VPTProcess.cpp
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#include "VPTProcess.h"
#include <stdlib.h>
#include <cuda_runtime.h>
#include "ErrorInfo.h"
#include "../FFNvDecoder/logger.hpp"
#define THRESHOLD 0.5
#define USE_YOLOV5
// #include "../../model/vptModeTrt/ga_vpt_init_net.h"
// #include "../../model/vptModeTrt/ga_vpt_predict_net.h"
// //#include "../../model/hidemodel_caffe_1108/ga_vpt_init_net_caffe2.h"
// //#include "../../model/hidemodel_caffe_1108/ga_vpt_predict_net_caffe2.h"
//model trt onnx 20210715
#include "../../model/vptModeTrt/ga_vpt_det_yolo_640x640.h" // debug by zsh
#include "../../model/vptModeTrt/ga_trt_yolo_vpt_calibrator.h" // debug by zsh
// // fpn
// #include "vpt_fpn_plugin_factory.h"
// #include "../../model/vptModeTrt/ga_trt_fpn_vpt_calibrator.h"
static long long get_cur_time_ms(){
chrono::time_point<chrono::system_clock, chrono::milliseconds> tpMicro
= chrono::time_point_cast<chrono::milliseconds>(chrono::system_clock::now());
return tpMicro.time_since_epoch().count();
}
VPTProcess::VPTProcess(/* args */)
{
}
VPTProcess::~VPTProcess()
{
}
void VPTProcess::config_fpn_param(ctools_init_params& param, int batch_size) {
// param.model_type_ = MODEL_FPN;
// param.weight_file_ = NULL;
// param.net_file_ = NULL;
// param.data_process_str_ =
// //"CopyData_CPU2GPU_U8;"
// "TypeConvert_U8_F32;"
// "ResizeMaxPad_F32_F32,test_size,720,test_max_size,1280,max_height,736,max_width,1280,"
// "submean_b,103.94,submean_g,116.78,submean_r,123.68,"
// "variance_rev_b,0.017,variance_rev_g,0.017,variance_rev_r,0.017;"
// "NHWC2NCHW_F32"
// ;
// param.need_im_info_ = 1; // true
// if (param.engine_type_ == ENGINE_MCAFFE2)
// {
// /*param.weight_array_ = (unsigned char*)ga_vpt_init_net_caffe2;
// param.weight_array_len_ = ga_vpt_init_net_len_caffe2;
// param.net_array_ = (unsigned char*)ga_vpt_predict_net_caffe2;
// param.net_array_len_ = ga_vpt_predict_net_len_caffe2;*/
// }
// else if (param.engine_type_ == ENGINE_TENSORRT)
// {
// param.weight_array_ = (uint8_t*)ga_vpt_init_net;
// param.weight_array_len_ = ga_vpt_init_net_len;
// param.net_array_ = (uint8_t*)ga_vpt_predict_net;
// param.net_array_len_ = ga_vpt_predict_net_len;
// memset(param.tensorrt_param_str_, 0, sizeof(param.tensorrt_param_str_));
// std::string g_data_mode = "FP32";
// bool g_is_create_calibrator = false;
// sprintf(param.tensorrt_param_str_, "max_batchsize %d,"
// "data_mode %s,"
// "is_create_calibrator %d,"
// "input_names data im_info,"
// "output_names cls_prob bbox_pred_final rois_count_each_img",
// batch_size, g_data_mode.c_str(), g_is_create_calibrator);
// param.tensorrt_calibrator_file_ = NULL;// "trt_fpn_vpt_calibrator";
// param.tensorrt_calibrator_array_len_ = ga_trt_fpn_vpt_calibrator_len;// "trt_fpn_vpt_calibrator";
// param.tensorrt_calibrator_array_ = (unsigned char*)ga_trt_fpn_vpt_calibrator;// "trt_fpn_vpt_calibrator";
// param.tensorrt_plugin_factory_ptr_ = &(tensorrt_plugin_factory);
// }
}
void VPTProcess::config_yolo_param(ctools_init_params& param, int batch_size) {
param.model_type_ = MODEL_YOLOV5;
param.weight_file_ = NULL;
param.net_file_ = NULL;
param.data_process_str_ =
//"CopyData_CPU2GPU_U8;"
"TypeConvert_U8_F32;"
"ResizeMaxMidPad_F32_F32,test_size,640,test_max_size,640,max_height,640,max_width,640,"
"submean_b,0,submean_g,0,submean_r,0,"
"variance_rev_b,0.00392,variance_rev_g,0.00392,variance_rev_r,0.00392;"
"BGR2RGB_F32_F32;"
"NHWC2NCHW_F32"
;
