第二个问题就是关于标定函数stereoCalibrate,在OpenCV2和OpenCV3中的参数定义的顺序是不同的,OpenCV2: double rms = cv::stereoCalibrate(objectPoints, imagePoints[0], imagePoints[1], cameraMatrix[0], distCoeffs[0], cameraMatrix[1], distCoeffs[1], imageSize, R, T, E, F, TermCriteria(CV_TERMCRIT...
步骤2:计算双目标定参数 # 计算左右相机的内参数和外参数ret,cameraMatrixL,distCoeffsL,cameraMatrixR,distCoeffsR,R,T,E,F=cv2.stereoCalibrate(objpoints,imgpoints_left,imgpoints_right,cameraMatrixL,distCoeffsL,cameraMatrixR,distCoeffsR,grayL.shape[::-1])print("左相机内参数:\n",cameraMatrixL)print("...
Mat R,T,E,F;doublerms=stereoCalibrate(objectPoints,imagePoints[0],imagePoints[1],cameraMatrix[0],distCoeffs[0],cameraMatrix[1],distCoeffs[1],imageSize,R,T,E,F,CALIB_FIX_ASPECT_RATIO+CALIB_ZERO_TANGENT_DIST+CALIB_USE_INTRINSIC_GUESS+CALIB_SAME_FOCAL_LENGTH+CALIB_RATIONAL_MODEL+CALIB_FIX_K...
但是算法stereoCalibrate()是如何知道要跳过单个摄像头的标定?对此我们设置了CALIB_FIX_INTRINSIC 标志。 步骤2:使用固定的内在参数进行立体标定 当摄像头被标定时,我们把它们传递到stereoCalibrate()方法中,并且设置CALIB_FIX_INTRINSIC标志。我们还传递在两...
为了学习使用Faster R-CNN,需要安装OpenCV +Python环境，之前已经在CentOS下安装好了python2.7。yum安装...
(corners2_right) # 立体相机标定 ret, mtx_left, dist_left, mtx_right, dist_right, R, T, E, F = cv2.stereoCalibrate( objpoints, imgpoints_left, imgpoints_right, gray_left.shape[::-1], gray_right.shape[::-1], None, None, None, None, cv2.CALIB_FIX_INTRINSIC, criteria=cv2....
stereoCalibrate(objectPoints, imagePoints1, imagePoints2, imageSize[, cameraMatrix1[, distCoeffs1[, cameraMatrix2[, distCoeffs2[, R[, T[, E[, F[, criteria[, flags]]]) -> retval, cameraMatrix1, distCoeffs1, cameraMatrix2, distCoeffs2, R, T, E, F stereoRectify...
double rms = stereoCalibrate(objRealPoint, imagePointL, imagePointR, cameraMatrixL, distCoeffL, cameraMatrixR, distCoeffR, Size(imageWidth, imageHeight),R, T,E, F, CALIB_USE_INTRINSIC_GUESS, TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 100, 1e-5...
() cv2.stereoCalibrate() cv2.stereoCalibrateExtended() cv2.stereoRectify() cv2.stereoRectifyUncalibrated() cv2.stylization() cv2.subtract() #两个图像相减 cv2.sumElems() cv2.Scharr() #Scharr边缘提取算子,是Sobel算子的增强算法 cv2.StereoBM #类,用块对应算法计算双目立体匹配 cv2.StereoSGBM #类,用半...
双目摄像头标定主要包括单目标定和双目标定两个阶段。单目标定涉及使用OpenCV的cv::findChessboardCorners、cv::cornerSubPix、cv::calibrateCamera函数，通过查找和处理棋盘格子的角点来获取相机参数。双目标定则使用cv::stereoCalibrate函数，获得更为精确的校准参数。在完成标定后，您可以将获取的参数应用于立体...