|
|
// 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
|
|
|
// 读取avi视频进行测试
|
|
|
#include "NeoArithStandardDll.h"
|
|
|
#include "S3312.h" // 解析3312参数行数据需要包含
|
|
|
#include "S338.h" // 解析338参数行数据需要包含
|
|
|
#include <iostream>
|
|
|
#include <memory>
|
|
|
#include <string.h>
|
|
|
#include <algorithm>
|
|
|
#include <thread>
|
|
|
#include "opencv2/opencv.hpp"
|
|
|
|
|
|
#define TEST_WITH_AID 0 // 是否使用AI Detect
|
|
|
#define TEST_WITH_AIT 0 // 是否使用AI Tracker
|
|
|
|
|
|
#define VOT_RECTANGLE
|
|
|
#define VOT_IR
|
|
|
#include "vot.h"
|
|
|
|
|
|
#if TEST_WITH_AID
|
|
|
#include "Arith_YOLO_Detect.h"
|
|
|
#endif
|
|
|
|
|
|
#if TEST_WITH_AIT
|
|
|
#include "Arith_AITracker.h"
|
|
|
#endif
|
|
|
|
|
|
using std::cout;
|
|
|
using std::endl;
|
|
|
|
|
|
short SelectCX = 0;
|
|
|
short SelectCY = 0;
|
|
|
unsigned short setLockBoxW = 0;
|
|
|
unsigned short setLockBoxH = 0;
|
|
|
|
|
|
int m_ArithName = 338; // 项目对应的红外测试数据338,3312
|
|
|
|
|
|
// 算法输入部分
|
|
|
ARIDLL_INPUTPARA stInputPara = { 0 };
|
|
|
|
|
|
// 算法输出部分
|
|
|
ARIDLL_OUTPUT stOutput = { 0 };
|
|
|
|
|
|
// 构建图像输入
|
|
|
GD_VIDEO_FRAME_S img = { 0 };
|
|
|
|
|
|
// S3312参数行解析结构体
|
|
|
Commdef::TParaWriteBackToFpga g_S3312_Para = { 0 }; // S3312录像参数临时变量
|
|
|
|
|
|
// AI Detect算法结果
|
|
|
#if TEST_WITH_AID
|
|
|
obj_res* g_pGLB_AIDetOutput = NULL;
|
|
|
int g_GLB_AIDetNum = 0;
|
|
|
#endif
|
|
|
|
|
|
// AI Tracker算法结果
|
|
|
#if TEST_WITH_AIT
|
|
|
API_AI_Tracker* g_GLB_AITracker = NULL;
|
|
|
AIT_OUTPUT g_GLB_AITrackOutput = { 0 };
|
|
|
#endif
|
|
|
|
|
|
#if TEST_WITH_AID
|
|
|
static void AIDetRun(ArithHandle pTracker, GD_VIDEO_FRAME_S img, int frameID)
|
|
|
{
|
|
|
// 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。
|
|
|
Async_YOLO_DetectTarget(img.u64VirAddr[0], img.u32Width, img.u32Height, frameID);
|
|
|
g_pGLB_AIDetOutput = Async_YOLO_GetTargetArray(g_GLB_AIDetNum);
|
|
|
|
|
|
int targetNum = 0;
|
|
|
TARGET_OBJECT* pArray = ARIDLL_SearchFrameTargets(pTracker, img, &targetNum);
|
|
|
|
|
|
int mergeNum = ARIDLL_MergeAITargets(pTracker, pArray, targetNum, g_pGLB_AIDetOutput, g_GLB_AIDetNum);
|
|
|
stInputPara.nInputTargetNum = mergeNum;
|
|
|
memcpy(stInputPara.stInputTarget, pArray, sizeof(TARGET_OBJECT) * mergeNum);
|
|
|
|
|
|
}
|
|
|
#endif
|
|
|
|
|
|
|
|
|
|
|
|
#if TEST_WITH_AIT
|
|
|
static int AITrackerRun(GD_VIDEO_FRAME_S img, int frameID)
|
|
|
{
|
|
|
// 从传统算法输出中获取AI跟踪器的控制指令
|
|
|
CENTERRECT32F InitBox = stOutput.stAI_TkCmd.InitBox;
|
|