param.need_im_info_ = 0;
if (param.engine_type_ == ENGINE_MCAFFE2)
{
/*param.weight_array_ = (unsigned char*)ga_vpt_init_net_caffe2;
param.weight_array_len_ = ga_vpt_init_net_len_caffe2;
param.net_array_ = (unsigned char*)ga_vpt_predict_net_caffe2;
param.net_array_len_ = ga_vpt_predict_net_len_caffe2;*/
}
else if (param.engine_type_ == ENGINE_TENSORRT)
{
param.net_array_ = (uint8_t*)ga_vpt_det_yolo_640x640;
param.net_array_len_ = ga_vpt_det_yolo_640x640_len; //debug by zsh
memset(param.tensorrt_param_str_, 0, sizeof(param.tensorrt_param_str_));
std::string g_data_mode = "FP32";
bool g_is_create_calibrator = false;
int g_is_onnx_model = 1;
sprintf(param.tensorrt_param_str_, "max_batchsize %d,"
"data_mode %s,"
"is_create_calibrator %d,"
"is_onnx_model %d,"
"input_names images,"
"output_names output",
batch_size, g_data_mode.c_str(), g_is_create_calibrator, g_is_onnx_model);
param.tensorrt_calibrator_array_len_ = ga_trt_yolo_vpt_calibrator_len;
param.tensorrt_calibrator_array_ = (unsigned char*)ga_trt_yolo_vpt_calibrator;
}
}
int VPTProcess::init(int gpuid, int max_batch_size)
{
ctools_init_params param;
param.thres_ = 0.5;
param.log_level_ = 0;
param.device_type_ = DEVICE_GPU;
param.device_id_ = gpuid;
param.engine_type_ = ENGINE_TENSORRT;
param.trt_serialize_file_ = "./serialize_file/VPT";
m_max_batch_size = max_batch_size;
#ifdef USE_YOLOV5
config_yolo_param(param, m_max_batch_size);
#else
config_fpn_param(param, m_max_batch_size);
#endif
int flag = ctools_init(&det_handle, ¶m);
if (SUCCESS != flag) {
LOG_ERROR("VPTProcess init failed!");
}
return flag;
}
void VPTProcess::check_VPT_Result(VPT_Result & vResult) {
int index = 0;
for (int i = 0; i < vResult.objCount; i++) {
if ((vResult.obj[i].right - vResult.obj[i].left) > 10 && (vResult.obj[i].bottom - vResult.obj[i].top) > 10)
{
if (index == i) {
index++;
continue;
}
vResult.obj[index].left = vResult.obj[i].left;
vResult.obj[index].top = vResult.obj[i].top;
vResult.obj[index].right = vResult.obj[i].right;
vResult.obj[index].bottom = vResult.obj[i].bottom;
vResult.obj[index].center_x = vResult.obj[i].center_x;
vResult.obj[index].center_y = vResult.obj[i].center_y;
vResult.obj[index].index = vResult.obj[i].index;
vResult.obj[index].id = vResult.obj[i].id;
vResult.obj[index].num = vResult.obj[i].num;
vResult.obj[index].confidence = vResult.obj[i].confidence;
vResult.obj[index].snap_flag = vResult.obj[i].snap_flag;
index++;
}
}
vResult.objCount = index;
}
int VPTProcess::process(sy_img * batch_img, int batchsize, vector<unsigned long long> vec_frameIndex, vector<VPT_Result>& result, vector<vector<int>>& deleteObjectID, vector<vector<VPT_Result>>& unUsedResult)
{
if(nullptr == det_handle){
return FAILED;
}
long long t1 = get_cur_time_ms();
vector <vector< vector <float>>> detectResult(batchsize);
int real_index = 0;
int cycle_time = batchsize / m_max_batch_size;
cycle_time = (batchsize % m_max_batch_size) == 0 ? cycle_time : (cycle_time + 1) ;
vector<sy_img> vec_img;
for (int i = 0; i < cycle_time; i++) {
vec_img.clear();
int start_index = i * m_max_batch_size;
int end_index = start_index + m_max_batch_size;
if(end_index >= batchsize) {
end_index = batchsize;
}
for (int j = start_index; j < end_index; j++) {
vec_img.push_back(batch_img[j]);
}
ctools_result *detresult;
int res_status = ctools_process(det_handle, vec_img.data(), vec_img.size(), &detresult);
for (size_t b = 0; b < vec_img.size(); b++) {
ctools_result &cur_result = detresult[b];
