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app.py
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# coding: utf-8
"""
The entrance of the gradio for human
"""
import os
import tyro
import subprocess
import gradio as gr
import os.path as osp
from src.utils.helper import load_description
from src.gradio_pipeline import GradioPipeline
from src.config.crop_config import CropConfig
from src.config.argument_config import ArgumentConfig
from src.config.inference_config import InferenceConfig
def partial_fields(target_class, kwargs):
return target_class(**{k: v for k, v in kwargs.items() if hasattr(target_class, k)})
def fast_check_ffmpeg():
try:
subprocess.run(["ffmpeg", "-version"], capture_output=True, check=True)
return True
except:
return False
# set tyro theme
tyro.extras.set_accent_color("bright_cyan")
args = tyro.cli(ArgumentConfig)
ffmpeg_dir = os.path.join(os.getcwd(), "ffmpeg")
if osp.exists(ffmpeg_dir):
os.environ["PATH"] += (os.pathsep + ffmpeg_dir)
if not fast_check_ffmpeg():
raise ImportError(
"FFmpeg is not installed. Please install FFmpeg (including ffmpeg and ffprobe) before running this script. https://ffmpeg.org/download.html"
)
# specify configs for inference
inference_cfg = partial_fields(InferenceConfig, args.__dict__) # use attribute of args to initial InferenceConfig
crop_cfg = partial_fields(CropConfig, args.__dict__) # use attribute of args to initial CropConfig
# global_tab_selection = None
gradio_pipeline = GradioPipeline(
inference_cfg=inference_cfg,
crop_cfg=crop_cfg,
args=args
)
if args.gradio_temp_dir not in (None, ''):
os.environ["GRADIO_TEMP_DIR"] = args.gradio_temp_dir
os.makedirs(args.gradio_temp_dir, exist_ok=True)
def gpu_wrapped_execute_video(*args, **kwargs):
return gradio_pipeline.execute_video(*args, **kwargs)
def gpu_wrapped_execute_image_retargeting(*args, **kwargs):
return gradio_pipeline.execute_image_retargeting(*args, **kwargs)
def gpu_wrapped_execute_video_retargeting(*args, **kwargs):
return gradio_pipeline.execute_video_retargeting(*args, **kwargs)
def reset_sliders(*args, **kwargs):
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
# assets
title_md = "assets/gradio/gradio_title.md"
example_portrait_dir = "assets/examples/source"
example_video_dir = "assets/examples/driving"
data_examples_i2v = [
[osp.join(example_portrait_dir, "s9.jpg"), osp.join(example_video_dir, "d0.mp4"), True, True, True, False],
[osp.join(example_portrait_dir, "s6.jpg"), osp.join(example_video_dir, "d0.mp4"), True, True, True, False],
[osp.join(example_portrait_dir, "s10.jpg"), osp.join(example_video_dir, "d0.mp4"), True, True, True, False],
[osp.join(example_portrait_dir, "s5.jpg"), osp.join(example_video_dir, "d18.mp4"), True, True, True, False],
[osp.join(example_portrait_dir, "s7.jpg"), osp.join(example_video_dir, "d19.mp4"), True, True, True, False],
[osp.join(example_portrait_dir, "s2.jpg"), osp.join(example_video_dir, "d13.mp4"), True, True, True, True],
]
data_examples_v2v = [
[osp.join(example_portrait_dir, "s13.mp4"), osp.join(example_video_dir, "d0.mp4"), True, True, True, False, 3e-7],
# [osp.join(example_portrait_dir, "s14.mp4"), osp.join(example_video_dir, "d18.mp4"), True, True, True, False, False, 3e-7],
# [osp.join(example_portrait_dir, "s15.mp4"), osp.join(example_video_dir, "d19.mp4"), True, True, True, False, False, 3e-7],
[osp.join(example_portrait_dir, "s18.mp4"), osp.join(example_video_dir, "d6.mp4"), True, True, True, False, 3e-7],
