Hu Chunming / vpt_proj

#include <vector>
#include <iostream>
#include <fstream>
#include <time.h>
#ifdef _MSC_VER
#include "../VPT/VPT.h"
#include <windows.h>
#include <cv.h>
#include <highgui.h>
#include <opencv2/opencv.hpp>
#else
#include "VPT.h"
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#endif
//#include "../VPT/header.h"

#ifndef _MSC_VER
#include<time.h>
#include <sys/time.h>
#include <unistd.h>
#define Sleep(a) usleep((a)*1000)
#define MACRO_COUNT_TIME_START(name)  struct timeval macro_tv_start_##name;\
		struct timeval macro_tv_end_##name;\
	gettimeofday(&macro_tv_start_##name,NULL);
#define MACRO_COUNT_TIME_END(name,___total_count___) gettimeofday(&macro_tv_end_##name,NULL);\
		printf("%s time cost: %.2f ms \n", #name, ( (double)(macro_tv_end_##name.tv_sec-macro_tv_start_##name.tv_sec)*1000000+(double)(macro_tv_end_##name.tv_usec-macro_tv_start_##name.tv_usec)   )/1000/___total_count___);
#endif

using namespace cv;
using namespace std;

//检测种类
const int detectType = 9;

//行人 自行车 摩托车 三轮车 小型车 大车 卡车 拖拉机 中巴
string type[detectType] = { "person", "bike", "motor", "tricycle", "car", "bigbus", "lorry", "tractor", "midibus" };
static int color[detectType][3] = { { 41, 244, 222 }, { 255, 128, 0 }, { 100, 13, 244 }, { 255, 215, 0 }, { 18, 220, 87 }, { 0, 128, 0 }, \
{0, 128, 255}, { 255, 0, 0 }, { 91, 46, 0 } };


//返回快照结果回调函数
void SnapshotInfoCallback(VIDEO_OBJECT_SNAPSHOT *videoObjectSnapshot)
{
	cout << videoObjectSnapshot->video_id << " " << videoObjectSnapshot->objectID << " " << videoObjectSnapshot->left << " " << videoObjectSnapshot->right << " " << videoObjectSnapshot->top << " " << videoObjectSnapshot->bottom
		<< " " << videoObjectSnapshot->firstPicPath << " " << videoObjectSnapshot->secondPicPath << " " << videoObjectSnapshot->taskFrameCount << " " << videoObjectSnapshot->objectIndex << endl;
}


//显示变量
Mat imgResized;
bool img_show = false;
bool show = true;

#ifdef _MSC_VER
//显示线程
DWORD WINAPI DiaplayThread(LPVOID param)
{
	LARGE_INTEGER nFreq, nSaveBeginTime, nSaveEndTime;
	QueryPerformanceFrequency(&nFreq);

	while (show)
	{
		if (img_show)
		{
			cv::imshow("RESULT", imgResized);
			cv::waitKey(1);
			img_show = false;
		}
		Sleep(1);
	}
	return 0;
}
#endif


int main(int argc, char** argv)
{
	//字体初始化
	CvFont font;
	cvInitFont(&font, CV_FONT_HERSHEY_COMPLEX, 1.0, 1.0, 0, 1, 3);
	int fontFace = CV_FONT_HERSHEY_COMPLEX;
	double fontScale = 1;
	int thickness = 2;
	int frameCount = 0;
	const int maxResultCount = 100;

#ifdef _MSC_VER
	LARGE_INTEGER nFreq, nBeginTime, nEndTime;
	QueryPerformanceFrequency(&nFreq);
#endif
	//初始化
	//快照保存参数设置
	SNAPSHOT_PARAMETER ssparam;
	ssparam.selectFromMinbox = true;
	ssparam.selectFromMindistance = true;

