Function transforms_noaug_train

timm/data/transforms_factory.py:17–41

(
        img_size=224,
        interpolation='bilinear',
        use_prefetcher=False,
        mean=IMAGENET_DEFAULT_MEAN,
        std=IMAGENET_DEFAULT_STD,
)

def transforms_noaug_train(
        img_size=224,
        interpolation='bilinear',
        use_prefetcher=False,
        mean=IMAGENET_DEFAULT_MEAN,
        std=IMAGENET_DEFAULT_STD,
):
    if interpolation == 'random':
        # random interpolation not supported with no-aug
        interpolation = 'bilinear'
    tfl = [
        transforms.Resize(img_size, interpolation=str_to_interp_mode(interpolation)),
        transforms.CenterCrop(img_size)
    ]
    if use_prefetcher:
        # prefetcher and collate will handle tensor conversion and norm
        tfl += [ToNumpy()]
    else:
        tfl += [
            transforms.ToTensor(),
            transforms.Normalize(
                mean=torch.tensor(mean),
                std=torch.tensor(std))
        ]
    return transforms.Compose(tfl)


def transforms_imagenet_train(