| import torchvision.transforms as tvs_trans |
|
|
| normalization_dict = { |
| 'cifar10': [[0.4914, 0.4822, 0.4465], [0.2470, 0.2435, 0.2616]], |
| 'cifar100': [[0.5071, 0.4867, 0.4408], [0.2675, 0.2565, 0.2761]], |
| 'imagenet': [[0.485, 0.456, 0.406], [0.229, 0.224, 0.225]], |
| 'imagenet200': [[0.485, 0.456, 0.406], [0.229, 0.224, 0.225]], |
| 'covid': [[0.4907, 0.4907, 0.4907], [0.2697, 0.2697, 0.2697]], |
| 'aircraft': [[0.5, 0.5, 0.5], [0.5, 0.5, 0.5]], |
| 'cub': [[0.5, 0.5, 0.5], [0.5, 0.5, 0.5]], |
| 'cars': [[0.5, 0.5, 0.5], [0.5, 0.5, 0.5]], |
| } |
|
|
| interpolation_modes = { |
| 'nearest': tvs_trans.InterpolationMode.NEAREST, |
| 'bilinear': tvs_trans.InterpolationMode.BILINEAR, |
| } |
|
|
|
|
| class Convert: |
| def __init__(self, mode='RGB'): |
| self.mode = mode |
|
|
| def __call__(self, image): |
| return image.convert(self.mode) |
|
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| |
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|
