(image, alpha=100.0, sigma=5.0)
return 1.0 / np.sqrt(1.0 + alpha * gradnorm)
Inverse of gradient magnitude.

    Compute the magnitude of the gradients in the image and then inverts the
    result in the range [0, 1]. Flat areas are assigned values close to 1,
    while areas close to borders are assigned values close to 0.

    This function or a similar one defined by the user should be applied over
    the image as a preprocessing step before calling
    `morphological_geodesic_active_contour`.

    Parameters
    ----------
    image : (M, N) or (L, M, N) array
        Grayscale image or volume.
    alpha : float, optional
        Controls the steepness of the inversion. A larger value will make the
        transition between the flat areas and border areas steeper in the
        resulting array.
    sigma : float, optional
        Standard deviation of the Gaussian filter applied over the image.

    Returns
    -------
    gimage : (M, N) or (L, M, N) array
        Preprocessed image (or volume) suitable for
        `morphological_geodesic_active_contour`.
Inverse of gradient magnitude.
Inverse of gradient magnitude .
def inverse_gaussian_gradient(image, alpha=100.0, sigma=5.0):
    """Inverse of gradient magnitude.

    Compute the magnitude of the gradients in the image and then inverts the
    result in the range [0, 1]. Flat areas are assigned values close to 1,
    while areas close to borders are assigned values close to 0.

    This function or a similar one defined by the user should be applied over
    the image as a preprocessing step before calling
    `morphological_geodesic_active_contour`.

    Parameters
    ----------
    image : (M, N) or (L, M, N) array
        Grayscale image or volume.
    alpha : float, optional
        Controls the steepness of the inversion. A larger value will make the
        transition between the flat areas and border areas steeper in the
        resulting array.
    sigma : float, optional
        Standard deviation of the Gaussian filter applied over the image.

    Returns
    -------
    gimage : (M, N) or (L, M, N) array
        Preprocessed image (or volume) suitable for
        `morphological_geodesic_active_contour`.
    """
    gradnorm = ndi.gaussian_gradient_magnitude(image, sigma, mode='nearest')
    return 1.0 / np.sqrt(1.0 + alpha * gradnorm)
def inverse_gaussian_gradient ( image , alpha = 100.0 , sigma = 5.0 ) : gradnorm = ndi . gaussian_gradient_magnitude ( image , sigma , mode = 'nearest' ) return 1.0 / np . sqrt ( 1.0 + alpha * gradnorm )