OpenCV半小时掌握基本操作之直线检测

cv2.HoughLines(image, rho, theta, threshold, lines=None, srn=None, stn=None, min_theta=None, max_theta=None)

import numpy as np
import cv2
from matplotlib import pyplot as plt

# 读取图片
image = cv2.imread("sudoku.jpg")
image_copy = image.copy()

# 转换成灰度图
image_gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

# 边缘检测, Sobel算子大小为3
edges = cv2.Canny(image_gray, 170, 220, apertureSize=3)

# 霍夫曼直线检测
lines = cv2.HoughLines(edges, 1, np.pi / 180, 250)

# 遍历
for line in lines:
    # 获取rho和theta
    rho, theta = line[0]
    a = np.cos(theta)
    b = np.sin(theta)
    x0 = a * rho
    y0 = b * rho
    x1 = int(x0 + 1000 * (-b))
    y1 = int(y0 + 1000 * (a))
    x2 = int(x0 - 1000 * (-b))
    y2 = int(y0 - 1000 * (a))
    cv2.line(image_copy, (x1, y1), (x2, y2), (0, 0, 255), thickness=5)

# 图片展示
f, ax = plt.subplots(2, 2, figsize=(12, 12))

# 子图
ax[0, 0].imshow(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
ax[0, 1].imshow(image_gray, "gray")
ax[1, 0].imshow(edges, "gray")
ax[1, 1].imshow(cv2.cvtColor(image_copy, cv2.COLOR_BGR2RGB))

# 标题
ax[0, 0].set_title("original")
ax[0, 1].set_title("image gray")
ax[1, 0].set_title("image edge")
ax[1, 1].set_title("image line")

plt.show()

HoughLinesP(image, rho, theta, threshold, lines=None, minLineLength=None, maxLineGap=None)

import numpy as np
import cv2
from matplotlib import pyplot as plt

# 读取图片
image = cv2.imread("sudoku.jpg")
image_copy = image.copy()

# 转换成灰度图
image_gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

# 边缘检测, Sobel算子大小为3
edges = cv2.Canny(image_gray, 170, 220, apertureSize=3)

# 霍夫曼直线检测
lines = cv2.HoughLinesP(edges, 1, np.pi / 180, 100, minLineLength=100, maxLineGap=10)

# 遍历
for line in lines:

    # 获取坐标
    x1, y1, x2, y2 = line[0]
    cv2.line(image_copy, (x1, y1), (x2, y2), (0, 0, 255), thickness=5)


# 图片展示
f, ax = plt.subplots(2, 2, figsize=(12, 12))

# 子图
ax[0, 0].imshow(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
ax[0, 1].imshow(image_gray, "gray")
ax[1, 0].imshow(edges, "gray")
ax[1, 1].imshow(cv2.cvtColor(image_copy, cv2.COLOR_BGR2RGB))

# 标题
ax[0, 0].set_title("original")
ax[0, 1].set_title("image gray")
ax[1, 0].set_title("image edge")
ax[1, 1].set_title("image line")

plt.show()