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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
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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 <tchar.h>
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#include <windows.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 namespace std;
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using namespace cv;
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#define TEST_WITH_AID 0 // 是否使用AI Detect
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#define TEST_WITH_AIT 0 // 是否使用AI Tracker，如果设置为1，最外部的CMakeLists.txt 需要设置set(BUILD_AI_TRACK TRUE)
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#if TEST_WITH_AID
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#include "Arith_YOLO_Detect.h"
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#endif
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#if TEST_WITH_AIT
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#include "Arith_AITracker.h"
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#endif
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unsigned short bcmd = 0;
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short SelectCX = 0;
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short SelectCY = 0;
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unsigned short setLockBoxW = 0;
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unsigned short setLockBoxH = 0;
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bool draw = false;
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cv::Point cursor = cv::Point(0, 0);
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cv::Rect rect;
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int key;
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cv::Mat frame, dstImage;
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//控制视频流
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VideoCapture capture;
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const char* windowName = "test"; //播放窗口名称
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const char* trackBarName = "Progress"; //trackbar控制条名称
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double totalFrame = 1.0; //视频总帧数
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double currentFrame = 1.0; //当前播放帧
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int trackbarValue = 1; //trackbar控制量
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int trackbarMax = 255; //trackbar控制条最大值
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double frameRate = 1.0; //视频帧率
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double controlRate = 0.1;
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int frameValue = 0;
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// 算法输入部分
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ARIDLL_INPUTPARA stInputPara = { 0 };
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// 算法输出部分
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ARIDLL_OUTPUT stOutput = { 0 };
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// AI Detect算法结果
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#if TEST_WITH_AID
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obj_res* g_pGLB_AIDetOutput = NULL;
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int g_GLB_AIDetNum = 0;
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#endif
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// AI Tracker算法结果
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#if TEST_WITH_AIT
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API_AI_Tracker* g_GLB_AITracker = NULL;
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AIT_OUTPUT g_GLB_AITrackOutput = { 0 };
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#endif
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//控制条回调函数
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static void TrackBarFunc(int, void(*))
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{
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controlRate = (double)trackbarValue / trackbarMax * totalFrame; //trackbar控制条对视频播放进度的控制
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capture.set(CAP_PROP_POS_FRAMES, controlRate); //设置当前播放帧
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frameValue = controlRate;
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}
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static void onMouse(int event, int x, int y, int flags, void* param)
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{
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//flags定义#define CV_EVENT_FLAG_LBUTTON 1 左鍵拖曳
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switch (event)
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{
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case cv::EVENT_LBUTTONDOWN: // 鼠标左键按下
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SelectCX = x;
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SelectCY = y;
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cursor = cv::Point(x, y);
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rect = cv::Rect(x, y, 0, 0);
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draw = true;
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break;
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case cv::EVENT_LBUTTONUP: //鼠标左键松开
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setLockBoxW = rect.width;
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setLockBoxH = rect.height;
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SelectCX = rect.x + rect.width / 2;
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SelectCY = rect.y + rect.height / 2;
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bcmd = 1;
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draw = false;
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break;
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case cv::EVENT_RBUTTONDOWN: //鼠标右键按下
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bcmd = 2;
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break;
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case cv::EVENT_RBUTTONUP: //鼠标右键松开
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break;
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case cv::EVENT_MBUTTONUP://左键双击
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bcmd = 1;
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break;
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case cv::EVENT_MOUSEMOVE: //移动光标
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if (draw)
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{
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cv::Mat dstImage1 = frame.clone();
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rect.x = MIN(x, cursor.x);
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rect.y = MIN(y, cursor.y);
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rect.width = abs(cursor.x - x);
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rect.height = abs(cursor.y - y);
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rectangle(dstImage1, rect, cv::Scalar(0, 0, 255), 1);
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cv::imshow("test", dstImage1);
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}
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break;
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}
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}
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#if TEST_WITH_AID
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static void AIDetRun(ArithHandle pTracker, GD_VIDEO_FRAME_S img, int frameID)
