Kevin Alberts
fb9ce46bd8
- Encoders: sparse, denoising, contractive and variational - Noise: gaussian
39 lines
854 B
Python
39 lines
854 B
Python
from models.base_dataset import BaseDataset
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class BaseCorruption:
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"""
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Base corruption model that is not implemented.
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"""
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name = "BaseCorruption"
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def __init__(self, name: str = None):
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if name is not None:
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self.name = name
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def __str__(self):
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return f"{self.name}"
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@classmethod
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def corrupt_image(cls, image):
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raise NotImplementedError()
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@classmethod
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def corrupt_dataset(cls, dataset: BaseDataset) -> BaseDataset:
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raise NotImplementedError()
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class NoCorruption(BaseCorruption):
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"""
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Corruption model that does not corrupt the dataset at all.
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"""
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name = "No corruption"
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@classmethod
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def corrupt_image(cls, image):
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return image
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@classmethod
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def corrupt_dataset(cls, dataset: BaseDataset) -> BaseDataset:
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return dataset
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