mirror of
https://github.com/KwaiVGI/LivePortrait.git
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7fda929bf2
* feat: edit * chore: edit * doc: update * doc: update * doc: update * chore: update --------- Co-authored-by: zhangdingyun <zhangdingyun@kuaishou.com>
449 lines
22 KiB
Python
449 lines
22 KiB
Python
# coding: utf-8
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"""
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The entrance of the gradio for human
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"""
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import os
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import tyro
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import subprocess
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import gradio as gr
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import os.path as osp
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from src.utils.helper import load_description
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from src.gradio_pipeline import GradioPipeline
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from src.config.crop_config import CropConfig
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from src.config.argument_config import ArgumentConfig
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from src.config.inference_config import InferenceConfig
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def partial_fields(target_class, kwargs):
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return target_class(**{k: v for k, v in kwargs.items() if hasattr(target_class, k)})
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def fast_check_ffmpeg():
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try:
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subprocess.run(["ffmpeg", "-version"], capture_output=True, check=True)
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return True
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except:
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return False
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# set tyro theme
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tyro.extras.set_accent_color("bright_cyan")
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args = tyro.cli(ArgumentConfig)
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ffmpeg_dir = os.path.join(os.getcwd(), "ffmpeg")
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if osp.exists(ffmpeg_dir):
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os.environ["PATH"] += (os.pathsep + ffmpeg_dir)
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if not fast_check_ffmpeg():
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raise ImportError(
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"FFmpeg is not installed. Please install FFmpeg (including ffmpeg and ffprobe) before running this script. https://ffmpeg.org/download.html"
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)
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# specify configs for inference
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inference_cfg = partial_fields(InferenceConfig, args.__dict__) # use attribute of args to initial InferenceConfig
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crop_cfg = partial_fields(CropConfig, args.__dict__) # use attribute of args to initial CropConfig
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# global_tab_selection = None
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gradio_pipeline = GradioPipeline(
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inference_cfg=inference_cfg,
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crop_cfg=crop_cfg,
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args=args
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)
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if args.gradio_temp_dir not in (None, ''):
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os.environ["GRADIO_TEMP_DIR"] = args.gradio_temp_dir
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os.makedirs(args.gradio_temp_dir, exist_ok=True)
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def gpu_wrapped_execute_video(*args, **kwargs):
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return gradio_pipeline.execute_video(*args, **kwargs)
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def gpu_wrapped_execute_image_retargeting(*args, **kwargs):
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return gradio_pipeline.execute_image_retargeting(*args, **kwargs)
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def gpu_wrapped_execute_video_retargeting(*args, **kwargs):
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return gradio_pipeline.execute_video_retargeting(*args, **kwargs)
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def reset_sliders(*args, **kwargs):
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return 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 2.5, True, True
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# assets
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title_md = "assets/gradio/gradio_title.md"
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example_portrait_dir = "assets/examples/source"
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example_video_dir = "assets/examples/driving"
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data_examples_i2v = [
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[osp.join(example_portrait_dir, "s9.jpg"), osp.join(example_video_dir, "d0.mp4"), True, True, True, False],
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[osp.join(example_portrait_dir, "s6.jpg"), osp.join(example_video_dir, "d0.mp4"), True, True, True, False],
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[osp.join(example_portrait_dir, "s10.jpg"), osp.join(example_video_dir, "d0.mp4"), True, True, True, False],
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[osp.join(example_portrait_dir, "s5.jpg"), osp.join(example_video_dir, "d18.mp4"), True, True, True, False],
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[osp.join(example_portrait_dir, "s7.jpg"), osp.join(example_video_dir, "d19.mp4"), True, True, True, False],
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[osp.join(example_portrait_dir, "s2.jpg"), osp.join(example_video_dir, "d13.mp4"), True, True, True, True],
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]
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data_examples_v2v = [
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[osp.join(example_portrait_dir, "s13.mp4"), osp.join(example_video_dir, "d0.mp4"), True, True, True, False, False, 3e-7],
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# [osp.join(example_portrait_dir, "s14.mp4"), osp.join(example_video_dir, "d18.mp4"), True, True, True, False, False, 3e-7],
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# [osp.join(example_portrait_dir, "s15.mp4"), osp.join(example_video_dir, "d19.mp4"), True, True, True, False, False, 3e-7],