|
CENTERRECT32F TargetBox = stOutput.stAI_TkCmd.TargetBox;
|
|
|
|
|
|
if (InitBox.w > 0 && InitBox.h > 0)
|
|
|
{
|
|
|
g_GLB_AITracker->init(img, InitBox);
|
|
|
return 0;
|
|
|
}
|
|
|
if (!stOutput.stAI_TkCmd.bTrack)
|
|
|
{
|
|
|
g_GLB_AITracker->stopTrack();
|
|
|
memset(&stInputPara.stAITrackerInfo, 0, sizeof(AIT_OUTPUT));
|
|
|
memset(&g_GLB_AITrackOutput, 0, sizeof(AIT_OUTPUT));
|
|
|
return 0;
|
|
|
}
|
|
|
|
|
|
g_GLB_AITracker->Track(img, TargetBox);
|
|
|
|
|
|
// 获取跟踪结果
|
|
|
g_GLB_AITracker->getTrackResult_Async(&g_GLB_AITrackOutput);
|
|
|
|
|
|
// 向传统算法传参
|
|
|
memcpy(&stInputPara.stAITrackerInfo, &g_GLB_AITrackOutput, sizeof(AIT_OUTPUT));
|
|
|
|
|
|
return 0;
|
|
|
}
|
|
|
#endif
|
|
|
|
|
|
static void RunProcess(ArithHandle pTracker, GD_VIDEO_FRAME_S img)
|
|
|
{
|
|
|
#if TEST_WITH_AID
|
|
|
// 运行AI识别算法
|
|
|
AIDetRun(pTracker, img, stInputPara.unFrmId);
|
|
|
#endif
|
|
|
|
|
|
#if TEST_WITH_AIT
|
|
|
// 运行SiamRPN跟踪算法
|
|
|
AITrackerRun(img, stInputPara.unFrmId);
|
|
|
#endif
|
|
|
// 调用小面目标检测
|
|
|
int targetNum = ARIDLL_SearchFrameTargets(pTracker, img);
|
|
|
|
|
|
// 运行算法主控逻辑API
|
|
|
ARIDLL_RunController(pTracker, img, stInputPara, &stOutput);
|
|
|
}
|
|
|
|
|
|
|
|
|
#ifdef _WIN32 // Windows平台
|
|
|
|
|
|
|
|
|
#elif __linux__ // Linux平台
|
|
|
|
|
|
|
|
|
#include <unistd.h>
|
|
|
|
|
|
|
|
|
//检查文件(所有类型)是否存在
|
|
|
//-1:存在 0:不存在
|
|
|
int IsFileExist(const char* path)
|
|
|
{
|
|
|
return !access(path, F_OK);
|
|
|
}
|
|
|
|
|
|
#else
|
|
|
|
|
|
#error Unsupported platform
|
|
|
|
|
|
#endif
|
|
|
|
|
|
|
|
|
|
|
|
int main()
|
|
|
{
|
|
|
VOT vot;
|
|
|
|
|
|
cv::Rect initialization;
|
|
|
|
|
|
int nParamLineCnt2 = 4; // 参数行数
|
|
|
int nImageWidth = 512; // 图像宽度
|
|
|
int nImageHeight = 640; // 图像高度
|
|
|
|
|
|
if (338 == m_ArithName)
|
|
|
{
|
|
|
nParamLineCnt2 = 4;
|
|
|
nImageWidth = 512;
|
|
|
nImageHeight = 640;
|
|
|
}
|
|
|
else if (3312 == m_ArithName)
|
|
|
{
|
|
|
nParamLineCnt2 = 9;
|
|
|
nImageWidth = 640;
|
|
|
nImageHeight = 512;
|
|
|
}
|
|
|
int nHeightWithParm = nImageHeight + nParamLineCnt2; // 叠加参数行后图像高度
|
|
|
|
|
|
|
|
|
int m_lImageDataSize = nImageWidth * nImageHeight; //图像大小，不包括参数行
|
|
|
int m_lArithReslutDataSize = nImageWidth * 2 * nParamLineCnt2; // 帧后参数占用空间（包括算法结果以及录像参数行）
|
|
|
|
|
|
|
|
|
///////////////////输入图像处理//////////////////////////////
|
|
|
// 算法库的输入数据类型PIXELTYPE需要定位为unsigned short
|
|
|
cv::Mat srcImageWithPara(nHeightWithParm, nImageWidth, CV_16UC1);
|
|
|
