#!/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'])