opencv 最大熵二值化 python

在Python中使用OpenCV进行最大熵二值化的示例代码如下：

import numpy as np
import cv2 as cv
import sys

image = cv.imread('F:/material/images/2022/2022-06/img_300_320.jpg')
if image is None:
    print('Error: Could not load image')
    sys.exit()

img_gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
cv.imshow('img_gray', img_gray)

blockSize = 5
constValue = 0
maxVal = 255

img_B_MEAN = cv.adaptiveThreshold(img_gray, maxVal, cv.ADAPTIVE_THRESH_MEAN_C, cv.THRESH_BINARY, blockSize, constValue)
img_B_GAUSSIAN = cv.adaptiveThreshold(img_gray, maxVal, cv.ADAPTIVE_THRESH_GAUSSIAN_C, cv.THRESH_BINARY, blockSize, constValue)

cv.imshow('img_B_MEAN', img_B_MEAN)
cv.imshow('img_B_GAUSSIAN', img_B_GAUSSIAN)

cv.waitKey(0)
cv.destroyAllWindows()

这段代码使用OpenCV的`adaptiveThreshold()`函数进行最大熵二值化。其中，`blockSize`表示局部区域的大小，`constValue`表示从平均值或加权平均值中减去的常数值，`maxVal`表示最大值。通过调整这些参数，可以得到不同的二值化结果。在示例代码中，分别使用了`ADAPTIVE_THRESH_MEAN_C`和`ADAPTIVE_THRESH_GAUSSIAN_C`两种算法进行二值化，并显示了结果图像。

希望对你有帮助！
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