prepro.py 文件源码

def projective_transform_by_points(x, src, dst, map_args={}, output_shape=None, order=1, mode='constant', cval=0.0, clip=True, preserve_range=False):
    """Projective transform by given coordinates, usually 4 coordinates. see `scikit-image <http://scikit-image.org/docs/dev/auto_examples/applications/plot_geometric.html>`_.

    Parameters
    -----------
    x : numpy array
        An image with dimension of [row, col, channel] (default).
    src : list or numpy
        The original coordinates, usually 4 coordinates of (x, y).
    dst : list or numpy
        The coordinates after transformation, the number of coordinates is the same with src.
    map_args : dict, optional
        Keyword arguments passed to inverse_map.
    output_shape : tuple (rows, cols), optional
        Shape of the output image generated. By default the shape of the input image is preserved. Note that, even for multi-band images, only rows and columns need to be specified.
    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
    mode : {‘constant’, ‘edge’, ‘symmetric’, ‘reflect’, ‘wrap’}, optional
        Points outside the boundaries of the input are filled according to the given mode. Modes match the behaviour of numpy.pad.
    cval : float, optional
        Used in conjunction with mode ‘constant’, the value outside the image boundaries.
    clip : bool, optional
        Whether to clip the output to the range of values of the input image. This is enabled by default, since higher order interpolation may produce values outside the given input range.
    preserve_range : bool, optional
        Whether to keep the original range of values. Otherwise, the input image is converted according to the conventions of img_as_float.

    Examples
    --------
    >>> Assume X is an image from CIFAR 10, i.e. shape == (32, 32, 3)
    >>> src = [[0,0],[0,32],[32,0],[32,32]]
    >>> dst = [[10,10],[0,32],[32,0],[32,32]]
    >>> x = projective_transform_by_points(X, src, dst)

    References
    -----------
    - `scikit-image : geometric transformations <http://scikit-image.org/docs/dev/auto_examples/applications/plot_geometric.html>`_
    - `scikit-image : examples <http://scikit-image.org/docs/dev/auto_examples/index.html>`_
    """
    if type(src) is list:   # convert to numpy
        src = np.array(src)
    if type(dst) is list:
        dst = np.array(dst)
    if np.max(x)>1:         # convert to [0, 1]
        x = x/255

    m = transform.ProjectiveTransform()
    m.estimate(dst, src)
    warped = transform.warp(x, m,  map_args=map_args, output_shape=output_shape, order=order, mode=mode, cval=cval, clip=clip, preserve_range=preserve_range)
    return warped

# Numpy and PIL