请用python写一个计算图像熵的程序

以下是一个用Python计算图像熵的示例代码：

import cv2
import math

def image_entropy(img_path):
    img = cv2.imread(img_path)
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    height, width = gray.shape
    histogram = [0.0] * 256
    for i in range(height):
        for j in range(width):
            histogram[gray[i][j]] += 1
    for i in range(256):
        histogram[i] /= height * width
    entropy = 0.0
    for i in range(256):
        if histogram[i] == 0:
            entropy -= 0
        else:
            entropy -= histogram[i] * math.log(histogram[i], 2)
    return entropy

img_path = "image.jpg"
entropy = image_entropy(img_path)
print(f"The entropy of the image is {entropy}")

代码首先使用OpenCV加载图像，将其转换为灰度图像，然后计算灰度直方图。接下来，对于每个灰度级别，计算它出现的概率，并使用Shannon熵公式计算图像的熵值。最后，返回计算的图像熵并显示结果。