helpers.py 文件源码

python
阅读 34 收藏 0 点赞 0 评论 0

项目:deep-prior 作者: moberweger 项目源码 文件源码
def gaussian_kernel(kernel_shape, sigma=None):
    """
    Get 2D Gaussian kernel
    :param kernel_shape: kernel size
    :param sigma: sigma of Gaussian distribution
    :return: 2D Gaussian kernel
    """
    kern = numpy.zeros((kernel_shape, kernel_shape), dtype='float32')

    # get sigma from kernel size
    if sigma is None:
        sigma = 0.3*((kernel_shape-1.)*0.5 - 1.) + 0.8

    def gauss(x, y, s):
        Z = 2. * numpy.pi * s ** 2.
        return 1. / Z * numpy.exp(-(x ** 2. + y ** 2.) / (2. * s ** 2.))

    mid = numpy.floor(kernel_shape / 2.)
    for i in xrange(0, kernel_shape):
        for j in xrange(0, kernel_shape):
            kern[i, j] = gauss(i - mid, j - mid, sigma)

    return kern / kern.sum()
评论列表
文章目录


问题


面经


文章

微信
公众号

扫码关注公众号