))) | |
| # when user uploads a new video | |
| motion_sequence.upload( | |
| read_video, | |
| motion_sequence, | |
| motion_sequence | |
| ) | |
| # when `first_frame` is updated | |
| reference_image.upload( | |
| read_image, | |
| reference_image, | |
| reference_image | |
| ) | |
| # when the `submit` button is clicked | |
| submit.click( | |
| animate, | |
| [reference_image, motion_sequence, random_seed, sampling_steps, guidance_scale], | |
| animation | |
| ) | |
| # Examples | |
| gr.Markdown("## Examples") | |
| gr.Examples( | |
| examples=[ | |
| ["inputs/applications/source_image/monalisa.png", "inputs/applications/driving/densepose/running.mp4"], | |
| ["inputs/applications/source_image/demo4.png", "inputs/applications/driving/densepose/demo4.mp4"], | |
| ["inputs/applications/source_image/0002.png", "inputs/applications/driving/densepose/demo4.mp4"], | |
| ["inputs/applications/source_image/dalle2.jpeg", "inputs/applications/driving/densepose/running2.mp4"], | |
| ["inputs/applications/source_image/dalle8.jpeg", "inputs/applications/driving/densepose/dancing2.mp4"], | |
| ["inputs/applications/source_image/multi1_source.png", "inputs/applications/driving/densepose/multi_dancing.mp4"], | |
| ], | |
| inputs=[reference_image, motion_sequence], | |
| outputs=animation, | |
| ) | |
| demo.launch(share=True) |