augmentation.py 文件源码

def translate_transform_batch(x):

    t = (np.random.rand(x.shape[0], 2) - 0.5) * 4

    x_out = np.empty_like(x)
    for i in range(x.shape[0]):

        # Super slow but whatever...
        shift(x[i, 0], shift=t[i], output=x_out[i, 0], order=3, mode='reflect')
        shift(x[i, 1], shift=t[i], output=x_out[i, 1], order=3, mode='reflect')
        shift(x[i, 2], shift=t[i], output=x_out[i, 2], order=3, mode='reflect')

    return x_out