Use os.makedirs(..., exist_ok=True)
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59419bd64a
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@ -20,9 +20,7 @@ codeformer = None
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def setup_model(dirname):
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global model_path
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if not os.path.exists(model_path):
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os.makedirs(model_path)
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os.makedirs(model_path, exist_ok=True)
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path = modules.paths.paths.get("CodeFormer", None)
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if path is None:
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@ -7,8 +7,7 @@ from modules.paths_internal import extensions_dir, extensions_builtin_dir, scrip
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extensions = []
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if not os.path.exists(extensions_dir):
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os.makedirs(extensions_dir)
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os.makedirs(extensions_dir, exist_ok=True)
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def active():
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@ -70,11 +70,8 @@ gfpgan_constructor = None
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def setup_model(dirname):
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global model_path
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if not os.path.exists(model_path):
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os.makedirs(model_path)
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try:
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os.makedirs(model_path, exist_ok=True)
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from gfpgan import GFPGANer
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from facexlib import detection, parsing # noqa: F401
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global user_path
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@ -95,8 +95,7 @@ def cleanup_models():
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def move_files(src_path: str, dest_path: str, ext_filter: str = None):
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try:
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if not os.path.exists(dest_path):
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os.makedirs(dest_path)
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os.makedirs(dest_path, exist_ok=True)
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if os.path.exists(src_path):
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for file in os.listdir(src_path):
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fullpath = os.path.join(src_path, file)
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@ -95,8 +95,7 @@ except Exception:
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def setup_model():
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if not os.path.exists(model_path):
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os.makedirs(model_path)
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os.makedirs(model_path, exist_ok=True)
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enable_midas_autodownload()
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@ -298,8 +298,7 @@ def download_and_cache_models(dirname):
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download_url = 'https://github.com/opencv/opencv_zoo/blob/91fb0290f50896f38a0ab1e558b74b16bc009428/models/face_detection_yunet/face_detection_yunet_2022mar.onnx?raw=true'
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model_file_name = 'face_detection_yunet.onnx'
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if not os.path.exists(dirname):
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os.makedirs(dirname)
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os.makedirs(dirname, exist_ok=True)
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cache_file = os.path.join(dirname, model_file_name)
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if not os.path.exists(cache_file):
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