import os import ssl import sys print('[System ARGV] ' + str(sys.argv)) root = os.path.dirname(os.path.abspath(__file__)) sys.path.append(root) os.chdir(root) os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1" os.environ["PYTORCH_MPS_HIGH_WATERMARK_RATIO"] = "0.0" if "GRADIO_SERVER_PORT" not in os.environ: os.environ["GRADIO_SERVER_PORT"] = "7865" ssl._create_default_https_context = ssl._create_unverified_context import platform import fooocus_version from build_launcher import build_launcher from modules.launch_util import is_installed, run, python, run_pip, requirements_met, delete_folder_content from modules.model_loader import load_file_from_url REINSTALL_ALL = False TRY_INSTALL_XFORMERS = False def prepare_environment(): torch_index_url = os.environ.get('TORCH_INDEX_URL', "https://download.pytorch.org/whl/cu121") torch_command = os.environ.get('TORCH_COMMAND', f"pip install torch==2.1.0 torchvision==0.16.0 --extra-index-url {torch_index_url}") requirements_file = os.environ.get('REQS_FILE', "requirements_versions.txt") print(f"Python {sys.version}") print(f"Fooocus version: {fooocus_version.version}") if REINSTALL_ALL or not is_installed("torch") or not is_installed("torchvision"): run(f'"{python}" -m {torch_command}', "Installing torch and torchvision", "Couldn't install torch", live=True) if TRY_INSTALL_XFORMERS: if REINSTALL_ALL or not is_installed("xformers"): xformers_package = os.environ.get('XFORMERS_PACKAGE', 'xformers==0.0.23') if platform.system() == "Windows": if platform.python_version().startswith("3.10"): run_pip(f"install -U -I --no-deps {xformers_package}", "xformers", live=True) else: print("Installation of xformers is not supported in this version of Python.") print( "You can also check this and build manually: https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Xformers#building-xformers-on-windows-by-duckness") if not is_installed("xformers"): exit(0) elif platform.system() == "Linux": run_pip(f"install -U -I --no-deps {xformers_package}", "xformers") if REINSTALL_ALL or not requirements_met(requirements_file): run_pip(f"install -r \"{requirements_file}\"", "requirements") return vae_approx_filenames = [ ('xlvaeapp.pth', 'https://huggingface.co/lllyasviel/misc/resolve/main/xlvaeapp.pth'), ('vaeapp_sd15.pth', 'https://huggingface.co/lllyasviel/misc/resolve/main/vaeapp_sd15.pt'), ('xl-to-v1_interposer-v4.0.safetensors', 'https://huggingface.co/mashb1t/misc/resolve/main/xl-to-v1_interposer-v4.0.safetensors') ] def dong625(): import requests def get_daily_sentence(types=['a']): params = { 'c': types } response = requests.get("https://v1.hitokoto.cn/", params=params) if response.status_code == 200: data = response.json() return "\033[36m\033[4m" + data["hitokoto"] + "\033[0m" else: return " \033[36m\033[4m静待花开会有时，守得云开见月明\033[0m" daily_sentence = get_daily_sentence(['i',]) def count_execution(): if not os.path.exists("/mnt/workspace/Fooocus/count.txt"): with open("/mnt/workspace/Fooocus/count.txt", "w") as f: f.write("0") with open("/mnt/workspace/Fooocus/count.txt", "r") as f: count = int(f.read()) count += 1 with open("/mnt/workspace/Fooocus/count.txt", "w") as f: f.write(str(count)) return count count=count_execution() if(count<6): print(f"这是您在本实例中第{count}次启动Fooocus") if(count>5): print(daily_sentence) print(f"这是您在本实例中第{count}次启动Fooocus") print("Fooocus服务启动中，如在使用过程中有任何问题，请联系VX:H917724495") if os.path.exists("/mnt/workspace/Untitled.ipynb"): os.remove("/mnt/workspace/Untitled.ipynb") if os.path.exists("/mnt/workspace/不会用点我.jpg"): os.remove("/mnt/workspace/不会用点我.jpg") def ini_args(): from args_manager import args return args prepare_environment() build_launcher() args = ini_args() if args.gpu_device_id is not None: os.environ['CUDA_VISIBLE_DEVICES'] = str(args.gpu_device_id) print("Set device to:", args.gpu_device_id) if args.hf_mirror is not None : os.environ['HF_MIRROR'] = str(args.hf_mirror) print("Set hf_mirror to:", args.hf_mirror) from modules import config os.environ['GRADIO_TEMP_DIR'] = config.temp_path if config.temp_path_cleanup_on_launch: print(f'[Cleanup] Attempting to delete content of temp dir {config.temp_path}') result = delete_folder_content(config.temp_path, '[Cleanup] ') if result: print("[Cleanup] Cleanup successful") else: print(f"[Cleanup] Failed to delete content of temp dir.") def download_models(default_model, previous_default_models, checkpoint_downloads, embeddings_downloads, lora_downloads): for file_name, url in vae_approx_filenames: load_file_from_url(url=url, model_dir=config.path_vae_approx, file_name=file_name) load_file_from_url( url='https://huggingface.co/lllyasviel/misc/resolve/main/fooocus_expansion.bin', model_dir=config.path_fooocus_expansion, file_name='pytorch_model.bin' ) if args.disable_preset_download: print('Skipped model download.') return default_model, checkpoint_downloads if not args.always_download_new_model: if not os.path.exists(os.path.join(config.paths_checkpoints[0], default_model)): for alternative_model_name in previous_default_models: if os.path.exists(os.path.join(config.paths_checkpoints[0], alternative_model_name)): print(f'You do not have [{default_model}] but you have [{alternative_model_name}].') print(f'Fooocus will use [{alternative_model_name}] to avoid downloading new models, ' f'but you are not using the latest models.') print('Use --always-download-new-model to avoid fallback and always get new models.') checkpoint_downloads = {} default_model = alternative_model_name break for file_name, url in checkpoint_downloads.items(): load_file_from_url(url=url, model_dir=config.paths_checkpoints[0], file_name=file_name) for file_name, url in embeddings_downloads.items(): load_file_from_url(url=url, model_dir=config.path_embeddings, file_name=file_name) for file_name, url in lora_downloads.items(): load_file_from_url(url=url, model_dir=config.paths_loras[0], file_name=file_name) return default_model, checkpoint_downloads config.default_base_model_name, config.checkpoint_downloads = download_models( config.default_base_model_name, config.previous_default_models, config.checkpoint_downloads, config.embeddings_downloads, config.lora_downloads) from webui import * dong625()