tenengrad梯度函数python实现

Tenengrad梯度函数可以通过以下Python代码实现：

import numpy as np

def tenengrad(img):
    # 计算图像在x和y方向上的梯度
    sobel_x = np.array([[-1, 0, 1], [-2, 0, 2], [-1, 0, 1]])
    sobel_y = np.array([[-1, -2, -1], [0, 0, 0], [1, 2, 1]])
    gx = np.abs(np.convolve(img.flatten(), sobel_x.flatten(), mode='same').reshape(img.shape))
    gy = np.abs(np.convolve(img.flatten(), sobel_y.flatten(), mode='same').reshape(img.shape))
    # 计算Tenengrad梯度
    gx2 = np.multiply(gx, gx)
    gy2 = np.multiply(gy, gy)
    gxgy = np.multiply(gx, gy)
    sigma_gx2 = np.convolve(gx2.flatten(), np.ones((3, 3)).flatten(), mode='same').reshape(img.shape)
    sigma_gy2 = np.convolve(gy2.flatten(), np.ones((3, 3)).flatten(), mode='same').reshape(img.shape)
    sigma_gxgy = np.convolve(gxgy.flatten(), np.ones((3, 3)).flatten(), mode='same').reshape(img.shape)
    tgrad = np.sqrt(np.divide(np.multiply(sigma_gy2, sigma_gx2) - np.square(sigma_gxgy), sigma_gy2 + sigma_gx2))
    return tgrad

其中，`img`为输入的灰度图像，输出为计算出的Tenengrad梯度图像。