286 lines
10 KiB
Python
286 lines
10 KiB
Python
import os
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import json
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import args_manager
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import modules.flags
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import modules.sdxl_styles
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from modules.model_loader import load_file_from_url
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from modules.util import get_files_from_folder
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config_path = "user_path_config.txt"
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config_dict = {}
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try:
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if os.path.exists(config_path):
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with open(config_path, "r", encoding="utf-8") as json_file:
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config_dict = json.load(json_file)
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except Exception as e:
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print('Load path config 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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preset = os.path.abspath(f'./presets/{preset}.json')
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try:
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if os.path.exists(preset):
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with open(preset, "r", encoding="utf-8") as json_file:
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preset = json.load(json_file)
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except Exception as e:
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print('Load preset config failed')
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print(e)
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preset = preset if isinstance(preset, dict) else None
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if preset is not None:
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config_dict.update(preset)
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def get_dir_or_set_default(key, default_value):
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global config_dict
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v = config_dict.get(key, None)
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if isinstance(v, str) and os.path.exists(v) and os.path.isdir(v):
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return v
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else:
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dp = os.path.abspath(os.path.join(os.path.dirname(__file__), default_value))
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os.makedirs(dp, exist_ok=True)
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config_dict[key] = dp
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return dp
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modelfile_path = get_dir_or_set_default('modelfile_path', '../models/checkpoints/')
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lorafile_path = get_dir_or_set_default('lorafile_path', '../models/loras/')
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embeddings_path = get_dir_or_set_default('embeddings_path', '../models/embeddings/')
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vae_approx_path = get_dir_or_set_default('vae_approx_path', '../models/vae_approx/')
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upscale_models_path = get_dir_or_set_default('upscale_models_path', '../models/upscale_models/')
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inpaint_models_path = get_dir_or_set_default('inpaint_models_path', '../models/inpaint/')
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controlnet_models_path = get_dir_or_set_default('controlnet_models_path', '../models/controlnet/')
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clip_vision_models_path = get_dir_or_set_default('clip_vision_models_path', '../models/clip_vision/')
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fooocus_expansion_path = get_dir_or_set_default('fooocus_expansion_path',
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'../models/prompt_expansion/fooocus_expansion')
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temp_outputs_path = get_dir_or_set_default('temp_outputs_path', '../outputs/')
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def get_config_item_or_set_default(key, default_value, validator, disable_empty_as_none=False):
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global config_dict
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if key not in config_dict:
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config_dict[key] = default_value
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return default_value
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v = config_dict.get(key, None)
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if not disable_empty_as_none:
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if v is None or v == '':
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v = 'None'
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if validator(v):
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return v
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else:
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config_dict[key] = default_value
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return default_value
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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='sd_xl_base_1.0_0.9vae.safetensors',
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validator=lambda x: isinstance(x, str)
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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='sd_xl_refiner_1.0_0.9vae.safetensors',
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validator=lambda x: isinstance(x, str)
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)
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default_lora_name = get_config_item_or_set_default(
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key='default_lora',
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default_value='sd_xl_offset_example-lora_1.0.safetensors',
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validator=lambda x: isinstance(x, str)
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)
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default_lora_weight = get_config_item_or_set_default(
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key='default_lora_weight',
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default_value=0.5,
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validator=lambda x: isinstance(x, float)
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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=7.0,
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validator=lambda x: isinstance(x, float)
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)
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default_sampler = get_config_item_or_set_default(
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key='default_sampler',
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default_value='dpmpp_2m_sde_gpu',
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validator=lambda x: x in modules.flags.sampler_list
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)
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default_scheduler = get_config_item_or_set_default(
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key='default_scheduler',
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default_value='karras',
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validator=lambda x: x in modules.flags.scheduler_list
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)
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default_styles = get_config_item_or_set_default(
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key='default_styles',
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default_value=['Fooocus V2', 'Default (Slightly Cinematic)'],
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validator=lambda x: isinstance(x, list) and all(y in modules.sdxl_styles.legal_style_names for y in x)
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)
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default_negative_prompt = get_config_item_or_set_default(
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key='default_negative_prompt',
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default_value='low quality, bad hands, bad eyes, cropped, missing fingers, extra digit',
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validator=lambda x: isinstance(x, str),
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disable_empty_as_none=True
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)
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default_positive_prompt = get_config_item_or_set_default(
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key='default_positive_prompt',
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default_value='',
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validator=lambda x: isinstance(x, str),
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disable_empty_as_none=True
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)
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default_advanced_checkbox = get_config_item_or_set_default(
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key='default_advanced_checkbox',
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default_value=False,
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validator=lambda x: isinstance(x, bool)
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)
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default_image_number = get_config_item_or_set_default(
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key='default_image_number',
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default_value=2,
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validator=lambda x: isinstance(x, int) and x >= 1 and x <= 32
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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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'sd_xl_base_1.0_0.9vae.safetensors':
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'https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/resolve/main/sd_xl_base_1.0_0.9vae.safetensors',
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'sd_xl_refiner_1.0_0.9vae.safetensors':
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'https://huggingface.co/stabilityai/stable-diffusion-xl-refiner-1.0/resolve/main/sd_xl_refiner_1.0_0.9vae.safetensors'
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},
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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':
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'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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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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key='embeddings_downloads',
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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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default_aspect_ratio = get_config_item_or_set_default(
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key='default_aspect_ratio',
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default_value='1152*896',
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validator=lambda x: x.replace('*', '×') in modules.sdxl_styles.aspect_ratios
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).replace('*', '×')
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if preset is None:
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# Do not overwrite user config if preset is applied.
