Function masked_loss

script/feature/misc.py:332–353

compute loss only in masked region :param criterion: loss function :param f1: [3, batch_size, H, W] :param f2: [3, batch_size, H, W] :param valid_mask: [batch_size, H, W] :return: loss

(criterion, f1, f2, valid_mask)

    return x

def masked_loss(criterion, f1, f2, valid_mask):
    ''' 
    compute loss only in masked region
    :param criterion: loss function
    :param f1: [3, batch_size, H, W]
    :param f2: [3, batch_size, H, W]

    :param valid_mask: [batch_size, H, W]
    :return:
        loss
    '''
    # apply mask on f1
    f1 = f1 * (valid_mask)
    f2 = f2

    # # print masked img features f1, and unwarped features f2
    # plot_features(f1, 'f1.png', False)
    # plot_features(f2, 'f2.png', False)
    loss = criterion(f1, f2)
    loss = (loss * valid_mask).sum() # take sum of loss
    loss = loss / (valid_mask.sum()) # take mean of loss
    return loss

def triplet_loss(f1, f2, margin=1.):
    '''