# ----------------------------------------------------------------------------------------------------------------------
@cython.boundscheck(False)
@cython.wraparound(False)
@cython.cdivision(True)
@cython.nonecheck(False)
cpdef object get_boundaries(object data):
    """
    For a given field of pixels, this method returns a black and white mask, by using the "get_row_boundaries" method
    for each row and column.

    This is pretty fast, as it can rely on the power of numpy to do this operation very quickly.
    """
    cdef object rows = data.copy().astype(float)

    # -- row boundaries
    for i in range(len(data)):
        rows[i] = get_row_boundaries(data[i])

    # -- to get the boundary mask of our columns, transpose the image, shifting columns into rows
    cdef object columns = data.copy().T
    cdef object column_data = data.T

    # -- column boundaries
    for i in range(len(column_data)):
        columns[i] = get_row_boundaries(column_data[i])

    # -- having created our column mask, transpose it back.
    columns = columns.T

    # -- now combine both maps.
    return np.maximum(rows, columns)