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[osp.join(example_portrait_dir, "s18.mp4"), osp.join(example_video_dir, "d6.mp4"), True, True, True, False, False, 3e-7],
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# [osp.join(example_portrait_dir, "s19.mp4"), osp.join(example_video_dir, "d6.mp4"), True, True, True, False, False, 3e-7],
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[osp.join(example_portrait_dir, "s20.mp4"), osp.join(example_video_dir, "d0.mp4"), True, True, True, False, False, 3e-7],
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]
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#################### interface logic ####################
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# Define components first
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retargeting_source_scale = gr.Number(minimum=1.8, maximum=3.2, value=2.5, step=0.05, label="crop scale")
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video_retargeting_source_scale = gr.Number(minimum=1.8, maximum=3.2, value=2.3, step=0.05, label="crop scale")
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driving_smooth_observation_variance_retargeting = gr.Number(value=3e-6, label="motion smooth strength", minimum=1e-11, maximum=1e-2, step=1e-8)
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eye_retargeting_slider = gr.Slider(minimum=0, maximum=0.8, step=0.01, label="target eyes-open ratio")
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lip_retargeting_slider = gr.Slider(minimum=0, maximum=0.8, step=0.01, label="target lip-open ratio")
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video_lip_retargeting_slider = gr.Slider(minimum=0, maximum=0.8, step=0.01, label="target lip-open ratio")
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head_pitch_slider = gr.Slider(minimum=-15.0, maximum=15.0, value=0, step=1, label="relative pitch")
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head_yaw_slider = gr.Slider(minimum=-25, maximum=25, value=0, step=1, label="relative yaw")
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head_roll_slider = gr.Slider(minimum=-15.0, maximum=15.0, value=0, step=1, label="relative roll")
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mov_x = gr.Slider(minimum=-0.19, maximum=0.19, value=0.0, step=0.01, label="x-axis movement")
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mov_y = gr.Slider(minimum=-0.19, maximum=0.19, value=0.0, step=0.01, label="y-axis movement")
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mov_z = gr.Slider(minimum=0.9, maximum=1.2, value=1.0, step=0.01, label="z-axis movement")
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lip_variation_zero = gr.Slider(minimum=-0.09, maximum=0.09, value=0, step=0.01, label="pouting")
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lip_variation_one = gr.Slider(minimum=-20.0, maximum=15.0, value=0, step=0.01, label="pursing 😐")
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lip_variation_two = gr.Slider(minimum=0.0, maximum=15.0, value=0, step=0.01, label="grin 😁")
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lip_variation_three = gr.Slider(minimum=-90.0, maximum=120.0, value=0, step=1.0, label="lip close <-> open")
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smile = gr.Slider(minimum=-0.3, maximum=1.3, value=0, step=0.01, label="smile 😄")
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wink = gr.Slider(minimum=0, maximum=39, value=0, step=0.01, label="wink 😉")
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eyebrow = gr.Slider(minimum=-30, maximum=30, value=0, step=0.01, label="eyebrow 🤨")
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eyeball_direction_x = gr.Slider(minimum=-30.0, maximum=30.0, value=0, step=0.01, label="eye gaze (horizontal) 👀")
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eyeball_direction_y = gr.Slider(minimum=-63.0, maximum=63.0, value=0, step=0.01, label="eye gaze (vertical) 🙄")
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retargeting_input_image = gr.Image(type="filepath")
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retargeting_input_video = gr.Video()
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output_image = gr.Image(type="numpy")
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output_image_paste_back = gr.Image(type="numpy")
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retargeting_output_image = gr.Image(type="numpy")
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retargeting_output_image_paste_back = gr.Image(type="numpy")
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output_video = gr.Video(autoplay=False)
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output_video_paste_back = gr.Video(autoplay=False)
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output_video_i2v = gr.Video(autoplay=False)
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output_video_concat_i2v = gr.Video(autoplay=False)
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with gr.Blocks(theme=gr.themes.Soft(font=[gr.themes.GoogleFont("Plus Jakarta Sans")])) as demo:
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gr.HTML(load_description(title_md))
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gr.Markdown(load_description("assets/gradio/gradio_description_upload.md"))
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with gr.Row():
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with gr.Column():
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with gr.Tabs():
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with gr.TabItem("🖼️ Source Image") as tab_image:
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with gr.Accordion(open=True, label="Source Image"):
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source_image_input = gr.Image(type="filepath")
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gr.Examples(
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examples=[
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[osp.join(example_portrait_dir, "s9.jpg")],
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[osp.join(example_portrait_dir, "s6.jpg")],
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[osp.join(example_portrait_dir, "s10.jpg")],
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[osp.join(example_portrait_dir, "s5.jpg")],
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[osp.join(example_portrait_dir, "s7.jpg")],
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[osp.join(example_portrait_dir, "s12.jpg")],
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[osp.join(example_portrait_dir, "s22.jpg")],
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[osp.join(example_portrait_dir, "s23.jpg")],
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],
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inputs=[source_image_input],
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cache_examples=False,
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)