# [osp.join(example_portrait_dir, "s19.mp4"), osp.join(example_video_dir, "d6.mp4"), True, True, True, False, False, 3e-7],
[osp.join(example_portrait_dir, "s20.mp4"), osp.join(example_video_dir, "d0.mp4"), True, True, True, False, 3e-7],
]
#################### interface logic ####################
# Define components first
retargeting_source_scale = gr.Number(minimum=1.8, maximum=3.2, value=2.5, step=0.05, label="crop scale")
video_retargeting_source_scale = gr.Number(minimum=1.8, maximum=3.2, value=2.3, step=0.05, label="crop scale")
driving_smooth_observation_variance_retargeting = gr.Number(value=3e-6, label="motion smooth strength", minimum=1e-11, maximum=1e-2, step=1e-8)
video_retargeting_silence = gr.Checkbox(value=False, label="keeping the lip silent")
eye_retargeting_slider = gr.Slider(minimum=0, maximum=0.8, step=0.01, label="target eyes-open ratio")
lip_retargeting_slider = gr.Slider(minimum=0, maximum=0.8, step=0.01, label="target lip-open ratio")
video_lip_retargeting_slider = gr.Slider(minimum=0, maximum=0.8, step=0.01, label="target lip-open ratio")
head_pitch_slider = gr.Slider(minimum=-15.0, maximum=15.0, value=0, step=1, label="relative pitch")
head_yaw_slider = gr.Slider(minimum=-25, maximum=25, value=0, step=1, label="relative yaw")
head_roll_slider = gr.Slider(minimum=-15.0, maximum=15.0, value=0, step=1, label="relative roll")
mov_x = gr.Slider(minimum=-0.19, maximum=0.19, value=0.0, step=0.01, label="x-axis movement")
mov_y = gr.Slider(minimum=-0.19, maximum=0.19, value=0.0, step=0.01, label="y-axis movement")
mov_z = gr.Slider(minimum=0.9, maximum=1.2, value=1.0, step=0.01, label="z-axis movement")
lip_variation_zero = gr.Slider(minimum=-0.09, maximum=0.09, value=0, step=0.01, label="pouting")
lip_variation_one = gr.Slider(minimum=-20.0, maximum=15.0, value=0, step=0.01, label="pursing 😐")
lip_variation_two = gr.Slider(minimum=0.0, maximum=15.0, value=0, step=0.01, label="grin 😁")
lip_variation_three = gr.Slider(minimum=-90.0, maximum=120.0, value=0, step=1.0, label="lip close <-> open")
smile = gr.Slider(minimum=-0.3, maximum=1.3, value=0, step=0.01, label="smile 😄")
wink = gr.Slider(minimum=0, maximum=39, value=0, step=0.01, label="wink 😉")
eyebrow = gr.Slider(minimum=-30, maximum=30, value=0, step=0.01, label="eyebrow 🤨")
eyeball_direction_x = gr.Slider(minimum=-30.0, maximum=30.0, value=0, step=0.01, label="eye gaze (horizontal) 👀")
eyeball_direction_y = gr.Slider(minimum=-63.0, maximum=63.0, value=0, step=0.01, label="eye gaze (vertical) 🙄")
retargeting_input_image = gr.Image(type="filepath")
retargeting_input_video = gr.Video()
output_image = gr.Image(type="numpy")
output_image_paste_back = gr.Image(type="numpy")
retargeting_output_image = gr.Image(type="numpy")
retargeting_output_image_paste_back = gr.Image(type="numpy")
output_video = gr.Video(autoplay=False)
output_video_paste_back = gr.Video(autoplay=False)
with gr.Blocks(theme=gr.themes.Soft(font=[gr.themes.GoogleFont("Plus Jakarta Sans")])) as demo:
gr.HTML(load_description(title_md))
gr.Markdown(load_description("assets/gradio/gradio_description_upload.md"))
with gr.Row():
with gr.Column():
with gr.Tabs():
with gr.TabItem("🖼️ Source Image") as tab_image:
with gr.Accordion(open=True, label="Source Image"):
source_image_input = gr.Image(type="filepath")
gr.Examples(
examples=[
[osp.join(example_portrait_dir, "s9.jpg")],
