用pycharm写一个检测矩形轮廓并标记出缺口像素

首先需要导入需要的库：cv2、numpy。

然后读取图片并转为灰度图像：

import cv2
import numpy as np

img = cv2.imread('image.png')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

接下来需要进行边缘检测，这里使用Canny算法：

edges = cv2.Canny(gray, 50, 150, apertureSize=3)

得到边缘后，我们可以使用霍夫变换进行直线检测：

lines = cv2.HoughLines(edges, 1, np.pi/180, 200)

这里的参数需要根据具体情况进行调整。

接下来，我们将检测到的直线绘制到原图上：

for line in lines:
    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(img, (x1, y1), (x2, y2), (0, 0, 255), 2)

最后，我们可以在缺口处标记出缺口像素：

for line in lines:
    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(img, (x1, y1), (x2, y2), (0, 0, 255), 2)

    if abs(x1 - x2) < abs(y1 - y2):
        for i in range(min(y1, y2), max(y1, y2)):
            if gray[i, int((x1 + x2) / 2)] == 0:
                img[i, int((x1 + x2) / 2)] = [0, 0, 255]
    else:
        for i in range(min(x1, x2), max(x1, x2)):
            if gray[int((y1 + y2) / 2), i] == 0:
                img[int((y1 + y2) / 2), i] = [0, 0, 255]

完整代码如下：

import cv2
import numpy as np

img = cv2.imread('image.png')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

edges = cv2.Canny(gray, 50, 150, apertureSize=3)

lines = cv2.HoughLines(edges, 1, np.pi/180, 200)

for line in lines:
    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(img, (x1, y1), (x2, y2), (0, 0, 255), 2)

    if abs(x1 - x2) < abs(y1 - y2):
        for i in range(min(y1, y2), max(y1, y2)):
            if gray[i, int((x1 + x2) / 2)] == 0:
                img[i, int((x1 + x2) / 2)] = [0, 0, 255]
    else:
        for i in range(min(x1, x2), max(x1, x2)):
            if gray[int((y1 + y2) / 2), i] == 0:
                img[int((y1 + y2) / 2), i] = [0, 0, 255]

cv2.imshow('image', img)
cv2.waitKey(0)
cv2.destroyAllWindows()