otsu算法代码opencv

以下是使用OpenCV实现Otsu算法的代码：

import numpy as np
import cv2

def otsu_threshold(image):
    # 将图像转换为灰度图
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    
    # 计算图像的直方图
    hist = cv2.calcHist([gray], [0], None, [256], [0, 256])
    
    # 归一化直方图
    hist /= hist.sum()
    
    # 初始化类间方差和最佳阈值
    inter_class_variance = 0
    best_threshold = 0
    
    # 遍历所有可能的阈值
    for threshold in range(256):
        # 计算背景和前景的像素概率和均值
        background_prob = hist[:threshold].sum()
        foreground_prob = hist[threshold:].sum()
        background_mean = np.average(np.arange(threshold), weights=hist[:threshold])
        foreground_mean = np.average(np.arange(threshold, 256), weights=hist[threshold:])
        
        # 计算类间方差
        current_inter_class_variance = background_prob * foreground_prob * (background_mean - foreground_mean) ** 2
        
        # 更新最佳阈值和类间方差
        if current_inter_class_variance > inter_class_variance:
            inter_class_variance = current_inter_class_variance
            best_threshold = threshold
    
    # 使用最佳阈值对灰度图像进行二值化处理
    _, threshold_image = cv2.threshold(gray, best_threshold, 255, cv2.THRESH_BINARY)
    
    return threshold_image