prepro.py 文件源码

def apply_transform(x, transform_matrix, channel_index=2, fill_mode='nearest', cval=0., order=1):
    """Return transformed images by given transform_matrix from ``transform_matrix_offset_center``.

    Parameters
    ----------
    x : numpy array
        An image with dimension of [row, col, channel] (default).
    transform_matrix : numpy array
        Transform matrix (offset center), can be generated by ``transform_matrix_offset_center``
    channel_index : int
        Index of channel, default 2.
    fill_mode : string
        Method to fill missing pixel, default ‘nearest’, more options ‘constant’, ‘reflect’ or ‘wrap’

        - `scipy ndimage affine_transform <https://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.ndimage.interpolation.affine_transform.html>`_
    cval : scalar, optional
        Value used for points outside the boundaries of the input if mode='constant'. Default is 0.0
    order : int, optional
        The order of interpolation. The order has to be in the range 0-5:

        - 0 Nearest-neighbor
        - 1 Bi-linear (default)
        - 2 Bi-quadratic
        - 3 Bi-cubic
        - 4 Bi-quartic
        - 5 Bi-quintic

        - `scipy ndimage affine_transform <https://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.ndimage.interpolation.affine_transform.html>`_

    Examples
    --------
    - See ``rotation``, ``shift``, ``shear``, ``zoom``.
    """
    x = np.rollaxis(x, channel_index, 0)
    final_affine_matrix = transform_matrix[:2, :2]
    final_offset = transform_matrix[:2, 2]
    channel_images = [ndi.interpolation.affine_transform(x_channel, final_affine_matrix,
                      final_offset, order=order, mode=fill_mode, cval=cval) for x_channel in x]
    x = np.stack(channel_images, axis=0)
    x = np.rollaxis(x, 0, channel_index+1)
    return x