	//1.设置最小检测框，各种类目标小于最小检测框大小时不进行快照的保存
	MRECT m_boxsize[DETECTTYPE] = { MRECT(20, 20), MRECT(50, 80), MRECT(50, 80), MRECT(60, 80), MRECT(80, 80), MRECT(90, 90), MRECT(100, 100), MRECT(100, 100), MRECT(100, 100) };  //行人 自行车 摩托车 三轮车 小型车 大车 卡车 拖拉机 中巴
																																													//2.设置目标距离画面边框的最小距离，当目标位置与画面边框小于最小距离时不再更新快照
	int m_distance[EDGES] = { 20, 30, 20, 30 };   //left, top, right, bottom

	memcpy(ssparam.minBoxsize, m_boxsize, sizeof(MRECT)* DETECTTYPE);
	memcpy(ssparam.minDistance, m_distance, sizeof(int)* EDGES);

	void * tools = NULL;
	VPT_PARAM vparam;
	vparam.gpuid = 2;//atoi(argv[2]);// 0;
	vparam.thres = 0.5;
	vparam.maxResultCount = maxResultCount;        //限制算法内部输出的最大前景个数
	vparam.SnaoshotParameter = &ssparam;
  	vparam.serialize_file = "./serialize_file/";   //指定缓存文件生产目录
#ifdef _MSC_VER
	int res = VPT_Init(&tools, vparam, "G:/TestRes", SnapshotInfoCallback);
#else
	int res = VPT_Init(&tools, vparam, "./", SnapshotInfoCallback);
#endif
	if (res != 0)
	{
		cout << "VPT Init Failed!" << endl;
		system("pause");
		return 0;
	}

#if 0
	//其他变量
	Mat img;
	VideoCapture cap;
#ifdef _MSC_VER
	cap.open(argv[1]);
#else
	cap.open("qst.avi");
	//cap.open(argv[1]);
#endif
	cap.read(img);
	VideoWriter writer("result.avi", CV_FOURCC('D', 'I', 'V', 'X'), 25.0, Size(img.cols, img.rows));
	
	
	//结果变量
	VPT_Result result;
	result.obj = new VPT_ObjInfo[maxResultCount];   //设置外部接收结果的最大前景个数

#ifdef _MSC_VER
													//创建显示线程
	DWORD dwThreadID = 0;
	HANDLE handle_display = CreateThread(NULL, 0, DiaplayThread, 0, 0, &dwThreadID);
#endif

	int start = 0;
	cap.set(CV_CAP_PROP_POS_FRAMES, start);

	double totalTime = 0.0;
	//检测

	ofstream file("res.txt");

	while (cap.read(img) && frameCount < 80)
	{
		start++;
		cout << "---------------- " << frameCount << " -----------------" << endl;

#ifdef _MSC_VER
		QueryPerformanceCounter(&nBeginTime);
#else
		MACRO_COUNT_TIME_START(vpt_process);
#endif
		VPT_Process(tools, img.data, img.cols, img.rows, img.channels(), frameCount, &result, true);

#ifdef _MSC_VER
		QueryPerformanceCounter(&nEndTime);
		totalTime += (double)(nEndTime.QuadPart - nBeginTime.QuadPart) * 1000 / (double)nFreq.QuadPart;
		printf("Total Time: %.2fms  \n", (double)(nEndTime.QuadPart - nBeginTime.QuadPart) * 1000 / (double)nFreq.QuadPart);
#else
		MACRO_COUNT_TIME_END(vpt_process, 1);
#endif
		for (int c = 0; c < result.objCount; c++)
		{
			char str_i[100];

			sprintf(str_i, "%d_%.2f", result.obj[c].id, result.obj[c].confidence);
			int colorIndex = result.obj[c].index;


			file << start << " " << result.obj[c].id << " " << result.obj[c].index << " " << result.obj[c].left << " " <<
				result.obj[c].top << " " << result.obj[c].right << " " << result.obj[c].bottom << endl;

			rectangle(img, cvPoint(result.obj[c].left - 5, result.obj[c].top - 15), cvPoint(result.obj[c].right + 5, result.obj[c].bottom + 10), cv::Scalar(color[colorIndex][0], color[colorIndex][1], color[colorIndex][2]), 3, 1);
			cv::putText(img, str_i, cv::Point(result.obj[c].left, result.obj[c].top), fontFace, fontScale, cv::Scalar(color[colorIndex][0], color[colorIndex][1], color[colorIndex][2]), thickness, 8);
		}

		cv::resize(img, imgResized, cv::Size(1280, 720));
		writer << img;
		img_show = true;
		frameCount++;
	}
	cout << "AVG TIME: " << totalTime / 5000 << endl;