cv::Mat srcImage(nImageHeight, nImageWidth, CV_16UC1);
|
|
|
|
|
|
// 创建算法句柄
|
|
|
ArithHandle pTracker = STD_CreatEOArithHandle();
|
|
|
|
|
|
#if TEST_WITH_AID
|
|
|
// AI检测初始化
|
|
|
//YOLO_Init();
|
|
|
Async_YOLO_Init();
|
|
|
#endif
|
|
|
|
|
|
#if TEST_WITH_AIT
|
|
|
// AI跟踪器初始化
|
|
|
g_GLB_AITracker = API_AI_Tracker::Create(AITrackerType::DaSaimRPN);
|
|
|
g_GLB_AITracker->loadModel();
|
|
|
|
|
|
memset(&g_GLB_AITrackOutput, 0, sizeof(AIT_OUTPUT));
|
|
|
#endif
|
|
|
// 初始化为凝视-对空模式
|
|
|
ARIDLL_EOArithInitWithMode(pTracker, nImageWidth, nImageHeight, GD_PIXEL_FORMAT_E::GD_PIXEL_FORMAT_GRAY_Y16,
|
|
|
GLB_SYS_MODE::GLB_SYS_STARE, GLB_SCEN_MODE::GLB_SCEN_SKY);
|
|
|
|
|
|
// 加载的参数文件需要跟随算法库一同更新
|
|
|
#ifdef _WIN32
|
|
|
std::string configFilePath = std::string(SOURCE_PATH) + "/NeoTracker/vot_test/ArithParaIR.json";
|
|
|
#else
|
|
|
|
|
|
std::string configFilePath = std::string(SOURCE_PATH) + "/NeoTracker/vot_test/ArithParaIR.json";
|
|
|
|
|
|
int isexist = IsFileExist(configFilePath.c_str());
|
|
|
if (0 == isexist)
|
|
|
{
|
|
|
// 用于自动化测试路径，192.168.1.11自动化测试服务器模型路径
|
|
|
configFilePath = "/mnt/dataD/VotToolkit/trackers/Native/NeoTracker/ArithParaIR.json";
|
|
|
}
|
|
|
#endif
|
|
|
|
|
|
ARIDLL_ReadSetParamFile(pTracker, configFilePath.c_str());
|
|
|
stInputPara.unFreq = 50;
|
|
|
stInputPara.stAirCraftInfo.stAtt.fYaw = 0;
|
|
|
stInputPara.stAirCraftInfo.stAtt.fRoll = 0;
|
|
|
stInputPara.stAirCraftInfo.stAtt.fPitch = 0;
|
|
|
stInputPara.stServoInfo.fServoAz = 0;
|
|
|
stInputPara.stServoInfo.fServoPt = 0;
|
|
|
stInputPara.stCameraInfo.fPixelSize = 15;
|
|
|
stInputPara.stCameraInfo.nFocus = 600;
|
|
|
stInputPara.unFrmId = 0;
|
|
|
|
|
|
|
|
|
// 模拟算法执行流程
|
|
|
while(!vot.end())
|
|
|
{
|
|
|
|
|
|
string imagepath = vot.frame();
|
|
|
|
|
|
if (imagepath.empty())
|
|
|
{
|
|
|
break;
|
|
|
}
|
|
|
ifstream inFile(imagepath, ios::in | ios::binary);
|
|
|
inFile.read((char*)srcImageWithPara.data, sizeof(short) * nHeightWithParm * nImageWidth);// 所有的单帧数据（包括图像和参数行）
|
|
|
|
|
|
memcpy(srcImage.data, srcImageWithPara.data, m_lImageDataSize * sizeof(short)); // 图像数据
|
|
|
|
|
|
if (3312 == m_ArithName)
|
|
|
{
|
|
|
// 参数行数据在图像数据的尾部
|
|
|
memcpy(&g_S3312_Para, &srcImageWithPara.data[m_lImageDataSize * sizeof(short)], m_lArithReslutDataSize); // 参数行数据
|
|
|
Commdef::TServoInfoOutput* tServoInfo = &g_S3312_Para.stTrackResultInfo.tServoAndPosInfo.tServoInfo;
|
|
|
|
|
|
stInputPara.unFreq = 50;
|
|
|
stInputPara.stAirCraftInfo.stAtt.fYaw = 0;
