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import PIL | |
import torch | |
import gradio as gr | |
import os | |
from process import load_seg_model, get_palette, generate_mask | |
device = 'cpu' | |
def read_content(file_path: str) -> str: | |
"""read the content of target file | |
""" | |
with open(file_path, 'r', encoding='utf-8') as f: | |
content = f.read() | |
return content | |
def initialize_and_load_models(): | |
checkpoint_path = 'model/cloth_segm.pth' | |
net = load_seg_model(checkpoint_path, device=device) | |
return net | |
net = initialize_and_load_models() | |
palette = get_palette(4) | |
def run(img): | |
cloth_seg = generate_mask(img, net=net, palette=palette, device=device) | |
return cloth_seg | |
# Define input and output interfaces | |
input_image = gr.inputs.Image(label="Input Image", type="pil") | |
# Define the Gradio interface | |
cloth_seg_image = gr.outputs.Image(label="Cloth Segmentation", type="pil") | |
title = "Demo for Cloth Segmentation" | |
description = "An app for Cloth Segmentation" | |
inputs = [input_image] | |
outputs = [cloth_seg_image] | |
css = ''' | |
.container {max-width: 1150px;margin: auto;padding-top: 1.5rem} | |
#image_upload{min-height:400px} | |
#image_upload [data-testid="image"], #image_upload [data-testid="image"] > div{min-height: 400px} | |
#mask_radio .gr-form{background:transparent; border: none} | |
#word_mask{margin-top: .75em !important} | |
#word_mask textarea:disabled{opacity: 0.3} | |
.footer {margin-bottom: 45px;margin-top: 35px;text-align: center;border-bottom: 1px solid #e5e5e5} | |
.footer>p {font-size: .8rem; display: inline-block; padding: 0 10px;transform: translateY(10px);background: white} | |
.dark .footer {border-color: #303030} | |
.dark .footer>p {background: #0b0f19} | |
.acknowledgments h4{margin: 1.25em 0 .25em 0;font-weight: bold;font-size: 115%} | |
#image_upload .touch-none{display: flex} | |
@keyframes spin { | |
from { | |
transform: rotate(0deg); | |
} | |
to { | |
transform: rotate(360deg); | |
} | |
} | |
#share-btn-container { | |
display: flex; padding-left: 0.5rem !important; padding-right: 0.5rem !important; background-color: #000000; justify-content: center; align-items: center; border-radius: 9999px !important; width: 13rem; | |
} | |
#share-btn { | |
all: initial; color: #ffffff;font-weight: 600; cursor:pointer; font-family: 'IBM Plex Sans', sans-serif; margin-left: 0.5rem !important; padding-top: 0.25rem !important; padding-bottom: 0.25rem !important; | |
} | |
#share-btn * { | |
all: unset; | |
} | |
#share-btn-container div:nth-child(-n+2){ | |
width: auto !important; | |
min-height: 0px !important; | |
} | |
#share-btn-container .wrap { | |
display: none !important; | |
} | |
''' | |
example={} | |
image_dir='input' | |
image_list=[os.path.join(image_dir,file) for file in os.listdir(image_dir)] | |
image_list.sort() | |
image_blocks = gr.Blocks(css=css) | |
with image_blocks as demo: | |
gr.HTML(read_content("header.html")) | |
with gr.Group(): | |
with gr.Box(): | |
with gr.Row(): | |
with gr.Column(): | |
image = gr.Image(source='upload', elem_id="image_upload", type="pil", label="Input Image") | |
with gr.Column(): | |
image_out = gr.Image(label="Output", elem_id="output-img").style(height=400) | |
with gr.Row(): | |
with gr.Column(): | |
gr.Examples(image_list, inputs=[image],label="Examples - Input Images",examples_per_page=12) | |
with gr.Column(): | |
with gr.Row(elem_id="prompt-container").style(mobile_collapse=False, equal_height=True): | |
btn = gr.Button("Run!").style( | |
margin=False, | |
rounded=(False, True, True, False), | |
full_width=True, | |
) | |
btn.click(fn=run, inputs=[image], outputs=[image_out]) | |
gr.HTML( | |
""" | |
<div class="footer"> | |
<p>Model by <a href="" style="text-decoration: underline;" target="_blank">WildOctopus</a> - Gradio Demo by π€ Hugging Face | |
</p> | |
</div> | |
<div class="acknowledgments"> | |
<p><h4>ACKNOWLEDGEMENTS</h4></p> | |
<p> | |
U2net model is from original u2net repo. Thanks to <a href="https://github.com/xuebinqin/U-2-Net" style="text-decoration: underline;" target="_blank">Xuebin Qin</a> for amazing repo.</p> | |
<p>Codes are modified from <a href="https://github.com/levindabhi/cloth-segmentation" style="text-decoration: underline;" target="_blank">levindabhi/cloth-segmentation</a> | |
</p> | |
""" | |
) | |
image_blocks.launch() |