canny阈值越高,检测到的边缘数量越少

# 导入OpenCV库，用于图像处理  
import cv2  
import numpy as np  
# 从matplotlib库中导入pyplot模块，用于绘制图像  
from matplotlib import pyplot as plt  # 创建一个名为'window'的窗口，窗口大小自动调整  
cv2.namedWindow('window', cv2.WINDOW_AUTOSIZE)  # cv2.WINDOW_AUTOSIZE: 窗口大小自动调整，不允许用户改变窗口大小  # 使用OpenCV的imread函数读取名为"mao.jpg"的图片，参数1表示读取彩色图像  
cat = cv2.imread("mao.jpg", 0)  # cat变量存储读取的图像数据，OpenCV默认以BGR格式读取  # 在名为'window'的窗口中显示图像  
cv2.imshow('window', cat)  sobelx = cv2.Sobel(cat,cv2.CV_64F,1,0,ksize=3)  
sobely = cv2.Sobel(cat,cv2.CV_64F,0,1,ksize=3)  
sobelx = cv2.convertScaleAbs(sobelx)  
sobely = cv2.convertScaleAbs(sobely)  
sobelxy = cv2.addWeighted(sobelx, 0.5, sobely, 0.5, 0)  scharrx = cv2.Scharr(cat,cv2.CV_64F,1,0)  
scharry = cv2.Scharr(cat,cv2.CV_64F,0,1)  
scharrx = cv2.convertScaleAbs(scharrx)  ![](https://gitee.com/lindongcms/blog/raw/master/img/202412131548505.png)
scharry = cv2.convertScaleAbs(scharry)  
scharrxy = cv2.addWeighted(sobelxy, 0.5, sobely, 0.5,0)  laplacian = cv2.Laplacian(cat,cv2.CV_64F)  
laplacian = cv2.convertScaleAbs(laplacian)  
res = np.hstack((sobelxy,scharrxy,laplacian))  
cv2.imshow('window1', res)  res1 = cv2.Canny(cat,80,150)  
res2 = cv2.Canny(cat,50,100)  
res = np.hstack((res1,res2))  
cv2.imshow('window3', res)  
key = cv2.waitKey(0)  # 检查按下的键是否是'q'，如果是则销毁所有窗口  
if key & 0xFF == ord('q'):  # 0xFF是掩码，用于确保只检查最低8位  print("准备销毁窗口")  cv2.destroyAllWindows()

检测效果图