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#!/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_depth import create_demo as create_demo_depth | |
from model import Model, download_all_controlnet_weights | |
DESCRIPTION = '# RoomGPT <p> Redesign your room using the power of AI</p>' | |
SPACE_ID = os.getenv('SPACE_ID') | |
MAX_IMAGES = 3 | |
DEFAULT_NUM_IMAGES = min(MAX_IMAGES,1) | |
if os.getenv('SYSTEM') == 'spaces': | |
download_all_controlnet_weights() | |
DEFAULT_MODEL_ID = os.getenv('DEFAULT_MODEL_ID', | |
'runwayml/stable-diffusion-v1-5') | |
model = Model(base_model_id=DEFAULT_MODEL_ID) | |
with gr.Blocks(css='style.css') as demo: | |
gr.Markdown(DESCRIPTION) | |
create_demo_depth(model.process_depth, | |
max_images=MAX_IMAGES, | |
default_num_images=DEFAULT_NUM_IMAGES) | |
demo.queue(api_open=False).launch(file_directories=['/tmp']) | |