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with gr.TabItem("🎞️ Source Video") as tab_video:
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with gr.Accordion(open=True, label="Source Video"):
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source_video_input = gr.Video()
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gr.Examples(
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examples=[
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[osp.join(example_portrait_dir, "s13.mp4")],
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# [osp.join(example_portrait_dir, "s14.mp4")],
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# [osp.join(example_portrait_dir, "s15.mp4")],
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[osp.join(example_portrait_dir, "s18.mp4")],
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# [osp.join(example_portrait_dir, "s19.mp4")],
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[osp.join(example_portrait_dir, "s20.mp4")],
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],
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inputs=[source_video_input],
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cache_examples=False,
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)
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tab_selection = gr.Textbox(visible=False)
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tab_image.select(lambda: "Image", None, tab_selection)
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tab_video.select(lambda: "Video", None, tab_selection)
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with gr.Accordion(open=True, label="Cropping Options for Source Image or Video"):
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with gr.Row():
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flag_do_crop_input = gr.Checkbox(value=True, label="do crop (source)")
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scale = gr.Number(value=2.3, label="source crop scale", minimum=1.8, maximum=3.2, step=0.05)
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vx_ratio = gr.Number(value=0.0, label="source crop x", minimum=-0.5, maximum=0.5, step=0.01)
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vy_ratio = gr.Number(value=-0.125, label="source crop y", minimum=-0.5, maximum=0.5, step=0.01)
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with gr.Column():
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with gr.Accordion(open=True, label="Driving Video"):
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driving_video_input = gr.Video()
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gr.Examples(
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examples=[
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[osp.join(example_video_dir, "d0.mp4")],
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[osp.join(example_video_dir, "d18.mp4")],
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[osp.join(example_video_dir, "d19.mp4")],
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[osp.join(example_video_dir, "d14.mp4")],
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[osp.join(example_video_dir, "d6.mp4")],
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[osp.join(example_video_dir, "d20.mp4")],
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],
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inputs=[driving_video_input],
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cache_examples=False,
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)
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# with gr.Accordion(open=False, label="Animation Instructions"):
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# gr.Markdown(load_description("assets/gradio/gradio_description_animation.md"))
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with gr.Accordion(open=True, label="Cropping Options for Driving Video"):
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with gr.Row():
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flag_crop_driving_video_input = gr.Checkbox(value=False, label="do crop (driving)")
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scale_crop_driving_video = gr.Number(value=2.2, label="driving crop scale", minimum=1.8, maximum=3.2, step=0.05)
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vx_ratio_crop_driving_video = gr.Number(value=0.0, label="driving crop x", minimum=-0.5, maximum=0.5, step=0.01)
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vy_ratio_crop_driving_video = gr.Number(value=-0.1, label="driving crop y", minimum=-0.5, maximum=0.5, step=0.01)
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with gr.Row():
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with gr.Accordion(open=True, label="Animation Options"):
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with gr.Row():
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flag_relative_input = gr.Checkbox(value=True, label="relative motion")
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flag_remap_input = gr.Checkbox(value=True, label="paste-back")
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flag_stitching_input = gr.Checkbox(value=True, label="stitching")
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driving_option_input = gr.Radio(['expression-friendly', 'pose-friendly'], value="expression-friendly", label="driving option (i2v)")
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driving_multiplier = gr.Number(value=1.0, label="driving multiplier (i2v)", minimum=0.0, maximum=2.0, step=0.02)
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flag_video_editing_head_rotation = gr.Checkbox(value=False, label="relative head rotation (v2v)")
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driving_smooth_observation_variance = gr.Number(value=3e-7, label="motion smooth strength (v2v)", minimum=1e-11, maximum=1e-2, step=1e-8)
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gr.Markdown(load_description("assets/gradio/gradio_description_animate_clear.md"))
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with gr.Row():
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process_button_animation = gr.Button("🚀 Animate", variant="primary")
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with gr.Row():
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with gr.Column():
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with gr.Accordion(open=True, label="The animated video in the original image space"):
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output_video_i2v.render()
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with gr.Column():
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with gr.Accordion(open=True, label="The animated video"):
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output_video_concat_i2v.render()
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with gr.Row():
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process_button_reset = gr.ClearButton([source_image_input, source_video_input, driving_video_input, output_video_i2v, output_video_concat_i2v], value="🧹 Clear")
