python自己编写代码实现hough变换

好的，下面是一个简单的 Python 代码实现 Hough 变换：

import cv2
import numpy as np
import math

# 读取图像
img = cv2.imread('test.jpg', cv2.IMREAD_GRAYSCALE)
h, w = img.shape

# Canny 边缘检测
edges = cv2.Canny(img, 50, 150, apertureSize=3)

# Hough 变换
theta_res = 1
rho_res = 1
theta_range = int(180 / theta_res)
rho_max = int(math.sqrt(h ** 2 + w ** 2) / rho_res)
hough_acc = np.zeros((rho_max, theta_range), dtype=np.uint32)

for y in range(h):
    for x in range(w):
        if edges[y, x] > 0:
            for itheta in range(theta_range):
                theta = itheta * theta_res * math.pi / 180
                rho = int(x * math.cos(theta) + y * math.sin(theta)) / rho_res
                hough_acc[int(rho), itheta] += 1

# 阈值处理
threshold = 100
lines = []
for itheta in range(theta_range):
    for irho in range(rho_max):
        if hough_acc[irho, itheta] > threshold:
            a = math.cos(itheta * theta_res * math.pi / 180)
            b = math.sin(itheta * theta_res * math.pi / 180)
            x0 = a * irho * rho_res
            y0 = b * irho * rho_res
            x1 = int(x0 + 1000 * (-b))
            y1 = int(y0 + 1000 * (a))
            x2 = int(x0 - 1000 * (-b))
            y2 = int(y0 - 1000 * (a))
            lines.append(((x1, y1), (x2, y2)))

# 绘制直线
for pt1, pt2 in lines:
    cv2.line(img, pt1, pt2, (0, 0, 255), 2)

# 显示结果
cv2.imshow('Hough', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

这个代码实现了图像的 Canny 边缘检测，然后对边缘进行 Hough 变换，找到直线。最后将直线绘制在原图像上并显示出来。