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from lama_cleaner.model.fcf import FcF |
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from lama_cleaner.model.lama import LaMa |
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from lama_cleaner.model.ldm import LDM |
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from lama_cleaner.model.mat import MAT |
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from lama_cleaner.model.sd import SD14 |
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from lama_cleaner.model.zits import ZITS |
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from lama_cleaner.model.opencv2 import OpenCV2 |
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from lama_cleaner.schema import Config |
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models = {"lama": LaMa, "ldm": LDM, "zits": ZITS, "mat": MAT, "fcf": FcF, "sd1.4": SD14, "cv2": OpenCV2} |
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class ModelManager: |
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def __init__(self, name: str, device, **kwargs): |
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self.name = name |
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self.device = device |
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self.kwargs = kwargs |
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self.model = self.init_model(name, device, **kwargs) |
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def init_model(self, name: str, device, **kwargs): |
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if name in models: |
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model = models[name](device, **kwargs) |
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else: |
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raise NotImplementedError(f"Not supported model: {name}") |
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return model |
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def is_downloaded(self, name: str) -> bool: |
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if name in models: |
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return models[name].is_downloaded() |
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else: |
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raise NotImplementedError(f"Not supported model: {name}") |
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def __call__(self, image, mask, config: Config): |
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return self.model(image, mask, config) |
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def switch(self, new_name: str): |
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if new_name == self.name: |
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return |
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try: |
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self.model = self.init_model(new_name, self.device, **self.kwargs) |
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self.name = new_name |
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except NotImplementedError as e: |
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raise e |
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