幸运的永恒533的个人资料

新人求助：关于立体校正和视差图，求大佬帮忙看看 const int imageWidth = 640; //摄像头的分辨率 const int imageHeight = 480; Size imageSize = Size(imageWidth, imageHeight); Mat rgbImageL, grayImageL; Mat rgbImageR, grayImageR; Mat rectifyImageL, rectifyImageR; Rect validROIL;//图像校正之后，会对图像进行裁剪，这里的validROI就是指裁剪之后的区域 Rect validROIR; Mat mapLx, mapLy, mapRx, mapRy; //映射表 Mat Rl, Rr, Pl, Pr, Q; //校正旋转矩阵R，投影矩阵P 重投影矩阵Q Mat xyz; //三维坐标 Point origin; //鼠标按下的起始点 Rect selection; //定义矩形选框 bool selectObject = false; //是否选择对象 //int blockSize = 3, uniquenessRatio = 10, numDisparities = 16; Ptr<StereoSGBM> sgbm = StereoSGBM::create(0,16,3); /* 事先标定好的相机的参数 fx 0 cx 0 fy cy 0 0 1 */ Mat cameraMatrixL = (Mat_<double>(3, 3) << 730.9859, 0.1427 , 294.2559, 0 , 735.3010, 261.9521, 0 , 0 , 1 ); Mat distCoeffL = (Mat_<double>(5, 1) << -0.4740, 0.1766,0.0017, -0.0039,0.1152); Mat cameraMatrixR = (Mat_<double>(3, 3) << 734.7534, 0.2424 , 283.8769, 0 , 737.4809, 342.1307, 0 , 0 , 1 ); Mat distCoeffR = (Mat_<double>(5, 1) << -0.5229, 0.6307,-0.0004, -0.0037,-0.7994); Mat T = (Mat_<double>(3, 1) << 9.1664, 0.0753, -0.2054);//T平移向量 //Mat rec = (Mat_<double>(3, 1) << -0.00306, -0.03207, 0.00206);//rec旋转向量 Mat R = (Mat_<double>(3, 3) << 0.9997, 0.0175, -0.0140, -0.0172, 0.9996, 0.0207, 0.0144, -0.0204, 0.9997); /*****立体匹配*****/ void stereo_match(int, void*) { sgbm->setPreFilterCap(15); int sgbmWinSize = 5;//根据实际情况自己设定 int NumDisparities = 624;//根据实际情况自己设定 int UniquenessRatio = 10;//根据实际情况自己设定 sgbm->setBlockSize(sgbmWinSize); int cn = rectifyImageL.channels(); sgbm->setP1(8 * cn*sgbmWinSize*sgbmWinSize); sgbm->setP2(32 * cn*sgbmWinSize*sgbmWinSize); sgbm->setMinDisparity(0); sgbm->setNumDisparities(NumDisparities); sgbm->setUniquenessRatio(UniquenessRatio); sgbm->setSpeckleWindowSize(100); sgbm->setSpeckleRange(10); sgbm->setDisp12MaxDiff(1); sgbm->setMode(StereoSGBM::MODE_SGBM); Mat disp, dispf, disp8; sgbm->compute(rectifyImageL, rectifyImageR, disp); //去黑边 Mat img1p, img2p; copyMakeBorder(rectifyImageL, img1p, 0, 0, NumDisparities, 0, IPL_BORDER_REPLICATE); copyMakeBorder(rectifyImageR, img2p, 0, 0, NumDisparities, 0, IPL_BORDER_REPLICATE); dispf = disp.colRange(NumDisparities, img2p.cols - NumDisparities); dispf.convertTo(disp8, CV_8U, 255 / (NumDisparities *16.)); reprojectImageTo3D(dispf, xyz, Q, true); //在实际求距离时，ReprojectTo3D出来的X / W, Y / W, Z / W都要乘以16(也就是W除以16)，才能得到正确的三维坐标信息。 xyz = xyz * 16; imshow("disparity", disp8); } /*****描述：鼠标操作回调*****/ static void onMouse(int event, int x, int y, int, void*) { if (selectObject) { selection.x = MIN(x, origin.x); selection.y = MIN(y, origin.y); selection.width = abs(x - origin.x); selection.height = abs(y - origin.y); } switch (event) { case EVENT_LBUTTONDOWN: //鼠标左按钮按下的事件 origin = Point(x, y); selection = Rect(x, y, 0, 0); selectObject = true; cout << origin << "in world coordinate is: " << xyz.at<Vec3f>(origin) << endl; break; case EVENT_LBUTTONUP: //鼠标左按钮释放的事件 selectObject = false; if (selection.width > 0 && selection.height > 0) break; } } int main(int argc, char** argv) { stereoRectify(cameraMatrixL, distCoeffL, cameraMatrixR, distCoeffR, imageSize, R, T, Rl, Rr, Pl, Pr, Q, CALIB_ZERO_DISPARITY, -1, imageSize, &validROIL, &validROIR); initUndistortRectifyMap(cameraMatrixL, distCoeffL, Rl, Pl, imageSize, CV_16SC2, mapLx, mapLy); initUndistortRectifyMap(cameraMatrixR, distCoeffR, Rr, Pr, imageSize, CV_16SC2, mapRx, mapRy); /* 读取图片 */ rgbImageL = imread("came04L.jpg", -1); cvtColor(rgbImageL, grayImageL, COLOR_BGR2GRAY); rgbImageR = imread("came04R.jpg", -1); cvtColor(rgbImageR, grayImageR, COLOR_BGR2GRAY); imshow("ImageL Before Rectify", grayImageL); imshow("ImageR Before Rectify", grayImageR); /* 经过remap之后，左右相机的图像已经共面并且行对准了 */ remap(grayImageL, rectifyImageL, mapLx, mapLy, INTER_LINEAR); remap(grayImageR, rectifyImageR, mapRx, mapRy, INTER_LINEAR); /* 把校正结果显示出来 */ Mat rgbRectifyImageL, rgbRectifyImageR; cvtColor(rectifyImageL, rgbRectifyImageL, COLOR_GRAY2BGR); //伪彩色图 cvtColor(rectifyImageR, rgbRectifyImageR, COLOR_GRAY2BGR); //单独显示 //rectangle(rgbRectifyImageL, validROIL, Scalar(0, 0, 255), 3, 8); //rectangle(rgbRectifyImageR, validROIR, Scalar(0, 0, 255), 3, 8); imshow("ImageL After Rectify", rgbRectifyImageL); imshow("ImageR After Rectify", rgbRectifyImageR); //显示在同一张图上 Mat canvas; double sf; int w, h; sf = 600. / MAX(imageSize.width, imageSize.height); w = cvRound(imageSize.width * sf); h = cvRound(imageSize.height * sf); canvas.create(h, w * 2, CV_8UC3); //注意通道 //左图像画到画布上 Mat canvasPart = canvas(Rect(w * 0, 0, w, h)); //得到画布的一部分 resize(rgbRectifyImageL, canvasPart, canvasPart.size(), 0, 0, INTER_AREA); //把图像缩放到跟canvasPart一样大小 Rect vroiL(cvRound(validROIL.x*sf), cvRound(validROIL.y*sf), //获得被截取的区域 cvRound(validROIL.width*sf), cvRound(validROIL.height*sf)); rectangle(canvasPart, vroiL, Scalar(0, 0, 255), 3, 8); //画上一个矩形 cout << "Painted ImageL" << endl; //右图像画到画布上 canvasPart = canvas(Rect(w, 0, w, h)); //获得画布的另一部分 resize(rgbRectifyImageR, canvasPart, canvasPart.size(), 0, 0, INTER_LINEAR); Rect vroiR(cvRound(validROIR.x * sf), cvRound(validROIR.y*sf), cvRound(validROIR.width * sf), cvRound(validROIR.height * sf)); rectangle(canvasPart, vroiR, Scalar(0, 0, 255), 3, 8); cout << "Painted ImageR" << endl; //画上对应的线条 for (int i = 0; i < canvas.rows; i += 16) line(canvas, Point(0, i), Point(canvas.cols, i), Scalar(0, 255, 0), 1, 8); imshow("rectified", canvas); /* 立体匹配 */ namedWindow("disparity", WINDOW_NORMAL); setMouseCallback("disparity", onMouse, 0); stereo_match(0,0); waitKey(0); return 0; }

刚被电子信息类录取学长学姐可不可以给我介绍？包括注意事项之类的

川大的软件工程是什么水平呢

想请问学长学姐们金属材料工程在川大怎样看到这个专业在全国排名第一但收分却不高是因为不好就业报的人才少吗？