api.py 文件源码

def skeletonize_image(image, method=None, dilation=None, binarization=None,
                      invert=False):
    """Extract a 1 pixel wide representation of image by morphologically
    thinning the white contiguous blobs (connected components).
    If image is not black and white, a binarization process is applied
    according to binarization, which can be 'sauvola', 'isodata', 'otsu',
    'li' (default, ref: binarize()).

    A process of dilation can also be applied by specifying the number
    of pixels in dilate prior to extracting the skeleton.

    The method for skeletonization can be 'medial', '3d', 'regular', or a
    'combined' version of the three. Defaults to 'regular'.
    A 'thin' operator is also available. For reference,
    see http://scikit-image.org/docs/dev/auto_examples/edges/plot_skeleton.html
    """
    # if image is all one single color, return it
    if len(np.unique(image)) == 1:
        return image
    # scikit-image needs only 0's and 1's
    mono_image = binarize_image(image, method=binarization) / 255
    if invert:
        mono_image = invert_image(mono_image)
    if dilation:
        dilation = (2 * dilation) + 1
        dilation_kernel = np.ones((dilation, dilation), np.uint8)
        mono_image = cv2.morphologyEx(mono_image, cv2.MORPH_DILATE,
                                      dilation_kernel)
    with warnings.catch_warnings(record=True):
        warnings.filterwarnings('ignore', category=UserWarning)
        if method == '3d':
            skeleton = morphology.skeletonize_3d(mono_image)
        elif method == 'medial':
            skeleton = morphology.medial_axis(mono_image,
                                              return_distance=False)
        elif method == 'thin':
            skeleton = morphology.thin(mono_image)
        elif method == 'combined':
            skeleton = (morphology.skeletonize_3d(mono_image)
                        | morphology.medial_axis(mono_image,
                                                 return_distance=False)
                        | morphology.skeletonize(mono_image))
        else:
            skeleton = morphology.skeletonize(mono_image)
    return convert(skeleton)