[osp.join(example_portrait_dir, "s6.jpg")],
[osp.join(example_portrait_dir, "s10.jpg")],
[osp.join(example_portrait_dir, "s5.jpg")],
[osp.join(example_portrait_dir, "s7.jpg")],
[osp.join(example_portrait_dir, "s12.jpg")],
[osp.join(example_portrait_dir, "s22.jpg")],
[osp.join(example_portrait_dir, "s23.jpg")],
],
inputs=[source_image_input],
cache_examples=False,
)
with gr.TabItem("🎞️ Source Video") as tab_video:
with gr.Accordion(open=True, label="Source Video"):
source_video_input = gr.Video()
gr.Examples(
examples=[
[osp.join(example_portrait_dir, "s13.mp4")],
# [osp.join(example_portrait_dir, "s14.mp4")],
# [osp.join(example_portrait_dir, "s15.mp4")],
[osp.join(example_portrait_dir, "s18.mp4")],
# [osp.join(example_portrait_dir, "s19.mp4")],
[osp.join(example_portrait_dir, "s20.mp4")],
],
inputs=[source_video_input],
cache_examples=False,
)
tab_selection = gr.Textbox(visible=False)
tab_image.select(lambda: "Image", None, tab_selection)
tab_video.select(lambda: "Video", None, tab_selection)
with gr.Accordion(open=True, label="Cropping Options for Source Image or Video"):
with gr.Row():
flag_do_crop_input = gr.Checkbox(value=True, label="do crop (source)")
scale = gr.Number(value=2.3, label="source crop scale", minimum=1.8, maximum=3.2, step=0.05)
vx_ratio = gr.Number(value=0.0, label="source crop x", minimum=-0.5, maximum=0.5, step=0.01)
vy_ratio = gr.Number(value=-0.125, label="source crop y", minimum=-0.5, maximum=0.5, step=0.01)
with gr.Column():
with gr.Tabs():
with gr.TabItem("🎞️ Driving Video") as v_tab_video:
with gr.Accordion(open=True, label="Driving Video"):
driving_video_input = gr.Video()
gr.Examples(
examples=[
[osp.join(example_video_dir, "d0.mp4")],
[osp.join(example_video_dir, "d18.mp4")],
[osp.join(example_video_dir, "d19.mp4")],
[osp.join(example_video_dir, "d14.mp4")],
[osp.join(example_video_dir, "d6.mp4")],
[osp.join(example_video_dir, "d20.mp4")],
],
inputs=[driving_video_input],
cache_examples=False,
)
with gr.TabItem("🖼️ Driving Image") as v_tab_image:
with gr.Accordion(open=True, label="Driving Image"):
driving_image_input = gr.Image(type="filepath")
gr.Examples(
examples=[
[osp.join(example_video_dir, "d30.jpg")],
[osp.join(example_video_dir, "d9.jpg")],
[osp.join(example_video_dir, "d19.jpg")],
[osp.join(example_video_dir, "d8.jpg")],
[osp.join(example_video_dir, "d12.jpg")],
[osp.join(example_video_dir, "d38.jpg")],
],
inputs=[driving_image_input],
cache_examples=False,
)
with gr.TabItem("📁 Driving Pickle") as v_tab_pickle:
with gr.Accordion(open=True, label="Driving Pickle"):
driving_video_pickle_input = gr.File(type="filepath", file_types=[".pkl"])
gr.Examples(
examples=[
[osp.join(example_video_dir, "d1.pkl")],
[osp.join(example_video_dir, "d2.pkl")],
[osp.join(example_video_dir, "d5.pkl")],
[osp.join(example_video_dir, "d7.pkl")],
[osp.join(example_video_dir, "d8.pkl")],
],
inputs=[driving_video_pickle_input],
cache_examples=False,
)
v_tab_selection = gr.Textbox(visible=False)
v_tab_video.select(lambda: "Video", None, v_tab_selection)
v_tab_image.select(lambda: "Image", None, v_tab_selection)
v_tab_pickle.select(lambda: "Pickle", None, v_tab_selection)
# with gr.Accordion(open=False, label="Animation Instructions"):
# gr.Markdown(load_description("assets/gradio/gradio_description_animation.md"))
with gr.Accordion(open=True, label="Cropping Options for Driving Video"):
with gr.Row():
