Spaces:
Running
on
Zero
Running
on
Zero
File size: 6,008 Bytes
a891a57 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 |
# coding: utf-8
"""
The entrance of the gradio
"""
import tyro
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)})
# set tyro theme
tyro.extras.set_accent_color("bright_cyan")
args = tyro.cli(ArgumentConfig)
# 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
gradio_pipeline = GradioPipeline(
inference_cfg=inference_cfg,
crop_cfg=crop_cfg,
args=args
)
# assets
title_md = "assets/gradio_title.md"
example_portrait_dir = "assets/examples/source"
example_video_dir = "assets/examples/driving"
data_examples = [
[osp.join(example_portrait_dir, "s9.jpg"), osp.join(example_video_dir, "d0.mp4"), True, True, True, True],
[osp.join(example_portrait_dir, "s6.jpg"), osp.join(example_video_dir, "d0.mp4"), True, True, True, True],
[osp.join(example_portrait_dir, "s10.jpg"), osp.join(example_video_dir, "d5.mp4"), True, True, True, True],
[osp.join(example_portrait_dir, "s5.jpg"), osp.join(example_video_dir, "d6.mp4"), True, True, True, True],
[osp.join(example_portrait_dir, "s7.jpg"), osp.join(example_video_dir, "d7.mp4"), True, True, True, True],
]
#################### interface logic ####################
# Define components first
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")
retargeting_input_image = gr.Image(type="numpy")
output_image = gr.Image(type="numpy")
output_image_paste_back = gr.Image(type="numpy")
output_video = gr.Video()
output_video_concat = gr.Video()
with gr.Blocks(theme=gr.themes.Soft()) as demo:
gr.HTML(load_description(title_md))
gr.Markdown(load_description("assets/gradio_description_upload.md"))
with gr.Row():
with gr.Accordion(open=True, label="Source Portrait"):
image_input = gr.Image(type="filepath")
with gr.Accordion(open=True, label="Driving Video"):
video_input = gr.Video()
gr.Markdown(load_description("assets/gradio_description_animation.md"))
with gr.Row():
with gr.Accordion(open=True, label="Animation Options"):
with gr.Row():
flag_relative_input = gr.Checkbox(value=True, label="relative motion")
flag_do_crop_input = gr.Checkbox(value=True, label="do crop")
flag_remap_input = gr.Checkbox(value=True, label="paste-back")
with gr.Row():
with gr.Column():
process_button_animation = gr.Button("🚀 Animate", variant="primary")
with gr.Column():
process_button_reset = gr.ClearButton([image_input, video_input, output_video, output_video_concat], value="🧹 Clear")
with gr.Row():
with gr.Column():
with gr.Accordion(open=True, label="The animated video in the original image space"):
output_video.render()
with gr.Column():
with gr.Accordion(open=True, label="The animated video"):
output_video_concat.render()
with gr.Row():
# Examples
gr.Markdown("## You could choose the examples below ⬇️")
with gr.Row():
gr.Examples(
examples=data_examples,
inputs=[
image_input,
video_input,
flag_relative_input,
flag_do_crop_input,
flag_remap_input
],
examples_per_page=5
)
gr.Markdown(load_description("assets/gradio_description_retargeting.md"))
with gr.Row():
eye_retargeting_slider.render()
lip_retargeting_slider.render()
with gr.Row():
process_button_retargeting = gr.Button("🚗 Retargeting", variant="primary")
process_button_reset_retargeting = gr.ClearButton(
[
eye_retargeting_slider,
lip_retargeting_slider,
retargeting_input_image,
output_image,
output_image_paste_back
],
value="🧹 Clear"
)
with gr.Row():
with gr.Column():
with gr.Accordion(open=True, label="Retargeting Input"):
retargeting_input_image.render()
with gr.Column():
with gr.Accordion(open=True, label="Retargeting Result"):
output_image.render()
with gr.Column():
with gr.Accordion(open=True, label="Paste-back Result"):
output_image_paste_back.render()
# binding functions for buttons
process_button_retargeting.click(
fn=gradio_pipeline.execute_image,
inputs=[eye_retargeting_slider, lip_retargeting_slider],
outputs=[output_image, output_image_paste_back],
show_progress=True
)
process_button_animation.click(
fn=gradio_pipeline.execute_video,
inputs=[
image_input,
video_input,
flag_relative_input,
flag_do_crop_input,
flag_remap_input
],
outputs=[output_video, output_video_concat],
show_progress=True
)
image_input.change(
fn=gradio_pipeline.prepare_retargeting,
inputs=image_input,
outputs=[eye_retargeting_slider, lip_retargeting_slider, retargeting_input_image]
)
##########################################################
demo.launch(
server_name=args.server_name,
server_port=args.server_port,
share=args.share,
)
|