	//释放
	show = false;
	delete[] result.obj; 
#else
	
	int batchsize = 5;
	double totalTime = 0.0;
	string videos[10] = { "qst.avi", "qst.avi", "qst.avi", "qst.avi", "qst.avi", "qst.avi", "qst.avi", "qst.avi", "qst.avi" ,"qst.avi"};
	//其他变量
	Mat img[batchsize];
	VideoCapture cap[batchsize];
	VideoWriter writer[batchsize];
	ofstream file("res.txt");
	for (int b = 0; b < batchsize; b++)
	{
		cap[b].open(videos[b]);
		cap[b].read(img[b]);
		std::string save_path = "result_" + to_string(b) + ".avi"; 
		writer[b].open(save_path, CV_FOURCC('D', 'I', 'V', 'X'), 25.0, Size(img[b].cols, img[b].rows));
	}
	

	//结果变量
	VPT_Result *batch_result = new VPT_Result[batchsize];
	for (int b = 0; b < batchsize; b++)
	{
		batch_result[b].objCount = 0;
		batch_result[b].obj = new VPT_ObjInfo[maxResultCount]; //设置外部接收结果的最大前景个数
	}

	int start = 0;
	int start_ = 0;
	for (int b = 0; b < batchsize; b++)
	{
		cap[b].set(CV_CAP_PROP_POS_FRAMES, start_);
		start_ += 80;
	}

	while (frameCount < 80) {
		cout << "---------------- " << frameCount << " -----------------" << endl;
		xjs_batch_img *batch_img = new xjs_batch_img[batchsize];
		start++;
		for (int b = 0; b < batchsize; b++)
		{
			if(cap[b].read(img[b])) {
				std::string video_key = "task_" + to_string(b);
				// std:cout << "video_key:" << video_key << std::endl;
				batch_img[b].set_data(img[b].cols, img[b].rows, img[b].channels(), img[b].data, video_key.c_str(), frameCount);
			}	
		}
#ifdef _MSC_VER
		QueryPerformanceCounter(&nBeginTime);
#else
		MACRO_COUNT_TIME_START(VPT_Process_batch);
#endif
		VPT_Process_batch(tools, batch_img, batchsize, &batch_result, false);
#ifdef _MSC_VER
		QueryPerformanceCounter(&nEndTime);
		totalTime += (double)(nEndTime.QuadPart - nBeginTime.QuadPart) * 1000 / (double)nFreq.QuadPart;
		printf("Total Time: %.2fms  \n", (double)(nEndTime.QuadPart - nBeginTime.QuadPart) * 1000 / (double)nFreq.QuadPart);
#else
		MACRO_COUNT_TIME_END(VPT_Process_batch, 1);
#endif
		for (int b = 0; b < batchsize; b++) {
			for (int c = 0; c < batch_result[b].objCount; c++)
			{
				char str_i[100];
				sprintf(str_i, "%d_%.2f", batch_result[b].obj[c].id, batch_result[b].obj[c].confidence);
				int colorIndex = batch_result[b].obj[c].index;

				file << start << " " << batch_img[b].video_key_ << " " << batch_result[b].obj[c].id << " " << batch_result[b].obj[c].index << " " << batch_result[b].obj[c].left << " " <<
					batch_result[b].obj[c].top << " " << batch_result[b].obj[c].right << " " << batch_result[b].obj[c].bottom << endl;

				rectangle(img[b], cvPoint(batch_result[b].obj[c].left - 5, batch_result[b].obj[c].top - 15), cvPoint(batch_result[b].obj[c].right + 5, batch_result[b].obj[c].bottom + 10), cv::Scalar(color[colorIndex][0], color[colorIndex][1], color[colorIndex][2]), 3, 1);
				cv::putText(img[b], str_i, cv::Point(batch_result[b].obj[c].left, batch_result[b].obj[c].top), fontFace, fontScale, cv::Scalar(color[colorIndex][0], color[colorIndex][1], color[colorIndex][2]), thickness, 8);
			}
			cv::resize(img[b], imgResized, cv::Size(1280, 720));
			writer[b] << img[b];

		}
		
		img_show = true;
		frameCount++;
		if (batch_img != nullptr) {
			delete[] batch_img;
			batch_img = nullptr;
		}

	}

	cout << "AVG TIME: " << totalTime / 5000 << endl;

	//释放
	show = false;
	for (int b = 0; b < batchsize; b++)
	{
		delete[] batch_result[b].obj; 
		cap[b].release();
		writer[b].release();
	}
	delete[] batch_result; 
#endif	

	VPT_Release(&tools);

	return 0;
}