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#!/usr/bin/env python
from __future__ import annotations
import os
import pathlib
import shlex
import subprocess
import gradio as gr
# base_url = 'https://huggingface.co/lllyasviel/ControlNet/resolve/main/annotator/ckpts/'
# names = [
# 'body_pose_model.pth',
# 'dpt_hybrid-midas-501f0c75.pt',
# 'hand_pose_model.pth',
# 'mlsd_large_512_fp32.pth',
# 'mlsd_tiny_512_fp32.pth',
# 'network-bsds500.pth',
# 'upernet_global_small.pth',
# ]
# for name in names:
# command = f'wget https://huggingface.co/lllyasviel/ControlNet/resolve/main/annotator/ckpts/{name} -O {name}'
# out_path = pathlib.Path(f'ControlNet/annotator/ckpts/{name}')
# if out_path.exists():
# continue
# subprocess.run(shlex.split(command), cwd='ControlNet/annotator/ckpts/')
from gradio_sketch import create_demo as create_demo_sketch
from gradio_pose import create_demo as create_demo_pose
from gradio_seg import create_demo as create_demo_seg
from model import Model
MAX_IMAGES = 1
description = '''This is an unofficial demo for T2I-Adapter. [Paper](https://arxiv.org/abs/2302.08453) [GitHub](https://github.com/TencentARC/T2I-Adapter)
'''
if (SPACE_ID := os.getenv('SPACE_ID')) is not None:
description += f'''<p>For faster inference without waiting in queue, you may duplicate the space and upgrade to GPU in settings.<br/>
<a href="https://huggingface.co/spaces/{SPACE_ID}?duplicate=true">
<img style="margin-top: 0em; margin-bottom: 0em" src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>
<p/>
'''
model = Model()
with gr.Blocks(css='style.css') as demo:
gr.Markdown("## T2I Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Models.")
gr.Markdown(description)
with gr.Tabs():
with gr.TabItem('Sketch'):
create_demo_sketch(model.process_sketch)
with gr.TabItem('Pose'):
create_demo_pose(model.process_pose)
with gr.TabItem('Segmentation'):
create_demo_seg(model.process_seg)
demo.queue(api_open=False).launch() |