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with gr.Row():
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# Examples
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gr.Markdown("## You could also choose the examples below by one click ⬇️")
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with gr.Row():
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with gr.Tabs():
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with gr.TabItem("🖼️ Portrait Animation"):
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gr.Examples(
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examples=data_examples_i2v,
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fn=gpu_wrapped_execute_video,
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inputs=[
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source_image_input,
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driving_video_input,
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flag_relative_input,
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flag_do_crop_input,
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flag_remap_input,
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flag_crop_driving_video_input,
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],
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outputs=[output_image, output_image_paste_back],
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examples_per_page=len(data_examples_i2v),
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cache_examples=False,
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)
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with gr.TabItem("🎞️ Portrait Video Editing"):
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gr.Examples(
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examples=data_examples_v2v,
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fn=gpu_wrapped_execute_video,
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inputs=[
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source_video_input,
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driving_video_input,
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flag_relative_input,
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flag_do_crop_input,
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flag_remap_input,
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flag_crop_driving_video_input,
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flag_video_editing_head_rotation,
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driving_smooth_observation_variance,
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],
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outputs=[output_image, output_image_paste_back],
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examples_per_page=len(data_examples_v2v),
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cache_examples=False,
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)
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# Retargeting Image
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gr.Markdown(load_description("assets/gradio/gradio_description_retargeting.md"), visible=True)
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with gr.Row(visible=True):
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flag_do_crop_input_retargeting_image = gr.Checkbox(value=True, label="do crop (source)")
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flag_stitching_retargeting_input = gr.Checkbox(value=True, label="stitching")
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retargeting_source_scale.render()
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eye_retargeting_slider.render()
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lip_retargeting_slider.render()
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with gr.Row(visible=True):
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with gr.Column():
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with gr.Accordion(open=True, label="Facial movement sliders"):
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with gr.Row(visible=True):
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head_pitch_slider.render()
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head_yaw_slider.render()
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head_roll_slider.render()
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with gr.Row(visible=True):
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mov_x.render()
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mov_y.render()
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mov_z.render()
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with gr.Column():
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with gr.Accordion(open=True, label="Facial expression sliders"):
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with gr.Row(visible=True):
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lip_variation_zero.render()
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lip_variation_one.render()
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lip_variation_two.render()
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with gr.Row(visible=True):
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lip_variation_three.render()
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smile.render()
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wink.render()
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with gr.Row(visible=True):
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eyebrow.render()
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eyeball_direction_x.render()
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eyeball_direction_y.render()
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with gr.Row(visible=True):
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reset_button = gr.Button("🔄 Reset")
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reset_button.click(
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fn=reset_sliders,
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inputs=None,
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outputs=[
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head_pitch_slider, head_yaw_slider, head_roll_slider, mov_x, mov_y, mov_z,
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lip_variation_zero, lip_variation_one, lip_variation_two, lip_variation_three, smile, wink, eyebrow, eyeball_direction_x, eyeball_direction_y,
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retargeting_source_scale, flag_stitching_retargeting_input, flag_do_crop_input_retargeting_image
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]
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)
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with gr.Row(visible=True):
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with gr.Column():
