83dc25dbc8b4ed98b4cc952e3cb35668e5a65490,dataloader.py,ToTensor,__call__,#ToTensor#Any#,120

Before Change

        // numpy image: H x W x C
        // torch image: C X H X W

        image = image.transpose((2, 0, 1))

        return {"img": torch.from_numpy(image),
                "annot": torch.from_numpy(annots)}

class Resizer(object):
    Convert ndarrays in sample to Tensors.

After Change

        image, annots = sample["img"], sample["annot"]

        return {"img":((image.astype(np.float32)-self.mean)/self.std), "annot": annots}

class UnNormalizer(object):
    def __init__(self, mean=None, std=None):
        if mean == None:

Instances