for (int c = 0; c < cur_result.obj_count_ && c < MAX_OBJ_COUNT; c++)
{
float x1 = cur_result.obj_results_[c].data_[2];
float y1 = cur_result.obj_results_[c].data_[3];
float x2 = cur_result.obj_results_[c].data_[4];
float y2 = cur_result.obj_results_[c].data_[5];
float class_id = cur_result.obj_results_[c].data_[0];
float score = cur_result.obj_results_[c].data_[1];
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[real_index].push_back(obj);
}
}
real_index++;
}
}
for (int i = 0; i < batchsize; i++){
TaskTracker& task_tracker = taskTrackers[i];
if (!task_tracker.tracker.GetState()) {
continue;
}
if (task_tracker.lastFrameIndex <= 0) {
// 第一帧，只做带检测框的跟踪
int objCount = task_tracker.tracker.update(task_tracker.ratioWidth, task_tracker.ratioHeight, true, detectResult[i], result[i].obj, deleteObjectID[i]);
result[i].objCount = objCount;
} else {
int update_times = vec_frameIndex[i] - task_tracker.lastFrameIndex - 1;
if (update_times < 0) {
cout << "FrameIndex error !! lastFrameIndex= " << task_tracker.lastFrameIndex << " cur_frameindex = " << vec_frameIndex[i] << endl;
}
// cout << "lastFrameIndex= " << task_tracker.lastFrameIndex << " cur_frameindex = " << vec_frameIndex[detectIndex] << endl;
// cout << "update_times = " << update_times << endl;
for (int j = 0; j < update_times; j++) { // 无检测框跟踪
//cout << "taskTrackers size: " << task_tracker.size() << " batchsize:" << detectResult.size() << " update_times: "<< update_times << endl;
task_tracker.lastUnUsedResult.objCount = task_tracker.tracker.update(task_tracker.ratioWidth, task_tracker.ratioHeight, false, task_tracker.lastDetectResult, task_tracker.lastUnUsedResult.obj, task_tracker.lastDeleteObjectID);
}
//有检测框输入的跟踪
int objCount = task_tracker.tracker.update(task_tracker.ratioWidth, task_tracker.ratioHeight, true, detectResult[i], result[i].obj, deleteObjectID[i]);
result[i].objCount = objCount;
}
check_VPT_Result(result[i]);
task_tracker.lastDetectResult = detectResult[i];
task_tracker.lastUnUsedResult.objCount = result[i].objCount;
memcpy(task_tracker.lastUnUsedResult.obj, result[i].obj, sizeof(VPT_ObjInfo) * MAX_OBJ_COUNT);
task_tracker.lastDeleteObjectID = deleteObjectID[i];
// 记录帧序号
task_tracker.lastFrameIndex = vec_frameIndex[i];
}
}
void VPTProcess::release() {
if (det_handle) {
ctools_release(&det_handle);
det_handle = NULL;
}
vector<TaskTracker>().swap(taskTrackers);
}
void VPTProcess::AddTaskTracker(const int taskID, const double rWidth, const double rHeight)
{
TaskTracker t;
t.TaskID = taskID;
t.ratioWidth = rWidth;
t.ratioHeight = rHeight;
t.lastFrameIndex = 0;
t.tracker.setYOLOv5(true); // YOLOv5 要设为true, fpn 要设为false
taskTrackers.push_back(t);
}
void VPTProcess::FinishTaskTracker(const int taskID)
{
for (int i = 0; i < taskTrackers.size(); i++)
{
if (taskTrackers[i].TaskID == taskID)
{
taskTrackers.erase(taskTrackers.begin() + i);
break;
}
}
}
void VPTProcess::PauseTaskTracker(const int taskID)
{
for (int i = 0; i < taskTrackers.size(); i++)
{
if (taskTrackers[i].TaskID == taskID)
{
taskTrackers[i].tracker.Pause();
break;
}
}
}
void VPTProcess::RestartTaskTraker(const int taskID)
{
for (int i = 0; i < taskTrackers.size(); i++)
{
if (taskTrackers[i].TaskID == taskID)
{
taskTrackers[i].tracker.ReSet();
break;
}
}
}
void VPTProcess::DrawTracker(const int taskID, cv::Mat *img)
{
for (int i = 0; i < taskTrackers.size(); i++)
{
if (taskTrackers[i].TaskID == taskID)
{
taskTrackers[i].tracker.addTracker(img);
break;
}
}
}