VPTProcess.cpp_debug
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#include "VPTProcess.h"
#include "../common/logger.hpp"
#include "../ai_platform/task_param_manager.h"
#include <stdlib.h>
#include <time.h>
#include <fstream>
#include "vpt.h"
#include "../ai_platform/macro_definition.h"
#include "../ai_platform/det_obj_header.h"
#include "opencv2/opencv.hpp"
#include "../util/vpc_util.h"
VPTProcess::VPTProcess(){
m_max_batchsize = 16;
}
VPTProcess::~VPTProcess(){
release();
}
/* 算法初始化 */
int VPTProcess::init(VPTProcess_PARAM vparam){
string model_path = vparam.model_dir + "/models/vpt230323_310p.om" ;
LOG_INFO("vpt 版本：{} 模型路径：{}", vpt_get_version(), model_path);
vpt_param param;
char modelNames[100];
strcpy(modelNames, model_path.c_str());
param.modelNames = modelNames;
param.threshold = vparam.threshold;
param.devId = vparam.gpuid;
param.isTrk = false;
m_devId = param.devId;
ACL_CALL(aclrtCreateContext(&m_algorthim_ctx, m_devId), ACL_ERROR_NONE, -1);
int ret = vpt_init(&m_det_handle, param);
if(ret != 0){
LOG_DEBUG("vpt init error.");
return -1;
}
jpegUtil.jpeg_init(m_devId);
return 0;
}
/* 算法计算 */
// int VPTProcess::process_gpu(sy_img * batch_img, vector<string>& tasklist,
// vector<onelevel_det_result>& result, vector<vector<int>>& deleteObjectID, vector<vector<onelevel_det_result>>& unUsedResult)
int VPTProcess::process_gpu(sy_img * batch_img, vector<DeviceMemory*> vec_vptMem, vector<string>& tasklist,
vector<onelevel_det_result>& result, vector<vector<int>>& deleteObjectID, vector<vector<onelevel_det_result>>& unUsedResult)
{
int batchsize = tasklist.size();
if (result.empty())
result.resize(batchsize);
/* 结果结构体初始化 */
vpt_result *vpt_det_result = new vpt_result[batchsize];
for (int b = 0; b < batchsize; b++){
vpt_det_result[b].obj_count_ = 0;
vpt_det_result[b].obj_results_ = new vpt_obj_result[MAX_DET_COUNT];
}
do{
/* 路数太多时 按照最大batchsize数 拆批次运行 */
int cur_batch_size = m_max_batchsize;
int cycleTimes = batchsize / cur_batch_size + (batchsize % cur_batch_size == 0 ? 0 : 1);
for (int c = 0; c < cycleTimes; c++){
int real_batchsize = c == cycleTimes - 1 ? (batchsize - cur_batch_size*c) : cur_batch_size;
int startbatch = c*cur_batch_size;
vpt_result *real_res = vpt_det_result + startbatch;
int ret = aclrtSetCurrentContext(m_algorthim_ctx);
if(ACL_ERROR_NONE != ret){
break;
}
ret = vpt_batch(m_det_handle, batch_img + startbatch, real_batchsize, real_res);
if(ret != 0){
break;
}
}
vector <vector< vector <float>>> detectResult(batchsize); // sort
/* 将检测的结果放进数组 转换为跟踪的输入需要（若为人脸 则检测结果可能跟多，比如需要带上ldmk点） */
// filter by threshold.
for (int b = 0; b < batchsize; b++)
{
vpt_result cur_result = vpt_det_result[b];
for (int c = 0; c < cur_result.obj_count_ && c < MAX_OBJ_COUNT; c++)
{
float x1 = vpt_det_result[b].obj_results_[c].obj_rect.left_;
float y1 = vpt_det_result[b].obj_results_[c].obj_rect.top_;
float x2 = vpt_det_result[b].obj_results_[c].obj_rect.left_ + vpt_det_result[b].obj_results_[c].obj_rect.width_;
float y2 = vpt_det_result[b].obj_results_[c].obj_rect.top_ + vpt_det_result[b].obj_results_[c].obj_rect.height_;
float class_id = vpt_det_result[b].obj_results_[c].obj_index;
float score = vpt_det_result[b].obj_results_[c].obj_score;
if (score >= THRESHOLD)
{
vector <float> obj;
obj.push_back(x1);
obj.push_back(y1);
obj.push_back(x2);
obj.push_back(y2);
obj.push_back(score);
obj.push_back(class_id);
detectResult[b].push_back(obj);
}
}
}
#if 0
for (int b = 0; b < batchsize; b++)
{
std::string file_path = "res/vpt_test/";
auto time_now = std::chrono::system_clock::now();
std::string cur_timestamp_us = std::to_string(std::chrono::duration_cast<std::chrono::microseconds>(time_now.time_since_epoch()).count());
std::string img_filename = file_path + cur_timestamp_us + "_" + std::to_string(detectResult[b].size()) + ".jpg";
vpc_img_info src_img_info = VPCUtil::vpc_devMem2vpcImg(vec_vptMem[b]);
bool bSaved = jpegUtil.jpeg_encode(src_img_info.pic_desc, img_filename);
cv::Mat big_img = cv::imread(img_filename);
for (int c = 0; c < detectResult[b].size(); c++) {
cv::rectangle(big_img, cv::Rect(detectResult[b][c][0], detectResult[b][c][1], detectResult[b][c][2] - detectResult[b][c][0],
