496766edd7
* add vae approx download * files * files * files * i * i * i * i * i * i * i * i * i * i
44 lines
1.6 KiB
Python
44 lines
1.6 KiB
Python
import os
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modelfile_path = os.path.abspath(os.path.join(os.path.dirname(__file__), '../models/checkpoints/'))
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lorafile_path = os.path.abspath(os.path.join(os.path.dirname(__file__), '../models/loras/'))
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vae_approx_path = os.path.abspath(os.path.join(os.path.dirname(__file__), '../models/vae_approx/'))
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temp_outputs_path = os.path.abspath(os.path.join(os.path.dirname(__file__), '../outputs/'))
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fooocus_expansion_path = os.path.abspath(os.path.join(os.path.dirname(__file__),
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'../models/prompt_expansion/fooocus_expansion'))
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os.makedirs(temp_outputs_path, exist_ok=True)
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default_base_model_name = 'sd_xl_base_1.0_0.9vae.safetensors'
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default_refiner_model_name = 'sd_xl_refiner_1.0_0.9vae.safetensors'
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default_lora_name = 'sd_xl_offset_example-lora_1.0.safetensors'
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default_lora_weight = 0.5
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model_filenames = []
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lora_filenames = []
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def get_model_filenames(folder_path):
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if not os.path.isdir(folder_path):
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raise ValueError("Folder path is not a valid directory.")
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filenames = []
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for filename in os.listdir(folder_path):
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if os.path.isfile(os.path.join(folder_path, filename)):
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_, file_extension = os.path.splitext(filename)
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if file_extension.lower() in ['.pth', '.ckpt', '.bin', '.safetensors']:
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filenames.append(filename)
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return filenames
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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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update_all_model_names()
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