evaluation code is wrong

In criterion.py:

def dist_between_onehot(lhs: Tensor, rhs: Tensor) -> float:
    """
    calculate the average distance between two one-hot array

    Args:
        lhs (Tensor): lhs tensor ([N,C]=[undefined,cls_num), dtype=float32, range=[0.0,1.0))
        rhs (Tensor): rhs tensor ([N]=[undefined], dtype=long, range=[0,cls_num))

    Returns:
        float: average distance. range=[0.0,1.0)

    Note:
        Multiply it by 360° to obtain dist in degrees.
    """

    cls_num = lhs.nelement()
    ...

The method to get cls_num is wrong. It should use: lhs.shape[1]

In addition, in test_RotNet.py:

for source, target in test_dataloader:
            source: Tensor = source.to(device=device)
            target: Tensor = target.to(device=device)

            predict: Tensor = model(source)

            digree_diff = dist_between_onehot(predict, target) * 360

The method to compute digree_diff is wrong, the target variable is in range[0, 1), you should multiply by 360, like the following:

digree_diff = dist_between_onehot(predict, target*360) * 360

lumina37 / rotate-captcha-crack

evaluation code is wrong #16