opencv+ffmpeg图片序列写Mp4

#include"..\match2\videoWriterFFmpeg.h" #include<iostream> using namespace std; string toString(int a) { char str[10]; sprintf(str, "%d", a); return string(str); } int main() { videoWriterFFmpeg videoWriter; Mat src; string img_name = "F:\\testdata_M2_DF\\error\\PIC_20171209155440787_629\\"; string video_path = "F:\\out.mp4"; int bitrate = 4500000; int fps = 24; if (videoWriter.open((char *)video_path.c_str(), bitrate, fps, 4000,3000) != 0) cout << "error" << endl; for (int i = 0; i < 4; i++) { src = imread(img_name + toString(i) + ".JPG"); for (int j = 0; j < 20; j++) { cout << "write frame " <<i*20+j+1 << " sucess" << endl; videoWriter.write(src); } } videoWriter.flush(); return 0; } ///******************************/ ///* 立体匹配和测距 */ ///******************************/ // //#include <opencv2/opencv.hpp> //#include <iostream> // //using namespace std; //using namespace cv; // //const int imageWidth = 1600; //摄像头的分辨率 //const int imageHeight = 1200; //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 = 0, uniquenessRatio = 0, numDisparities = 0; //Ptr<StereoBM> bm = StereoBM::create(16, 9); // ///* //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) << 1.3326580049539741e+03, 0., 8.5707693143813731e+02, 0., // 1.3328103465314075e+03, 5.8864510013773088e+02, 0., 0., 1.); ////对应matlab里的左相机标定矩阵 //Mat distCoeffL = (Mat_<double>(5, 1) << -2.8045130586483613e-01, 2.3793216045311979e-02, // 1.2707455545866691e-03, -8.5396571769118861e-05, // 1.5333351218494151e-01); ////对应Matlab所得左i相机畸变参数 // //Mat cameraMatrixR = (Mat_<double>(3, 3) << 1.3415015304155293e+03, 0., 8.2015522358224712e+02, 0., // 1.3405584983867755e+03, 6.2602260787344244e+02, 0., 0., 1.); ////对应matlab里的右相机标定矩阵 // //Mat distCoeffR = (Mat_<double>(5, 1) << -2.9689673143127382e-01, 1.4135067565749787e-01, // -5.2500364253100303e-04, -5.9239444589348561e-06, // -5.2601323055946496e-02); ////对应Matlab所得右相机畸变参数 // //Mat T = (Mat_<double>(3, 1) << 6.5772611841823936e-001, -1.0384210259014603e+001, // -4.3222483571379522e+000);//T平移向量 // //对应Matlab所得T参数 ////Mat rec = (Mat_<double>(3, 1) << -0.00306, -0.03207, 0.00206);//rec旋转向量，对应matlab om参数 //Mat R=(Mat_<double>(3,3)<< 9.9992653287053390e-001, -6.5184724487311113e-003, // 1.0219509697052322e-002, 6.5049975997708192e-003, // 9.9997792935128083e-001, 1.3512277941784086e-003, // -1.0228092086992024e-002, -1.2846506373009731e-003, // 9.9994686649091513e-001);//R 旋转矩阵 // // // /*****立体匹配*****/ //void stereo_match(int, void*) //{ // bm->setBlockSize(2 * blockSize + 5); //SAD窗口大小，5~21之间为宜 // bm->setROI1(validROIL); // bm->setROI2(validROIR); // bm->setPreFilterCap(31); // bm->setMinDisparity(0); //最小视差，默认值为0, 可以是负值，int型 // bm->setNumDisparities(numDisparities * 16 + 16);//视差窗口，即最大视差值与最小视差值之差,窗口大小必须是16的整数倍，int型 // bm->setTextureThreshold(10); // bm->setUniquenessRatio(uniquenessRatio);//uniquenessRatio主要可以防止误匹配 // bm->setSpeckleWindowSize(100); // bm->setSpeckleRange(32); // bm->setDisp12MaxDiff(-1); // Mat disp, disp8; // bm->compute(rectifyImageL, rectifyImageR, disp);//输入图像必须为灰度图 // disp.convertTo(disp8, CV_8U, 255 / ((numDisparities * 16 + 16)*16.));//计算出的视差是CV_16S格式 // reprojectImageTo3D(disp, 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 = std::abs(x - origin.x); // selection.height = std::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; // } //} // //Mat scaleMat(Mat src, Size sz) //{ // Size src_sz = src.size(); // if (src_sz == sz) // return src; // Mat dst; // float scale = min(float(src_sz.height) / sz.height, float(src_sz.width) / sz.width); // resize(src, dst, Size(), 1.0 / scale, 1.0 / scale); // return dst(Rect(0, 0, sz.width, sz.height)); //} // ///*****主函数*****/ //int main() //{ // /* // 立体校正 // */ // //Rodrigues(rec, R); //Rodrigues变换 // stereoRectify(cameraMatrixL, distCoeffL, cameraMatrixR, distCoeffR, imageSize, R, T, Rl, Rr, Pl, Pr, Q, 0, // 0, imageSize, &validROIL, &validROIR); // initUndistortRectifyMap(cameraMatrixL, distCoeffL, Rl, Pr, imageSize, CV_32FC1, mapLx, mapLy); // initUndistortRectifyMap(cameraMatrixR, distCoeffR, Rr, Pr, imageSize, CV_32FC1, mapRx, mapRy); // // /* // 读取图片 // */ // // rgbImageL = imread("../calib/13m1/13.bmp", CV_LOAD_IMAGE_COLOR); // cvtColor(rgbImageL, grayImageL, CV_BGR2GRAY); // rgbImageR = imread("../calib/2m1/2.bmp", CV_LOAD_IMAGE_COLOR); // cvtColor(rgbImageR, grayImageR, CV_BGR2GRAY); // Size imgSize = Size(1600, 1200); // rgbImageL = scaleMat(rgbImageL, imgSize); // rgbImageR = scaleMat(rgbImageR, imgSize); // 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, CV_GRAY2BGR); //伪彩色图 // cvtColor(rectifyImageR, rgbRectifyImageR, CV_GRAY2BGR); // resize(rgbRectifyImageL, rgbRectifyImageL, Size(), 0.25, 0.25); // resize(rgbRectifyImageR, rgbRectifyImageR, Size(), 0.25, 0.25); // //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 = canv