效果：

代码：

import cv2
import numpy as np
from matplotlib import pyplot as pltif __name__ == "__main__":h = 10w = 10data = np.random.normal(0, 1, [h, w]) # sigma, 2*sigma, 3*sigma之间的数的比例分别为0.68， 0.96， 0.99mask_new = data > 2print(data)print(np.sum(abs(data) < 1) / (h*w))print(np.sum(data < 0) / (h * w))mask_new = (mask_new * 255).astype(np.uint8)mask_new[3:6, 4:6] = 255kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3, 3))a = cv2.dilate(mask_new, kernel) # 膨胀b = cv2.erode(a, kernel) #腐蚀closing = cv2.morphologyEx(mask_new, cv2.MORPH_CLOSE, kernel) # 先膨胀后腐蚀opening = cv2.morphologyEx(mask_new, cv2.MORPH_OPEN, kernel)  # 先腐蚀后膨胀plt.figure()plt.subplot(231)plt.imshow(mask_new, cmap='gray')plt.subplot(232)plt.imshow(a, cmap='gray')plt.subplot(233)plt.imshow(b, cmap='gray')plt.subplot(234)plt.imshow(opening, cmap='gray')plt.subplot(235)plt.imshow(closing, cmap='gray')plt.show()