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{
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// 异步调用，考虑机器上传输延时，注意异步方式结果天然缓1帧。
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Async_YOLO_DetectTarget(img.u64VirAddr[0], img.u32Width, img.u32Height, frameID);
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g_pGLB_AIDetOutput = Async_YOLO_GetTargetArray(g_GLB_AIDetNum);
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int targetNum = 0;
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TARGET_OBJECT* pArray = ARIDLL_SearchFrameTargets(pTracker, img, &targetNum);
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int mergeNum = ARIDLL_MergeAITargets(pTracker, pArray, targetNum, g_pGLB_AIDetOutput, g_GLB_AIDetNum);
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stInputPara.nInputTargetNum = mergeNum;
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memcpy(stInputPara.stInputTarget, pArray, sizeof(TARGET_OBJECT) * mergeNum);
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}
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#endif
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#if TEST_WITH_AIT
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static int AITrackerRun(GD_VIDEO_FRAME_S img, int frameID)
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{
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// 从传统算法输出中获取AI跟踪器的控制指令
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CENTERRECT32F InitBox = stOutput.stAI_TkCmd.InitBox;
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CENTERRECT32F TargetBox = stOutput.stAI_TkCmd.TargetBox;
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if (InitBox.w > 0 && InitBox.h > 0)
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{
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g_GLB_AITracker->init(img, InitBox);
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return 0;
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}
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if (!stOutput.stAI_TkCmd.bTrack)
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{
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g_GLB_AITracker->stopTrack();
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memset(&stInputPara.stAITrackerInfo, 0, sizeof(AIT_OUTPUT));
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memset(&g_GLB_AITrackOutput, 0, sizeof(AIT_OUTPUT));
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return 0;
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}
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g_GLB_AITracker->Track(img, TargetBox);
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g_GLB_AITracker->getTrackResult_Async(&g_GLB_AITrackOutput);
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// 向传统算法传参
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memcpy(&stInputPara.stAITrackerInfo, &g_GLB_AITrackOutput, sizeof(AIT_OUTPUT));
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return 0;
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}
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#endif
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static void RunProcess(ArithHandle pTracker, GD_VIDEO_FRAME_S img)
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{
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#if TEST_WITH_AID
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// 运行AI识别算法
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AIDetRun(pTracker, img, stInputPara.unFrmId);
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#endif
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#if TEST_WITH_AIT
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// 运行SiamRPN跟踪算法
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AITrackerRun(img, stInputPara.unFrmId);
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#endif
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// 调用TLD流程
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//ARIDLL_RunTLDTracker(pTracker, img);
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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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}
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int main()
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{
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#ifdef _WIN32
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char message[128];
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TCHAR szBuffer[MAX_PATH] = { 0 };
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OPENFILENAME ofn = { 0 };
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ofn.lStructSize = sizeof(ofn);
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//ofn.hwndOwner = m_hWnd;
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ofn.lpstrFilter = _T("所有文件(*.*)\0*.*\0Exe文件(*.mp4)\0*.avi\0");//要选择的文件后缀
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ofn.lpstrInitialDir = _T("F:\\Datasets\\20240219_AutoTest");//默认的文件路径
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ofn.lpstrFile = szBuffer;//存放文件的缓冲区
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ofn.nMaxFile = sizeof(szBuffer) / sizeof(*szBuffer);
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ofn.nFilterIndex = 0;
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ofn.Flags = OFN_PATHMUSTEXIST | OFN_FILEMUSTEXIST | OFN_EXPLORER;//标志如果是多选要加上OFN_ALLOWMULTISELECT
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bool bSel = GetOpenFileName(&ofn);
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string video_fileName = ofn.lpstrFile;
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capture.open(video_fileName);
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if (!capture.isOpened())
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return 0;
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#elif __linux__
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cv::VideoCapture capture("/home/temp/VL_公司门口车辆3.avi");
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#endif
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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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//控制视频流进度
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totalFrame = capture.get(CAP_PROP_FRAME_COUNT); //获取总帧数
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frameRate = capture.get(CAP_PROP_FPS); //获取帧率
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trackbarMax = totalFrame;
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namedWindow(windowName, 0);
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//resizeWindow(windowName, 960, 540);
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//在图像窗口上创建控制条
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createTrackbar(trackBarName, windowName, &trackbarValue, trackbarMax, TrackBarFunc);
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TrackBarFunc(0, 0);
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// 创建算法句柄
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ArithHandle pTracker = STD_CreatEOArithHandle();
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#if TEST_WITH_AID
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// AI检测初始化
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//YOLO_Init();
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Async_YOLO_Init();
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#endif
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#if TEST_WITH_AIT
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// AI跟踪器初始化
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//CreatSiamRPN();
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//Async_CreatSiamRPN();
