Spaces:
Running
Running
File size: 7,891 Bytes
db75512 42046e4 db75512 37c98fe db75512 37c98fe db75512 42046e4 db75512 37c98fe db75512 42046e4 db75512 713078e 42046e4 713078e db75512 42046e4 db75512 713078e 42046e4 713078e db75512 713078e db75512 37c98fe db75512 42046e4 37c98fe db75512 42046e4 db75512 42046e4 db75512 37c98fe db75512 42046e4 37c98fe db75512 42046e4 db75512 42046e4 db75512 37c98fe db75512 37c98fe db75512 |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 |
#!/usr/bin/env python
from __future__ import annotations
import argparse
import pathlib
import tarfile
import gradio as gr
from model import AppDetModel, AppPoseModel
DESCRIPTION = '''# ViTPose
This is an unofficial demo for [https://github.com/ViTAE-Transformer/ViTPose](https://github.com/ViTAE-Transformer/ViTPose).'''
FOOTER = '<img id="visitor-badge" alt="visitor badge" src="https://visitor-badge.glitch.me/badge?page_id=hysts.vitpose" />'
def parse_args() -> argparse.Namespace:
parser = argparse.ArgumentParser()
parser.add_argument('--device', type=str, default='cpu')
parser.add_argument('--theme', type=str)
parser.add_argument('--share', action='store_true')
parser.add_argument('--port', type=int)
parser.add_argument('--disable-queue',
dest='enable_queue',
action='store_false')
return parser.parse_args()
def set_example_image(example: list) -> dict:
return gr.Image.update(value=example[0])
def extract_tar() -> None:
if pathlib.Path('mmdet_configs/configs').exists():
return
with tarfile.open('mmdet_configs/configs.tar') as f:
f.extractall('mmdet_configs')
def main():
args = parse_args()
extract_tar()
det_model = AppDetModel(device=args.device)
pose_model = AppPoseModel(device=args.device)
with gr.Blocks(theme=args.theme, css='style.css') as demo:
gr.Markdown(DESCRIPTION)
with gr.Box():
gr.Markdown('## Step 1')
with gr.Row():
with gr.Column():
with gr.Row():
input_image = gr.Image(label='Input Image',
type='numpy')
with gr.Row():
detector_name = gr.Dropdown(list(
det_model.MODEL_DICT.keys()),
value=det_model.model_name,
label='Detector')
with gr.Row():
detect_button = gr.Button(value='Detect')
det_preds = gr.Variable()
with gr.Column():
with gr.Row():
detection_visualization = gr.Image(
label='Detection Result',
type='numpy',
elem_id='det-result')
with gr.Row():
vis_det_score_threshold = gr.Slider(
0,
1,
step=0.05,
value=0.5,
label='Visualization Score Threshold')
with gr.Row():
redraw_det_button = gr.Button(value='Redraw')
with gr.Row():
paths = sorted(pathlib.Path('images').rglob('*.jpg'))
example_images = gr.Dataset(components=[input_image],
samples=[[path.as_posix()]
for path in paths])
with gr.Box():
gr.Markdown('## Step 2')
with gr.Row():
with gr.Column():
with gr.Row():
pose_model_name = gr.Dropdown(
list(pose_model.MODEL_DICT.keys()),
value=pose_model.model_name,
label='Pose Model')
det_score_threshold = gr.Slider(
0,
1,
step=0.05,
value=0.5,
label='Box Score Threshold')
with gr.Row():
predict_button = gr.Button(value='Predict')
pose_preds = gr.Variable()
with gr.Column():
with gr.Row():
pose_visualization = gr.Image(label='Result',
type='numpy',
elem_id='pose-result')
with gr.Row():
vis_kpt_score_threshold = gr.Slider(
0,
1,
step=0.05,
value=0.3,
label='Visualization Score Threshold')
with gr.Row():
vis_dot_radius = gr.Slider(1,
10,
step=1,
value=4,
label='Dot Radius')
with gr.Row():
vis_line_thickness = gr.Slider(1,
10,
step=1,
value=2,
label='Line Thickness')
with gr.Row():
redraw_pose_button = gr.Button(value='Redraw')
gr.Markdown(FOOTER)
detector_name.change(fn=det_model.set_model,
inputs=detector_name,
outputs=None)
detect_button.click(fn=det_model.run,
inputs=[
detector_name,
input_image,
vis_det_score_threshold,
],
outputs=[
det_preds,
detection_visualization,
])
redraw_det_button.click(fn=det_model.visualize_detection_results,
inputs=[
input_image,
det_preds,
vis_det_score_threshold,
],
outputs=detection_visualization)
pose_model_name.change(fn=pose_model.set_model,
inputs=pose_model_name,
outputs=None)
predict_button.click(fn=pose_model.run,
inputs=[
pose_model_name,
input_image,
det_preds,
det_score_threshold,
vis_kpt_score_threshold,
vis_dot_radius,
vis_line_thickness,
],
outputs=[
pose_preds,
pose_visualization,
])
redraw_pose_button.click(fn=pose_model.visualize_pose_results,
inputs=[
input_image,
pose_preds,
vis_kpt_score_threshold,
vis_dot_radius,
vis_line_thickness,
],
outputs=pose_visualization)
example_images.click(
fn=set_example_image,
inputs=example_images,
outputs=input_image,
)
demo.launch(
enable_queue=args.enable_queue,
server_port=args.port,
share=args.share,
)
if __name__ == '__main__':
main()
|