detectResult[b][c][3] - detectResult[b][c][1]), cv::Scalar(158, 52, 254), 3, 1, 0);
}
cv::imwrite(img_filename, big_img);
VPCUtil::vpc_img_release(src_img_info);
}
#endif
bool isUseDet = true;
for (size_t detectIndex = 0; detectIndex < batchsize; detectIndex++) {
string task_id = tasklist[detectIndex];
if (! taskTrackers[task_id].tracker.GetState())
continue;
Sort &cur_sort = taskTrackers[task_id].tracker;
isUseDet = true;
const float maxLen = std::sqrt(batch_img[detectIndex].w_ * batch_img[detectIndex].w_ + batch_img[detectIndex].h_ * batch_img[detectIndex].h_); //-modified by zsh 220719
/* FusionInterval是跳帧参数，以十类人车物为例，一般跳5帧，所以第一帧检测，后续四帧纯跟踪 */
for (int j = 0; j < taskTrackers[task_id].tracker.FusionInterval; j++)
{
/* 跟踪：第一帧 带检测框信息的跟踪，取结果返回 */
if (j == 0)
{
// int objCount = cur_sort.update_v2(isUseDet, /*save lk = */false, /*center_dist = */true, maxLen, detectResult[detectIndex], result[detectIndex].obj, deleteObjectID[detectIndex]);
int objCount = cur_sort.update_v3(isUseDet, /*save lk = */false, /*center_dist = */true, maxLen, detectResult[detectIndex], result[detectIndex].obj, deleteObjectID[detectIndex]);
result[detectIndex].obj_count = objCount;
result[detectIndex].task_id = task_id;
// vector<vector<float>>().swap(detectResult[detectIndex]);
// detectResult[detectIndex].clear();
isUseDet = false;
} else /* 跟踪：后四帧 纯粹跟踪 纯跟踪结果不返回 */
{
onelevel_det_result un_result;
//un_result.obj_count = cur_sort.update(isUseDet, false, detectResult[detectIndex], un_result.obj, deleteObjectID[detectIndex]);
// un_result.obj_count = cur_sort.update_v2(isUseDet, false, true, maxLen, detectResult[detectIndex], un_result.obj, deleteObjectID[detectIndex]);
un_result.obj_count = cur_sort.update_v3(isUseDet, false, true, maxLen, detectResult[detectIndex], un_result.obj, deleteObjectID[detectIndex]);
}
}
}
#if 1
for (int b = 0; b < batchsize; b++)
{
std::string file_path = "res/vpt_track/";
auto time_now = std::chrono::system_clock::now();
std::string cur_timestamp_us = std::to_string(std::chrono::duration_cast<std::chrono::microseconds>(time_now.time_since_epoch()).count());
std::string img_filename = file_path + cur_timestamp_us + "_" + std::to_string(result[b].obj_count) + ".jpg";
vpc_img_info src_img_info = VPCUtil::vpc_devMem2vpcImg(vec_vptMem[b]);
bool flag = false;
for (int c = 0; c < result[b].obj_count; c++) {
if (result[b].obj[c].id > 7700 && result[b].obj[c].id < 8000) flag = true;
}
if (flag) {
bool bSaved = jpegUtil.jpeg_encode(src_img_info.pic_desc, img_filename);
cv::Mat big_img = cv::imread(img_filename);
for (int c = 0; c < result[b].obj_count; c++) {
cv::putText(big_img, std::to_string(result[b].obj[c].id), cv::Point(result[b].obj[c].left, result[b].obj[c].top-5), cv::FONT_HERSHEY_SIMPLEX, 0.75, cv::Scalar(255,0,0),2,8);
cv::rectangle(big_img, cv::Rect(result[b].obj[c].left, result[b].obj[c].top, result[b].obj[c].right - result[b].obj[c].left,
result[b].obj[c].bottom - result[b].obj[c].top), cv::Scalar(158, 52, 254), 3, 1, 0);
}
for (int c = 0; c < detectResult[b].size(); c++) {
cv::rectangle(big_img, cv::Rect(detectResult[b][c][0], detectResult[b][c][1], detectResult[b][c][2] - detectResult[b][c][0],
detectResult[b][c][3] - detectResult[b][c][1]), cv::Scalar(0, 0, 255), 3, 1, 0);
}
cv::imwrite(img_filename, big_img);
}
VPCUtil::vpc_img_release(src_img_info);
}
#endif
vector <vector< vector <float>>>().swap(detectResult); // free memory.
} while (0);
if(vpt_det_result){
for (int b = 0; b < batchsize; b++){
delete[] vpt_det_result[b].obj_results_;
}
delete[] vpt_det_result;
}
return 0;
}
/* 算法句柄 资源释放 */
void VPTProcess::release(){
if (m_det_handle){
vpt_release(&m_det_handle);
m_det_handle = NULL;
}
jpegUtil.jpeg_release();
if(m_algorthim_ctx){
aclrtDestroyContext(m_algorthim_ctx);
}
}
// 221117byzsh
void VPTProcess::addTaskTracker(const string taskID, double rWidth, double rHeight, int skip_frame)
{
TaskTracker t;
t.TaskID = taskID;
t.ratioWidth = rWidth;
t.ratioHeight = rHeight;
t.tracker.FusionInterval = skip_frame;
taskTrackers[taskID] = t;
}
/* 任务结束跟踪器 */
bool VPTProcess::finishTaskTracker(const string taskID)
{
taskTrackers.erase(taskID);
return true;
}