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// 单目标对地跟踪流程测试:将TLD从算法中剥离到外部，导致API调用形式调整int argc,char *argv[]
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// 读取avi视频进行测试
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#include "NeoArithStandardDll.h"
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#include "utils.h"
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#include <iostream>
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#include <memory>
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#include <string.h>
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#include <algorithm>
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#include <thread>
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#include "opencv2/opencv.hpp"
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using std::cout;
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using std::endl;
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using std::string;
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using namespace cv;
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void convertRGBToNV12(const cv::Mat& rgb, cv::Mat& yuv) {
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if (rgb.empty()) {
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std::cerr << "Input image is empty." << std::endl;
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return;
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}
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// 将RGB转换为YUV格式（YUV444）
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cv::Mat yuv444;
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cv::cvtColor(rgb, yuv444, cv::COLOR_BGR2YUV);
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// 准备Y和UV平面
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int width = rgb.cols;
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int height = rgb.rows;
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// NV12格式需要的尺寸
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yuv.create(height + height / 2, width, CV_8UC1);
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// 提取Y通道
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for (int i = 0; i < height; ++i) {
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for (int j = 0; j < width; ++j) {
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yuv.at<uchar>(i, j) = yuv444.at<cv::Vec3b>(i, j)[0];
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}
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}
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// 提取UV平面（交替存储）
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for (int i = 0; i < height / 2; ++i) {
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for (int j = 0; j < width / 2; ++j) {
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int u = 0, v = 0;
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for (int k = 0; k < 2; ++k) {
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for (int l = 0; l < 2; ++l) {
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u += yuv444.at<cv::Vec3b>(2 * i + k, 2 * j + l)[1];
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v += yuv444.at<cv::Vec3b>(2 * i + k, 2 * j + l)[2];
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}
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}
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// 平均化UV值并存储
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yuv.at<uchar>(height + i, 2 * j) = static_cast<uchar>(u / 4);
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yuv.at<uchar>(height + i, 2 * j + 1) = static_cast<uchar>(v / 4);
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}
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}
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}
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int main(int argc,char *argv[])
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{
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cv::VideoCapture capture(argv[1]);
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printf("argv[0]:%s\n",argv[1]);
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int nWidth = int(capture.get(cv::CAP_PROP_FRAME_WIDTH));
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int nHeight = int(capture.get(cv::CAP_PROP_FRAME_HEIGHT));
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// 创建算法句柄
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ArithHandle pTracker = STD_CreatEOArithHandle();
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// 初始化为凝视-对地模式
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ARIDLL_EOArithInitWithMode(pTracker,nWidth,nHeight,GD_PIXEL_FORMAT_E::GD_PIXEL_FORMAT_RGB_PACKED,
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GLB_SYS_MODE::GLB_SYS_STARE,GLB_SCEN_MODE::GLB_SCEN_GROUND);
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// 算法输入部分
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ARIDLL_INPUTPARA stInputPara = { 0 };
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stInputPara.unFrmId++;
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stInputPara.stCameraInfo.fPixelSize = 15;
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stInputPara.stCameraInfo.nFocus = 300;
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// 算法输出部分
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ARIDLL_OUTPUT stOutput = { 0 };
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// 模拟算法执行流程
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int nTrackSuc = 0;
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cv::Mat frame;
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cv::Mat framenv12;
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while(1)
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{
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stInputPara.unFrmId++;
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capture.read(frame);
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convertRGBToNV12(frame,framenv12);
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// cv::Mat bgr;
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// cv::cvtColor(framenv12, bgr, cv::COLOR_YUV2BGR_NV12);
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// imshow("bgr",bgr);
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// waitKey(1);
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if(frame.empty())
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break;
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// 下发面锁定指令
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if (stInputPara.unFrmId == 10)
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{
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ARIDLL_LockCommand(pTracker, 228*2,279*2,40,25);
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}
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// 构建图像类型
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GD_VIDEO_FRAME_S img = { 0 };
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img.enPixelFormat = GD_PIXEL_FORMAT_E::GD_PIXEL_FORMAT_NV12;
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img.u32Width = nWidth;
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img.u32Height = nHeight;
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img.u32Stride[0] = img.u32Width;
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img.u64VirAddr[0] = framenv12.data;
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// 运行算法主控逻辑API
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ARIDLL_RunController(pTracker, img, stInputPara, &stOutput);
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cv::Mat bgr;
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cv::cvtColor(framenv12, bgr, cv::COLOR_YUV2BGR_NV12);
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auto trackerOut = stOutput.stTrackers[0];
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cv::Rect outRect;
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outRect.width = MAX(15,(int)trackerOut.nObjW);
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outRect.height= MAX(15, (int)trackerOut.nObjH);
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outRect.x = (int)trackerOut.nX-outRect.width/2;
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outRect.y = (int)trackerOut.nY-outRect.height/2;
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printf("%f,%f,%f,%f\n",trackerOut.nX,trackerOut.nY,trackerOut.nObjW,trackerOut.nObjH);
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//cv::rectangle(bgr,outRect,cv::Scalar(0,0,255));
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//cv::resize(bgr,bgr,cv::Size(nWidth/2,nHeight/2));
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//imshow("res",bgr);
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//cv::waitKey(2);
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}
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if(fabs(stOutput.stTrackers[0].nX - 1508) < 20 &&
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fabs(stOutput.stTrackers[0].nY - 750) < 20)
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{
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cout << "pass" << endl;
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}
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return 0;
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}
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