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with open(config_path, "w", encoding="utf-8") as json_file:
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json.dump(config_dict, json_file, indent=4)
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os.makedirs(temp_outputs_path, exist_ok=True)
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model_filenames = []
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lora_filenames = []
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def get_model_filenames(folder_path, name_filter=None):
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return get_files_from_folder(folder_path, ['.pth', '.ckpt', '.bin', '.safetensors', '.fooocus.patch'], name_filter)
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def update_all_model_names():
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global model_filenames, lora_filenames
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model_filenames = get_model_filenames(modelfile_path)
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lora_filenames = get_model_filenames(lorafile_path)
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return
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def downloading_inpaint_models(v):
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assert v in ['v1', 'v2.5']
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load_file_from_url(
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url='https://huggingface.co/lllyasviel/fooocus_inpaint/resolve/main/fooocus_inpaint_head.pth',
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model_dir=inpaint_models_path,
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file_name='fooocus_inpaint_head.pth'
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)
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head_file = os.path.join(inpaint_models_path, 'fooocus_inpaint_head.pth')
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patch_file = None
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# load_file_from_url(
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# url='https://huggingface.co/lllyasviel/Annotators/resolve/main/ControlNetLama.pth',
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# model_dir=inpaint_models_path,
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# file_name='ControlNetLama.pth'
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# )
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# lama_file = os.path.join(inpaint_models_path, 'ControlNetLama.pth')
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if v == 'v1':
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load_file_from_url(
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url='https://huggingface.co/lllyasviel/fooocus_inpaint/resolve/main/inpaint.fooocus.patch',
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model_dir=inpaint_models_path,
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file_name='inpaint.fooocus.patch'
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)
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patch_file = os.path.join(inpaint_models_path, 'inpaint.fooocus.patch')
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if v == 'v2.5':
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load_file_from_url(
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url='https://huggingface.co/lllyasviel/fooocus_inpaint/resolve/main/inpaint_v25.fooocus.patch',
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model_dir=inpaint_models_path,
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file_name='inpaint_v25.fooocus.patch'
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)
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patch_file = os.path.join(inpaint_models_path, 'inpaint_v25.fooocus.patch')
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return head_file, patch_file
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def downloading_controlnet_canny():
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load_file_from_url(
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url='https://huggingface.co/lllyasviel/misc/resolve/main/control-lora-canny-rank128.safetensors',
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model_dir=controlnet_models_path,
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file_name='control-lora-canny-rank128.safetensors'
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)
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return os.path.join(controlnet_models_path, 'control-lora-canny-rank128.safetensors')
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def downloading_controlnet_cpds():
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load_file_from_url(
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url='https://huggingface.co/lllyasviel/misc/resolve/main/fooocus_xl_cpds_128.safetensors',
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model_dir=controlnet_models_path,
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file_name='fooocus_xl_cpds_128.safetensors'
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)
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return os.path.join(controlnet_models_path, 'fooocus_xl_cpds_128.safetensors')
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def downloading_ip_adapters():
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results = []
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load_file_from_url(
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url='https://huggingface.co/lllyasviel/misc/resolve/main/clip_vision_vit_h.safetensors',
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model_dir=clip_vision_models_path,
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file_name='clip_vision_vit_h.safetensors'
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)
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results += [os.path.join(clip_vision_models_path, 'clip_vision_vit_h.safetensors')]
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load_file_from_url(
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url='https://huggingface.co/lllyasviel/misc/resolve/main/fooocus_ip_negative.safetensors',
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model_dir=controlnet_models_path,
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file_name='fooocus_ip_negative.safetensors'
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)
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results += [os.path.join(controlnet_models_path, 'fooocus_ip_negative.safetensors')]
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load_file_from_url(
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url='https://huggingface.co/lllyasviel/misc/resolve/main/ip-adapter-plus_sdxl_vit-h.bin',
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model_dir=controlnet_models_path,
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file_name='ip-adapter-plus_sdxl_vit-h.bin'
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)
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results += [os.path.join(controlnet_models_path, 'ip-adapter-plus_sdxl_vit-h.bin')]
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return results
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def downloading_upscale_model():
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load_file_from_url(
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url='https://huggingface.co/lllyasviel/misc/resolve/main/fooocus_upscaler_s409985e5.bin',
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model_dir=upscale_models_path,
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file_name='fooocus_upscaler_s409985e5.bin'
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)
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return os.path.join(upscale_models_path, 'fooocus_upscaler_s409985e5.bin')
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update_all_model_names()
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