lines = cv2.HoughLinesP(edges, 1, np.pi / 180, 100, minLineLength=50, maxLineGap=10) for line in lines: x1, y1, x2, y2 = line[0] cv2.line(image, (x1, y1), (x2, y2), (0, 0, 255), 2) cv2.imshow("line_detect_possible", image) if __name__ == "__main__": sr...
cv.line(image,(x1,y1),(x2,y2),(0,0,255),2) cv.imshow("line_detect_possible_demo",image) 相关知识补充: (一)HoughLinesP方法 def HoughLinesP(image, rho, theta, threshold, lines=None, minLineLength=None, maxLineGap=None): # real signature unknown; restoredfrom__doc__ cv.HoughLinesP(e...
img_gray1 = cv2.imread("lena.jpg", cv2.IMREAD_GRAYSCALE) #创建SURF()对象,并设置 hessianThreshold和nOctaves参数, #这两个参数为计算关键点的参数,hessianThreshold越大则关 键点的个数越少,nOctaves越大则关键点的尺寸范围越大 surf = cv2.SURF(2000, 2) #detect()方法从灰度图像中检 测出关键点。
2.1.2HoughLinesP(渐进概率式霍夫变换) def line_detect_possible_demo(image): # 渐进概率式霍夫变换 gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY) edge = cv.Canny(gray, 50, 150, apertureSize=3) lines = cv.HoughLinesP(edge, 1, np.pi / 180, 100, minLineLength=50, maxLineGap=10) for ...
cv.imshow('input_image', src) line_detection(src) src= cv.imread('E:/imageload/louti.jpg')#调用上一个函数后,会把传入的src数组改变,所以调用下一个函数时,要重新读取图片line_detect_possible_demo(src) cv.waitKey(0) cv.destroyAllWindows() ...
<< "Usage: ./Line path_to_image1 path_to_image2" << endl; return 1; } std::string window_name("LSD Detect"); string imagePath1 = string(argv[1]); string imagePath2 = string(argv[2]); cout << "import two images" << endl; ...
line(image, (x1, y1), (x2, y2), (0, 255, 0), 2) return image # 读取测试图像 image = cv2.imread('road.jpg') # 检测车道线 result = detect_lane(image) # 显示结果图像 cv2.imshow("Lane detection", result) cv2.waitKey(0) cv2.destroyAllWindows() 这个示例代码将输入图像转换为灰度...
mFeatureDetector.detect(mGraySrc, mSceneKeypoints); mDescriptorExtractor.compute(mGraySrc, mSceneKeypoints, mSceneDescriptors); mDescriptorMatcher.match(mSceneDescriptors, mReferenceDescriptors, mMatches); // Attempt to find the target image's corners in the scene. ...
发挥主要作用的函数有且仅有一个:detectMultiScale()。前一篇猫脸检测中已经提到过这个函数,这里就不再详细赘述。 这里只说一下笑脸检测的流程,显然也都是套路: 1.加载人脸检测器进行人脸检测 2 加载笑脸检测器进行笑脸检测 检测的时候用的都是同一个函数,也即上述detectMultiScale()函数。这里需要注意的一点是:...
// detect first frame and find corners in itMat old_frame,old_gray;capture.read(old_frame);cvtColor(old_frame,old_gray,COLOR_BGR2GRAY);goodFeaturesToTrack(old_gray,featurePoints,maxCorners,qualityLevel,minDistance,Mat(),blockSize,useHarrisDetector,k); ...