canny python实现

Canny边缘检测是一种常用的边缘检测算法，Python实现如下：

import cv2
import numpy as np

# 读取图像
img = cv2.imread('image.jpg', 0)

# 高斯滤波
img = cv2.GaussianBlur(img, (3,3), 0)

# 计算梯度
gx = cv2.Sobel(img, cv2.CV_32F, 1, 0)
gy = cv2.Sobel(img, cv2.CV_32F, 0, 1)
mag, ang = cv2.cartToPolar(gx, gy, angleInDegrees=True)

# 非极大值抑制
rows, cols = img.shape
for i in range(1, rows - 1):
    for j in range(1, cols - 1):
        if (ang[i, j] <= 22.5 and ang[i, j] > -22.5) or (ang[i, j] > 157.5 and ang[i, j] <= -157.5):
            if mag[i, j] >= mag[i, j-1] and mag[i, j] >= mag[i, j+1]:
                img[i, j] = mag[i, j]
            else:
                img[i, j] = 0
        elif (ang[i, j] > 22.5 and ang[i, j] <= 67.5) or (ang[i, j] > -157.5 and ang[i, j] <= -112.5):
            if mag[i, j] >= mag[i-1, j-1] and mag[i, j] >= mag[i+1, j+1]:
                img[i, j] = mag[i, j]
            else:
                img[i, j] = 0
        elif (ang[i, j] > 67.5 and ang[i, j] <= 112.5) or (ang[i, j] > -112.5 and ang[i, j] <= -67.5):
            if mag[i, j] >= mag[i-1, j] and mag[i, j] >= mag[i+1, j]:
                img[i, j] = mag[i, j]
            else:
                img[i, j] = 0
        elif (ang[i, j] > 112.5 and ang[i, j] <= 157.5) or (ang[i, j] > -67.5 and ang[i, j] <= -22.5):
            if mag[i, j] >= mag[i-1, j+1] and mag[i, j] >= mag[i+1, j-1]:
                img[i, j] = mag[i, j]
            else:
                img[i, j] = 0

# 双阈值处理
high_threshold = np.max(img) * 0.8
low_threshold = high_threshold * 0.5

rows, cols = img.shape
for i in range(rows):
    for j in range(cols):
        if img[i, j] >= high_threshold:
            img[i, j] = 255
        elif img[i, j] <= low_threshold:
            img[i, j] = 0
        else:
            img[i, j] = 50

# 滞后阈值处理
img = cv2.Canny(img, 50, 150)

# 显示图像
cv2.imshow('Canny Edge Detection', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

以上代码中，先读取图像，然后进行高斯滤波，接着计算梯度、进行非极大值抑制、双阈值处理和滞后阈值处理，最后显示图像。