flag_crop_driving_video_input = gr.Checkbox(value=False, label="do crop (driving)")
scale_crop_driving_video = gr.Number(value=2.2, label="driving crop scale", minimum=1.8, maximum=3.2, step=0.05)
vx_ratio_crop_driving_video = gr.Number(value=0.0, label="driving crop x", minimum=-0.5, maximum=0.5, step=0.01)
vy_ratio_crop_driving_video = gr.Number(value=-0.1, label="driving crop y", minimum=-0.5, maximum=0.5, step=0.01)
with gr.Row():
with gr.Accordion(open=True, label="Animation Options"):
with gr.Row():
flag_normalize_lip = gr.Checkbox(value=False, label="normalize lip")
flag_relative_input = gr.Checkbox(value=True, label="relative motion")
flag_remap_input = gr.Checkbox(value=True, label="paste-back")
flag_stitching_input = gr.Checkbox(value=True, label="stitching")
animation_region = gr.Radio(["exp", "pose", "lip", "eyes", "all"], value="all", label="animation region")
driving_option_input = gr.Radio(['expression-friendly', 'pose-friendly'], value="expression-friendly", label="driving option (i2v)")
driving_multiplier = gr.Number(value=1.0, label="driving multiplier (i2v)", minimum=0.0, maximum=2.0, step=0.02)
driving_smooth_observation_variance = gr.Number(value=3e-7, label="motion smooth strength (v2v)", minimum=1e-11, maximum=1e-2, step=1e-8)
gr.Markdown(load_description("assets/gradio/gradio_description_animate_clear.md"))
with gr.Row():
process_button_animation = gr.Button("🚀 Animate", variant="primary")
with gr.Row():
with gr.Column():
output_video_i2v = gr.Video(autoplay=False, label="The animated video in the original image space")
with gr.Column():
output_video_concat_i2v = gr.Video(autoplay=False, label="The animated video")
with gr.Row():
with gr.Column():
output_image_i2i = gr.Image(type="numpy", label="The animated image in the original image space", visible=False)
with gr.Column():
output_image_concat_i2i = gr.Image(type="numpy", label="The animated image", visible=False)
with gr.Row():
process_button_reset = gr.ClearButton([source_image_input, source_video_input, driving_video_pickle_input, driving_video_input, driving_image_input, output_video_i2v, output_video_concat_i2v, output_image_i2i, output_image_concat_i2i], value="🧹 Clear")
with gr.Row():
# Examples
gr.Markdown("## You could also choose the examples below by one click ⬇️")
with gr.Row():
with gr.Tabs():
with gr.TabItem("🖼️ Portrait Animation"):
gr.Examples(
examples=data_examples_i2v,
fn=gpu_wrapped_execute_video,
inputs=[
source_image_input,
driving_video_input,
flag_relative_input,
flag_do_crop_input,
flag_remap_input,
flag_crop_driving_video_input,
],
outputs=[output_image, output_image_paste_back],
examples_per_page=len(data_examples_i2v),
cache_examples=False,
)
with gr.TabItem("🎞️ Portrait Video Editing"):
gr.Examples(
examples=data_examples_v2v,
fn=gpu_wrapped_execute_video,
inputs=[
source_video_input,
driving_video_input,
flag_relative_input,
flag_do_crop_input,
flag_remap_input,
flag_crop_driving_video_input,
driving_smooth_observation_variance,
],
outputs=[output_image, output_image_paste_back],
examples_per_page=len(data_examples_v2v),
cache_examples=False,
)
# Retargeting Image
gr.Markdown(load_description("assets/gradio/gradio_description_retargeting.md"), visible=True)
with gr.Row(visible=True):
flag_do_crop_input_retargeting_image = gr.Checkbox(value=True, label="do crop (source)")
flag_stitching_retargeting_input = gr.Checkbox(value=True, label="stitching")
