advanced preset load
new model list i new candidates add model fallback allow disable preset download Update anime.json Update anime.json Update config.py Update anime.json Update readme.md Update default.json
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lllyasviel
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ff2187efed
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69ad1b3c24
@ -20,6 +20,12 @@ args_parser.parser.add_argument("--disable-image-log", action='store_true',
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args_parser.parser.add_argument("--disable-analytics", action='store_true',
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help="Disables analytics for Gradio", default=False)
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args_parser.parser.add_argument("--disable-preset-download", action='store_true',
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help="Disables downloading models for presets", default=False)
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args_parser.parser.add_argument("--always-download-new-model", action='store_true',
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help="Always download newer models ", default=False)
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args_parser.parser.set_defaults(
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disable_cuda_malloc=True,
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in_browser=True,
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59
launch.py
59
launch.py
@ -21,8 +21,7 @@ import fooocus_version
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from build_launcher import build_launcher
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from modules.launch_util import is_installed, run, python, run_pip, requirements_met
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from modules.model_loader import load_file_from_url
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from modules.config import path_checkpoints, path_loras, path_vae_approx, path_fooocus_expansion, \
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checkpoint_downloads, path_embeddings, embeddings_downloads, lora_downloads
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from modules import config
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REINSTALL_ALL = False
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@ -70,25 +69,6 @@ vae_approx_filenames = [
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]
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def download_models():
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for file_name, url in checkpoint_downloads.items():
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load_file_from_url(url=url, model_dir=path_checkpoints, file_name=file_name)
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for file_name, url in embeddings_downloads.items():
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load_file_from_url(url=url, model_dir=path_embeddings, file_name=file_name)
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for file_name, url in lora_downloads.items():
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load_file_from_url(url=url, model_dir=path_loras, file_name=file_name)
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for file_name, url in vae_approx_filenames:
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load_file_from_url(url=url, model_dir=path_vae_approx, file_name=file_name)
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load_file_from_url(
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url='https://huggingface.co/lllyasviel/misc/resolve/main/fooocus_expansion.bin',
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model_dir=path_fooocus_expansion,
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file_name='pytorch_model.bin'
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)
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return
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def ini_args():
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from args_manager import args
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return args
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@ -104,6 +84,43 @@ if args.gpu_device_id is not None:
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print("Set device to:", args.gpu_device_id)
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def download_models():
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for file_name, url in vae_approx_filenames:
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load_file_from_url(url=url, model_dir=config.path_vae_approx, file_name=file_name)
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load_file_from_url(
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url='https://huggingface.co/lllyasviel/misc/resolve/main/fooocus_expansion.bin',
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model_dir=config.path_fooocus_expansion,
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file_name='pytorch_model.bin'
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)
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if args.disable_preset_download:
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print('Skipped model download.')
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return
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if not args.always_download_new_model:
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if not os.path.exists(os.path.join(config.path_checkpoints, config.default_base_model_name)):
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for alternative_model_name in config.previous_default_models:
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if os.path.exists(os.path.join(config.path_checkpoints, alternative_model_name)):
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print(f'You do not have [{config.default_base_model_name}] but you have [{alternative_model_name}].')
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print(f'Fooocus will use [{alternative_model_name}] to avoid downloading new models, '
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f'but you are not using latest models.')
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print('Use --always-download-new-model to avoid fallback and always get new models.')
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config.checkpoint_downloads = {}
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config.default_base_model_name = alternative_model_name
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break
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for file_name, url in config.checkpoint_downloads.items():
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load_file_from_url(url=url, model_dir=config.path_checkpoints, file_name=file_name)
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for file_name, url in config.embeddings_downloads.items():
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load_file_from_url(url=url, model_dir=config.path_embeddings, file_name=file_name)
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for file_name, url in config.lora_downloads.items():
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load_file_from_url(url=url, model_dir=config.path_loras, file_name=file_name)
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return
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download_models()
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from webui import *
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@ -79,6 +79,13 @@ def try_load_deprecated_user_path_config():
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try_load_deprecated_user_path_config()
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try:
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with open(os.path.abspath(f'./presets/default.json'), "r", encoding="utf-8") as json_file:
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config_dict.update(json.load(json_file))
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except Exception as e:
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print(f'Load default preset failed.')
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print(e)
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preset = args_manager.args.preset
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if isinstance(preset, str):
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@ -153,9 +160,14 @@ def get_config_item_or_set_default(key, default_value, validator, disable_empty_
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default_base_model_name = get_config_item_or_set_default(
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key='default_model',
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default_value='juggernautXL_version6Rundiffusion.safetensors',
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default_value='model.safetensors',
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validator=lambda x: isinstance(x, str)
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)
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previous_default_models = get_config_item_or_set_default(
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key='previous_default_models',
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default_value=[],
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validator=lambda x: isinstance(x, list) and all(isinstance(k, str) for k in x)
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)
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default_refiner_model_name = get_config_item_or_set_default(
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key='default_refiner',
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default_value='None',
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@ -163,15 +175,15 @@ default_refiner_model_name = get_config_item_or_set_default(
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)
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default_refiner_switch = get_config_item_or_set_default(
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key='default_refiner_switch',
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default_value=0.5,
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default_value=0.8,
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validator=lambda x: isinstance(x, numbers.Number) and 0 <= x <= 1
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)
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default_loras = get_config_item_or_set_default(
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key='default_loras',
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default_value=[
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[
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"sd_xl_offset_example-lora_1.0.safetensors",
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0.1
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"None",
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1.0
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],
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[
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"None",
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@ -194,7 +206,7 @@ default_loras = get_config_item_or_set_default(
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)
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default_cfg_scale = get_config_item_or_set_default(
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key='default_cfg_scale',
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default_value=4.0,
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default_value=7.0,
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validator=lambda x: isinstance(x, numbers.Number)
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)
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default_sample_sharpness = get_config_item_or_set_default(
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@ -255,16 +267,12 @@ default_image_number = get_config_item_or_set_default(
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)
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checkpoint_downloads = get_config_item_or_set_default(
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key='checkpoint_downloads',
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default_value={
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"juggernautXL_version6Rundiffusion.safetensors": "https://huggingface.co/lllyasviel/fav_models/resolve/main/fav/juggernautXL_version6Rundiffusion.safetensors"
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},
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default_value={},
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validator=lambda x: isinstance(x, dict) and all(isinstance(k, str) and isinstance(v, str) for k, v in x.items())
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)
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lora_downloads = get_config_item_or_set_default(
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key='lora_downloads',
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default_value={
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"sd_xl_offset_example-lora_1.0.safetensors": "https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/resolve/main/sd_xl_offset_example-lora_1.0.safetensors"
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},
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default_value={},
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validator=lambda x: isinstance(x, dict) and all(isinstance(k, str) and isinstance(v, str) for k, v in x.items())
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)
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embeddings_downloads = get_config_item_or_set_default(
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