Initialize is_undersized to False, fix bug in directory resolver
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685bada570
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@ -271,6 +271,7 @@ class ImageTrainItem:
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else:
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else:
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self.image = image
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self.image = image
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self.is_undersized = False
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self.error = None
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self.error = None
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self.__compute_target_width_height()
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self.__compute_target_width_height()
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@ -13,6 +13,7 @@ from data.image_train_item import ImageCaption, ImageTrainItem
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class DataResolver:
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class DataResolver:
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def __init__(self, aspects: list[typing.Tuple[int, int]], flip_p=0.0, seed=555):
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def __init__(self, aspects: list[typing.Tuple[int, int]], flip_p=0.0, seed=555):
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self.seed = seed
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self.aspects = aspects
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self.aspects = aspects
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self.flip_p = flip_p
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self.flip_p = flip_p
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@ -146,9 +147,6 @@ class DirectoryResolver(DataResolver):
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if cur_file_multiplier > 0:
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if cur_file_multiplier > 0:
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if randomizer.random() < cur_file_multiplier:
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if randomizer.random() < cur_file_multiplier:
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items.append(item)
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items.append(item)
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if item:
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items.append(item)
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return items
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return items
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@staticmethod
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@staticmethod
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@ -230,7 +228,7 @@ def resolve(value: typing.Union[dict, str], aspects: list[float], flip_p: float=
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case 'multi':
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case 'multi':
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items = []
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items = []
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for resolver in value.get('resolvers', []):
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for resolver in value.get('resolvers', []):
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items.extend(resolve(resolver, aspects, flip_p, seed))
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items += resolve(resolver, aspects, flip_p, seed)
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return items
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return items
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case _:
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case _:
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raise ValueError(f"Cannot resolve training data for resolver value '{resolver}'")
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raise ValueError(f"Cannot resolve training data for resolver value '{resolver}'")
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