Class ReidAugmentation

PATH/core/data/transforms/reid_transforms.py:44–90

class ReidAugmentation(object):
    def __init__(self, height, width, re, vit=False):
        normalizer = T.Normalize(mean=[0.485, 0.456, 0.406],
                                 std=[0.229, 0.224, 0.225])

        if not vit:
            self.train_transformer = T.Compose([
                T.Resize((height, width)),
                T.RandomHorizontalFlip(),
                T.Pad(10),
                T.RandomCrop((height, width)),
                T.ToTensor(),
                normalizer,
            ])

            if re:
                self.train_transformer = T.Compose([
                    T.Resize((height, width)),
                    T.RandomHorizontalFlip(),
                    T.Pad(10),
                    T.RandomCrop((height, width)),
                    RandomSizedEarser(),
                    T.ToTensor(),
                    normalizer,
                ])
        else:
            self.train_transformer = T.Compose([
                T.Resize((height, width)),
                T.RandomHorizontalFlip(),
                T.Pad(10),
                T.RandomCrop((height, width)),
                T.PILToTensor(),
            ])

            if re:
                self.train_transformer = T.Compose([
                    T.Resize((height, width)),
                    T.RandomHorizontalFlip(),
                    T.Pad(10),
                    T.RandomCrop((height, width)),
                    RandomSizedEarser(),
                    T.PILToTensor(),
                ])

    def __call__(self, img):
        ## transform
        return self.train_transformer(img)