#!/usr/bin/env python from __future__ import annotations import os import pathlib import shlex import subprocess import gradio as gr if os.getenv('SYSTEM') == 'spaces': with open('patch') as f: subprocess.run(shlex.split('patch -p1'), stdin=f, cwd='ControlNet') 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 app_canny import create_demo as create_demo_canny from app_depth import create_demo as create_demo_depth from app_fake_scribble import create_demo as create_demo_fake_scribble from app_hed import create_demo as create_demo_hed from app_hough import create_demo as create_demo_hough from app_normal import create_demo as create_demo_normal from app_pose import create_demo as create_demo_pose from app_scribble import create_demo as create_demo_scribble from app_scribble_interactive import \ create_demo as create_demo_scribble_interactive from app_seg import create_demo as create_demo_seg from model import Model DESCRIPTION = '''# ControlNet This is an unofficial demo for [https://github.com/lllyasviel/ControlNet](https://github.com/lllyasviel/ControlNet). If you are interested in trying out other base models, check out [this Space](https://huggingface.co/spaces/hysts/ControlNet-with-other-models) as well. ''' if (SPACE_ID := os.getenv('SPACE_ID')) is not None: DESCRIPTION += f'''

For faster inference without waiting in queue, you may duplicate the space and upgrade to GPU in settings.
Duplicate Space

''' MAX_IMAGES = int(os.getenv('MAX_IMAGES', '3')) DEFAULT_NUM_IMAGES = min(MAX_IMAGES, int(os.getenv('DEFAULT_NUM_IMAGES', '1'))) model = Model() with gr.Blocks(css='style.css') as demo: gr.Markdown(DESCRIPTION) with gr.Tabs(): with gr.TabItem('Canny'): create_demo_canny(model.process_canny, max_images=MAX_IMAGES, default_num_images=DEFAULT_NUM_IMAGES) with gr.TabItem('Hough'): create_demo_hough(model.process_hough, max_images=MAX_IMAGES, default_num_images=DEFAULT_NUM_IMAGES) with gr.TabItem('HED'): create_demo_hed(model.process_hed, max_images=MAX_IMAGES, default_num_images=DEFAULT_NUM_IMAGES) with gr.TabItem('Scribble'): create_demo_scribble(model.process_scribble, max_images=MAX_IMAGES, default_num_images=DEFAULT_NUM_IMAGES) with gr.TabItem('Scribble Interactive'): create_demo_scribble_interactive( model.process_scribble_interactive, max_images=MAX_IMAGES, default_num_images=DEFAULT_NUM_IMAGES) with gr.TabItem('Fake Scribble'): create_demo_fake_scribble(model.process_fake_scribble, max_images=MAX_IMAGES, default_num_images=DEFAULT_NUM_IMAGES) with gr.TabItem('Pose'): create_demo_pose(model.process_pose, max_images=MAX_IMAGES, default_num_images=DEFAULT_NUM_IMAGES) with gr.TabItem('Segmentation'): create_demo_seg(model.process_seg, max_images=MAX_IMAGES, default_num_images=DEFAULT_NUM_IMAGES) with gr.TabItem('Depth'): create_demo_depth(model.process_depth, max_images=MAX_IMAGES, default_num_images=DEFAULT_NUM_IMAGES) with gr.TabItem('Normal map'): create_demo_normal(model.process_normal, max_images=MAX_IMAGES, default_num_images=DEFAULT_NUM_IMAGES) demo.queue(api_open=False).launch()