retargeting_source_scale.render()
eye_retargeting_slider.render()
lip_retargeting_slider.render()
with gr.Row(visible=True):
with gr.Column():
with gr.Accordion(open=True, label="Facial movement sliders"):
with gr.Row(visible=True):
head_pitch_slider.render()
head_yaw_slider.render()
head_roll_slider.render()
with gr.Row(visible=True):
mov_x.render()
mov_y.render()
mov_z.render()
with gr.Column():
with gr.Accordion(open=True, label="Facial expression sliders"):
with gr.Row(visible=True):
lip_variation_zero.render()
lip_variation_one.render()
lip_variation_two.render()
with gr.Row(visible=True):
lip_variation_three.render()
smile.render()
wink.render()
with gr.Row(visible=True):
eyebrow.render()
eyeball_direction_x.render()
eyeball_direction_y.render()
with gr.Row(visible=True):
reset_button = gr.Button("🔄 Reset")
reset_button.click(
fn=reset_sliders,
inputs=None,
outputs=[
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_source_scale, flag_stitching_retargeting_input, flag_do_crop_input_retargeting_image
]
)
with gr.Row(visible=True):
with gr.Column():
with gr.Accordion(open=True, label="Retargeting Image Input"):
retargeting_input_image.render()
gr.Examples(
examples=[
[osp.join(example_portrait_dir, "s9.jpg")],
[osp.join(example_portrait_dir, "s6.jpg")],
[osp.join(example_portrait_dir, "s10.jpg")],
[osp.join(example_portrait_dir, "s5.jpg")],
[osp.join(example_portrait_dir, "s7.jpg")],
[osp.join(example_portrait_dir, "s12.jpg")],
[osp.join(example_portrait_dir, "s22.jpg")],
# [osp.join(example_portrait_dir, "s23.jpg")],
[osp.join(example_portrait_dir, "s42.jpg")],
],
inputs=[retargeting_input_image],
cache_examples=False,
)
with gr.Column():
with gr.Accordion(open=True, label="Retargeting Result"):
retargeting_output_image.render()
with gr.Column():
with gr.Accordion(open=True, label="Paste-back Result"):
retargeting_output_image_paste_back.render()
with gr.Row(visible=True):
process_button_reset_retargeting = gr.ClearButton(
[
retargeting_input_image,
retargeting_output_image,
retargeting_output_image_paste_back,
],
value="🧹 Clear"
)
# Retargeting Video
gr.Markdown(load_description("assets/gradio/gradio_description_retargeting_video.md"), visible=True)
with gr.Row(visible=True):
flag_do_crop_input_retargeting_video = gr.Checkbox(value=True, label="do crop (source)")
video_retargeting_source_scale.render()
video_lip_retargeting_slider.render()
driving_smooth_observation_variance_retargeting.render()
video_retargeting_silence.render()
with gr.Row(visible=True):
process_button_retargeting_video = gr.Button("🚗 Retargeting Video", variant="primary")
with gr.Row(visible=True):
with gr.Column():
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")],
[osp.join(example_video_dir, "d3.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,
driving_image_input,
driving_video_pickle_input,
flag_normalize_lip,
flag_relative_input,
flag_do_crop_input,
flag_remap_input,
flag_stitching_input,
animation_region,
driving_option_input,
driving_multiplier,
flag_crop_driving_video_input,
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,
v_tab_selection,
],
outputs=[output_video_i2v, output_video_i2v, output_video_concat_i2v, output_video_concat_i2v, output_image_i2i, output_image_i2i, output_image_concat_i2i, output_image_concat_i2i],
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, video_retargeting_silence, 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
)