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with gr.Accordion(open=True, label="Retargeting Image Input"):
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retargeting_input_image.render()
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gr.Examples(
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examples=[
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[osp.join(example_portrait_dir, "s9.jpg")],
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[osp.join(example_portrait_dir, "s6.jpg")],
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[osp.join(example_portrait_dir, "s10.jpg")],
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[osp.join(example_portrait_dir, "s5.jpg")],
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[osp.join(example_portrait_dir, "s7.jpg")],
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[osp.join(example_portrait_dir, "s12.jpg")],
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[osp.join(example_portrait_dir, "s22.jpg")],
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# [osp.join(example_portrait_dir, "s23.jpg")],
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[osp.join(example_portrait_dir, "s42.jpg")],
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],
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inputs=[retargeting_input_image],
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cache_examples=False,
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)
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with gr.Column():
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with gr.Accordion(open=True, label="Retargeting Result"):
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retargeting_output_image.render()
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with gr.Column():
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with gr.Accordion(open=True, label="Paste-back Result"):
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retargeting_output_image_paste_back.render()
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with gr.Row(visible=True):
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process_button_reset_retargeting = gr.ClearButton(
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[
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retargeting_input_image,
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retargeting_output_image,
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retargeting_output_image_paste_back,
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],
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value="🧹 Clear"
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)
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# Retargeting Video
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gr.Markdown(load_description("assets/gradio/gradio_description_retargeting_video.md"), visible=True)
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with gr.Row(visible=True):
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flag_do_crop_input_retargeting_video = gr.Checkbox(value=True, label="do crop (source)")
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video_retargeting_source_scale.render()
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video_lip_retargeting_slider.render()
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driving_smooth_observation_variance_retargeting.render()
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with gr.Row(visible=True):
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process_button_retargeting_video = gr.Button("🚗 Retargeting Video", variant="primary")
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with gr.Row(visible=True):
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with gr.Column():
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with gr.Accordion(open=True, label="Retargeting Video Input"):
|
|
retargeting_input_video.render()
|
|
gr.Examples(
|
|
examples=[
|
|
[osp.join(example_portrait_dir, "s13.mp4")],
|
|
# [osp.join(example_portrait_dir, "s18.mp4")],
|
|
[osp.join(example_portrait_dir, "s20.mp4")],
|
|
[osp.join(example_portrait_dir, "s29.mp4")],
|
|
[osp.join(example_portrait_dir, "s32.mp4")],
|
|
],
|
|
inputs=[retargeting_input_video],
|
|
cache_examples=False,
|
|
)
|
|
with gr.Column():
|
|
with gr.Accordion(open=True, label="Retargeting Result"):
|
|
output_video.render()
|
|
with gr.Column():
|
|
with gr.Accordion(open=True, label="Paste-back Result"):
|
|
output_video_paste_back.render()
|
|
with gr.Row(visible=True):
|
|
process_button_reset_retargeting = gr.ClearButton(
|
|
[
|
|
video_lip_retargeting_slider,
|
|
retargeting_input_video,
|
|
output_video,
|
|
output_video_paste_back
|
|
],
|
|
value="🧹 Clear"
|
|
)
|
|
|
|
# binding functions for buttons
|
|
process_button_animation.click(
|
|
fn=gpu_wrapped_execute_video,
|
|
inputs=[
|
|
source_image_input,
|
|
source_video_input,
|
|
driving_video_input,
|
|
flag_relative_input,
|
|
flag_do_crop_input,
|
|
flag_remap_input,
|
|
flag_stitching_input,
|
|
driving_option_input,
|
|
driving_multiplier,
|
|
flag_crop_driving_video_input,
|
|
flag_video_editing_head_rotation,
|
|
scale,
|
|
vx_ratio,
|
|
vy_ratio,
|
|
scale_crop_driving_video,
|
|
vx_ratio_crop_driving_video,
|
|
vy_ratio_crop_driving_video,
|
|
driving_smooth_observation_variance,
|
|
tab_selection,
|
|
],
|
|
outputs=[output_video_i2v, output_video_concat_i2v],
|
|
show_progress=True
|
|
)
|
|
|
|
retargeting_input_image.change(
|
|
fn=gradio_pipeline.init_retargeting_image,
|
|
inputs=[retargeting_source_scale, eye_retargeting_slider, lip_retargeting_slider, retargeting_input_image],
|
|
outputs=[eye_retargeting_slider, lip_retargeting_slider]
|
|
)
|
|
|
|
sliders = [eye_retargeting_slider, lip_retargeting_slider, head_pitch_slider, head_yaw_slider, head_roll_slider, mov_x, mov_y, mov_z, lip_variation_zero, lip_variation_one, lip_variation_two, lip_variation_three, smile, wink, eyebrow, eyeball_direction_x, eyeball_direction_y]
|
|
for slider in sliders:
|
|
# NOTE: gradio >= 4.0.0 may cause slow response
|
|
slider.change(
|
|
fn=gpu_wrapped_execute_image_retargeting,
|
|
inputs=[
|
|
eye_retargeting_slider, lip_retargeting_slider, head_pitch_slider, head_yaw_slider, head_roll_slider, mov_x, mov_y, mov_z,
|
|
lip_variation_zero, lip_variation_one, lip_variation_two, lip_variation_three, smile, wink, eyebrow, eyeball_direction_x, eyeball_direction_y,
|
|
retargeting_input_image, retargeting_source_scale, flag_stitching_retargeting_input, flag_do_crop_input_retargeting_image
|
|
],
|
|
outputs=[retargeting_output_image, retargeting_output_image_paste_back],
|
|
)
|
|
|
|
process_button_retargeting_video.click(
|
|
fn=gpu_wrapped_execute_video_retargeting,
|
|
inputs=[video_lip_retargeting_slider, retargeting_input_video, video_retargeting_source_scale, driving_smooth_observation_variance_retargeting, flag_do_crop_input_retargeting_video],
|
|
outputs=[output_video, output_video_paste_back],
|
|
show_progress=True
|
|
)
|
|
|
|
demo.launch(
|
|
server_port=args.server_port,
|
|
share=args.share,
|
|
server_name=args.server_name
|
|
)
|