tensorlayer/prepro.py
def shift(
        x, wrg=0.1, hrg=0.1, is_random=False, row_index=0, col_index=1, channel_index=2, fill_mode='nearest', cval=0.,
        order=1
):
    """Shift an image randomly or non-randomly.

    Parameters
    -----------
    x : numpy.array
        An image with dimension of [row, col, channel] (default).
    wrg : float
        Percentage of shift in axis x, usually -0.25 ~ 0.25.
    hrg : float
        Percentage of shift in axis y, usually -0.25 ~ 0.25.
    is_random : boolean
        If True, randomly shift. Default is False.
    row_index col_index and channel_index : int
        Index of row, col and channel, default (0, 1, 2), for theano (1, 2, 0).
    fill_mode : str
        Method to fill missing pixel, default `nearest`, more options `constant`, `reflect` or `wrap`, see `scipy ndimage affine_transform <https://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.ndimage.interpolation.affine_transform.html>`__
    cval : float
        Value used for points outside the boundaries of the input if mode='constant'. Default is 0.0.
    order : int
        The order of interpolation. The order has to be in the range 0-5. See ``tl.prepro.affine_transform`` and `scipy ndimage affine_transform <https://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.ndimage.interpolation.affine_transform.html>`__

    Returns
    -------
    numpy.array
        A processed image.

    """
    h, w = x.shape[row_index], x.shape[col_index]
    if is_random:
        tx = np.random.uniform(-hrg, hrg) * h
        ty = np.random.uniform(-wrg, wrg) * w
    else:
        tx, ty = hrg * h, wrg * w
    translation_matrix = np.array([[1, 0, tx], [0, 1, ty], [0, 0, 1]])

    transform_matrix = translation_matrix  # no need to do offset
    x = affine_transform(x, transform_matrix, channel_index, fill_mode, cval, order)
    return x
def shift(
        x, wrg=0.1, hrg=0.1, is_random=False, row_index=0, col_index=1, channel_index=2, fill_mode='nearest', cval=0.,
        order=1
):
    """Shift an image randomly or non-randomly.

    Parameters
    -----------
    x : numpy.array
        An image with dimension of [row, col, channel] (default).
    wrg : float
        Percentage of shift in axis x, usually -0.25 ~ 0.25.
    hrg : float
        Percentage of shift in axis y, usually -0.25 ~ 0.25.
    is_random : boolean
        If True, randomly shift. Default is False.
    row_index col_index and channel_index : int
        Index of row, col and channel, default (0, 1, 2), for theano (1, 2, 0).
    fill_mode : str
        Method to fill missing pixel, default `nearest`, more options `constant`, `reflect` or `wrap`, see `scipy ndimage affine_transform <https://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.ndimage.interpolation.affine_transform.html>`__
    cval : float
        Value used for points outside the boundaries of the input if mode='constant'. Default is 0.0.
    order : int
        The order of interpolation. The order has to be in the range 0-5. See ``tl.prepro.affine_transform`` and `scipy ndimage affine_transform <https://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.ndimage.interpolation.affine_transform.html>`__

    Returns
    -------
    numpy.array
        A processed image.

    """
    h, w = x.shape[row_index], x.shape[col_index]
    if is_random:
        tx = np.random.uniform(-hrg, hrg) * h
        ty = np.random.uniform(-wrg, wrg) * w
    else:
        tx, ty = hrg * h, wrg * w
    translation_matrix = np.array([[1, 0, tx], [0, 1, ty], [0, 0, 1]])

    transform_matrix = translation_matrix  # no need to do offset
    x = affine_transform(x, transform_matrix, channel_index, fill_mode, cval, order)
    return x
Shift an image randomly or non-randomly.

    Parameters
    -----------
    x : numpy.array
        An image with dimension of [row, col, channel] (default).
    wrg : float
        Percentage of shift in axis x, usually -0.25 ~ 0.25.
    hrg : float
        Percentage of shift in axis y, usually -0.25 ~ 0.25.
    is_random : boolean
        If True, randomly shift. Default is False.
    row_index col_index and channel_index : int
        Index of row, col and channel, default (0, 1, 2), for theano (1, 2, 0).
    fill_mode : str
        Method to fill missing pixel, default `nearest`, more options `constant`, `reflect` or `wrap`, see `scipy ndimage affine_transform <https://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.ndimage.interpolation.affine_transform.html>`__
    cval : float
        Value used for points outside the boundaries of the input if mode='constant'. Default is 0.0.
    order : int
        The order of interpolation. The order has to be in the range 0-5. See ``tl.prepro.affine_transform`` and `scipy ndimage affine_transform <https://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.ndimage.interpolation.affine_transform.html>`__

    Returns
    -------
    numpy.array
        A processed image.