6324799d51a451995a91b76306eae40ccd11f55e,utils.py,,accuracy,#Any#Any#,96

Before Change

    (imgs, segs, infos) = batch_data
    _, preds = torch.max(pred.data.cpu(), dim=1)
    valid = (segs >= 0)
    acc = 1.0 * torch.sum(valid * (preds == segs)) / (torch.sum(valid) + 1e-10)
    return acc, torch.sum(valid)


def intersectionAndUnion(batch_data, pred, numClass):

After Change

def accuracy(preds, label):
    valid = (label >= 0)
    acc_sum = (valid * (preds == label)).sum()
    valid_sum = valid.sum()
    acc = float(acc_sum) / (valid_sum + 1e-10)
    return acc, valid_sum

def intersectionAndUnion(imPred, imLab, numClass):
    imPred = np.asarray(imPred).copy()

Instances