utils.py 文件源码

def gauss(mean, stddev, ksize):
    """Use Tensorflow to compute a Gaussian Kernel.

    Parameters
    ----------
    mean : float
        Mean of the Gaussian (e.g. 0.0).
    stddev : float
        Standard Deviation of the Gaussian (e.g. 1.0).
    ksize : int
        Size of kernel (e.g. 16).

    Returns
    -------
    kernel : np.ndarray
        Computed Gaussian Kernel using Tensorflow.
    """
    g = tf.Graph()
    with tf.Session(graph=g):
        x = tf.linspace(-3.0, 3.0, ksize)
        z = (tf.exp(tf.neg(tf.pow(x - mean, 2.0) /
                           (2.0 * tf.pow(stddev, 2.0)))) *
             (1.0 / (stddev * tf.sqrt(2.0 * 3.1415))))
        return z.eval()