|
|
|
stInputPara.stAirCraftInfo.stAtt.fRoll = 0;
|
|
|
stInputPara.stAirCraftInfo.stAtt.fPitch = 0;
|
|
|
stInputPara.stCameraInfo.unVideoType = GLB_VIDEO_TYPE::GLB_VIDEO_IR_MW;
|
|
|
stInputPara.stCameraInfo.fPixelSize = 25;
|
|
|
stInputPara.stCameraInfo.nFocus = 400;//基本都是小视场
|
|
|
stInputPara.stCameraInfo.fAglReso = 0.0001f * g_S3312_Para.stTrackResultInfo.usResol; // 角分辨率
|
|
|
stInputPara.stServoInfo.fServoAz = -tServoInfo->fServoPtAngle;
|
|
|
stInputPara.stServoInfo.fServoPt = tServoInfo->fServoAzAngle;
|
|
|
|
|
|
stInputPara.stServoInfo.fServoAzSpeed = 0;
|
|
|
stInputPara.stServoInfo.fServoPtSpeed = 0;
|
|
|
}
|
|
|
else if (338 == m_ArithName)
|
|
|
{
|
|
|
EORADERINPUT g_S338_Para = { 0 };
|
|
|
// 参数行的第二行
|
|
|
memcpy(&g_S338_Para, &srcImageWithPara.data[m_lImageDataSize * sizeof(short) + nImageWidth * sizeof(short)], sizeof(EORADERINPUT));//读取录像中算法输入
|
|
|
|
|
|
stInputPara.stCameraInfo.fPixelSize = 25;
|
|
|
stInputPara.stCameraInfo.nFocus = 400;//基本都是小视场
|
|
|
stInputPara.stServoInfo.fServoAz = g_S338_Para.ServoAngel.fOriAngle;
|
|
|
stInputPara.stServoInfo.fServoPt = g_S338_Para.ServoAngel.fPitAngle;
|
|
|
|
|
|
stInputPara.stServoInfo.fServoAzSpeed = g_S338_Para.ServoAngel.fOriAngleSpeed;
|
|
|
stInputPara.stServoInfo.fServoPtSpeed = g_S338_Para.ServoAngel.fPitAngleSpeed;
|
|
|
}
|
|
|
|
|
|
if (6 == stInputPara.unFrmId)
|
|
|
{
|
|
|
initialization << vot.region();
|
|
|
// 下发锁定
|
|
|
SelectCX = initialization.x + initialization.width / 2;
|
|
|
SelectCY = initialization.y + initialization.height / 2;
|
|
|
setLockBoxW = initialization.width;
|
|
|
setLockBoxH = initialization.height;
|
|
|
|
|
|
ARIDLL_OBJINFO obj = { 0 };
|
|
|
obj = ARIDLL_LockTarget(pTracker, img, SelectCX, SelectCY, setLockBoxW, setLockBoxH);
|
|
|
}
|
|
|
stInputPara.unFrmId++;
|
|
|
|
|
|
// 构建图像类型
|
|
|
img.enPixelFormat = GD_PIXEL_FORMAT_E::GD_PIXEL_FORMAT_GRAY_Y16;
|
|
|
img.u32Width = nImageWidth;
|
|
|
img.u32Height = nImageHeight;
|
|
|
img.u32Stride[0] = img.u32Width * 2;
|
|
|
img.u64VirAddr[0] = srcImage.data;
|
|
|
|
|
|
RunProcess(pTracker, img);
|
|
|
|
|
|
auto trackerOut = stOutput.stTrackers[0];
|
|
|
cv::Rect outRect;
|
|
|
outRect.width = (int)trackerOut.nObjW;
|
|
|
outRect.height= (int)trackerOut.nObjH;
|
|
|
outRect.x = (int)trackerOut.nX - outRect.width / 2;
|
|
|
outRect.y = (int)trackerOut.nY - outRect.height / 2;
|
|
|
|
|
|
vot.report(outRect, trackerOut.fConf);
|
|
|
}
|
|
|
return 0;
|
|
|
} |
