augmentation.py 文件源码

def elastic_transform(image, mask, alpha, sigma, alpha_affine=None, random_state=None):
    """Elastic deformation of images as described in [Simard2003]_ (with modifications).
    .. [Simard2003] Simard, Steinkraus and Platt, "Best Practices for
         Convolutional Neural Networks applied to Visual Document Analysis", in
         Proc. of the International Conference on Document Analysis and
         Recognition, 2003.

     Based on https://gist.github.com/erniejunior/601cdf56d2b424757de5
    """
    if random_state is None:
        random_state = np.random.RandomState(None)

    shape = image.shape

    dx = gaussian_filter((random_state.rand(*shape) * 2 - 1), sigma) * alpha
    dy = gaussian_filter((random_state.rand(*shape) * 2 - 1), sigma) * alpha

    x, y = np.meshgrid(np.arange(shape[1]), np.arange(shape[0]))
    indices = np.reshape(y+dy, (-1, 1)), np.reshape(x+dx, (-1, 1))


    res_x = map_coordinates(image, indices, order=1, mode='reflect').reshape(shape)
    res_y = map_coordinates(mask, indices, order=1, mode='reflect').reshape(shape)
    return res_x, res_y