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// AI跟踪器初始化
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g_GLB_AITracker = API_AI_Tracker::Create(AITrackerType::DaSaimRPN);
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g_GLB_AITracker->loadModel();
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memset(&g_GLB_AITrackOutput, 0, sizeof(AIT_OUTPUT));
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#endif
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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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stInputPara.unFreq = frameRate;
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stInputPara.stAirCraftInfo.stAtt.fYaw = 0;
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stInputPara.stAirCraftInfo.stAtt.fRoll = 0;
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stInputPara.stAirCraftInfo.stAtt.fPitch = 0;
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stInputPara.stServoInfo.fServoAz = 0;
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stInputPara.stServoInfo.fServoPt = 0;
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stInputPara.stCameraInfo.fPixelSize = 15;
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stInputPara.stCameraInfo.nFocus = 600;
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stInputPara.unFrmId = 0;
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//stInputPara.nInputTargetNum = 0;
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while(1)
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{
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stInputPara.unFrmId++;
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//stInputPara.nInputTargetNum = 0;
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capture.read(frame);
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if (frame.empty())
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{
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/*
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capture.set(CAP_PROP_POS_FRAMES, 0);
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frameValue = 0;
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capture >> frame;*/
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break;
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}
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dstImage = frame.clone();
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///控制台交互界面调试用----------------------------------
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//cv::namedWindow("SOT_TRACKING", cv::WINDOW_NORMAL);
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cv::setMouseCallback(windowName, onMouse, NULL);
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// 首帧算法内部需要初始化，不要进行锁定
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if (key == 32 || stInputPara.unFrmId == 2)
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{
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imshow("test", frame);
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waitKey(0);
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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_RGB_PACKED;
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img.u32Width = nWidth;
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img.u32Height = nHeight;
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img.u32Stride[0] = img.u32Width * 3;
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img.u64VirAddr[0] = frame.data;
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//点选转跟踪
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if (1 == bcmd)
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{
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/* setLockBoxW = 65;
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setLockBoxH = 31;
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SelectCX = 1525 + setLockBoxW / 2;
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SelectCY = 354 + setLockBoxH / 2;*/
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//ARIDLL_LockCommand(pTracker, SelectCX, SelectCY, setLockBoxW, setLockBoxH);
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// 调用该接口，可在当前帧完成锁定响应，不必缓一帧得到结果有利于运动目标锁定，同时将锁定决策结果返回，提供外部跟踪器同步锁定
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// 主要原因是点选锁定时无宽高，波门设置等来源于传统跟踪器决策结果。
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ARIDLL_OBJINFO obj = { 0 };
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obj = ARIDLL_LockTarget(pTracker, img, SelectCX, SelectCY, setLockBoxW, setLockBoxH);
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#if TEST_WITH_AIT
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if (obj.nObjW > 0)
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{
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// 使用EOTracker的锁定决策初始化AI跟踪器
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CENTERRECT32F initBox = { obj.nX,obj.nY, obj.nObjW, obj.nObjH };
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g_GLB_AITracker->init(img, initBox);
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// 获取跟踪结果
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g_GLB_AITracker->getTrackResult_Async(&g_GLB_AITrackOutput);
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}
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#endif
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}
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//右键解锁退出跟踪状态
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if (2 == bcmd)
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{
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// 解锁传统跟踪器
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ARIDLL_unLockCommand(pTracker, SelectCX, SelectCY, 0);
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#if TEST_WITH_AIT
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// 解锁AI跟踪器
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g_GLB_AITracker->stopTrack();
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#endif
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}
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RunProcess(pTracker, img);
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auto trackerOut = stOutput.stTrackers[0];
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cv::Rect outRect;
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outRect.width = (int)trackerOut.nObjW;
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outRect.height= (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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cv::rectangle(dstImage, outRect, cv::Scalar(0, 0, 255));
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//cv::rectangle(dstImage, cv::Rect(g_GLB_AITrackOutput.fX - g_GLB_AITrackOutput.nObjW / 2,
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// g_GLB_AITrackOutput.fY - g_GLB_AITrackOutput.nObjH / 2,
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// g_GLB_AITrackOutput.nObjW,
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// g_GLB_AITrackOutput.nObjH), cv::Scalar(0, 255, 255));
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bcmd = 0;
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SelectCX = 0;
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SelectCY = 0;
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setLockBoxW = 0;
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setLockBoxH = 0;
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cv::imshow("test", dstImage);
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key = cv::waitKey(10);
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}
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return 0;
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} |
