85cc8cb9
 Hu Chunming
原版代码
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#include "face_det_ai_engine.h"
#include <cuda.h>
#include <cuda_runtime.h>
#include "cuda_kernels.h"
#include "mvpt_process_assist.h"
#include "../helpers/logger.hpp"
#include "../helpers/cuda_helper.h"
face_det_ai_engine::~face_det_ai_engine()
{
fd_release(&handle);
clear();
}
int face_det_ai_engine::init_ai_engine(const facedet_ai_engine_param &ai_param/*, person_det_algorthim_cache * cache*/)
{
max_batchsize = ai_param.sdk_param.max_batch_size_detect;
frame_count = 0;
skips = 6;
is_open = true;
task_param_manager_ = task_param_manager::getInstance();
return fd_init(&handle, ai_param.sdk_param);
}
int face_det_ai_engine::ai_engine_process_batch(sy_img *image_data_array, const int &image_size, std::set<std::string> &task_ids,
std::vector<onelevel_det_result> &result, std::vector<std::vector<int>> &deleteObjectID)
{
map<string, map<algo_type, task_param_manager::algo_param_type_t_*>> && algor_param = task_param_manager_->get_task_other_params();
const int total_batchsize = image_size;
if (total_batchsize > 0 /*&& task_batchsize != 0*/)
{
fd_result *fd_result_ = new fd_result[total_batchsize];
for (int i = 0; i < total_batchsize; ++i)
fd_result_[i].info = new fd_info[50];
// int stride = min(total_batchsize, max_batchsize); // min(best_batchsize, max_batchsize));
int stride = max_batchsize;
int steps = (total_batchsize + stride - 1) / stride;
for (int c = 0; c < steps; ++c)
{
int offset = c * max_batchsize;
const int batchsize = (c == steps - 1) ? (total_batchsize - offset) : stride;
LOG_TRACE("[face_detection]: image_size: {} model_batch_size: {}, step: [{}/{}] offset: {} batchsize: {}", image_size, max_batchsize, c, steps, offset, batchsize);
auto flag = fd_detect_batch(handle, image_data_array + offset, SY_FORMAT_BGR888, batchsize, fd_result_ + offset);
}
// 属性检测使用人脸检测的原图，不需要切图
int cur_index = 0;
int img_index = 0;
vector <vector< vector <float>>> detectResult(total_batchsize); // sort
auto task_id_iter = task_ids.cbegin();
for (int c = 0; c < total_batchsize; ++c)
{
task_param_manager::algo_param_type_t_* cur_task_params = algor_param[*task_id_iter++][algorithm_type_t::FACE_SNAPSHOT];
for (int i = 0; i < fd_result_[c].count; ++i)
{
if (!snapshot_legal_inarea(cur_task_params->basic_param->algor_valid_rect,
fd_result_[c].info[i].face_position.left_, fd_result_[c].info[i].face_position.top_,
fd_result_[c].info[i].face_position.left_ + fd_result_[c].info[i].face_position.width_,
fd_result_[c].info[i].face_position.top_ + fd_result_[c].info[i].face_position.height_)
|| fd_result_[c].info[i].face_pos_score < ((algor_config_param_snapshot *)cur_task_params->algor_param)->threshold)
{
continue;
}
vector <float> obj;
obj.push_back(fd_result_[c].info[i].face_position.left_);
obj.push_back(fd_result_[c].info[i].face_position.top_);
obj.push_back(fd_result_[c].info[i].face_position.left_ + fd_result_[c].info[i].face_position.width_); //right
obj.push_back(fd_result_[c].info[i].face_position.top_ + fd_result_[c].info[i].face_position.height_); //bottom
obj.push_back(fd_result_[c].info[i].score);
obj.push_back(1); //统一index值为1
//存入关键点信息
for(int j = 0; j < FACIALFEAPOINTSIZE; ++j)
{
obj.push_back(fd_result_[c].info[i].facial_fea_point[j].x_);
obj.push_back(fd_result_[c].info[i].facial_fea_point[j].y_);
}
//-added by zsh 添加姿态角信息------------------------------
obj.push_back(fd_result_[c].info[i].roll);
obj.push_back(fd_result_[c].info[i].yaw);
obj.push_back(fd_result_[c].info[i].pitch);
// cout << fabs(fd_result_[c].info[i].roll) << " " << fabs(fd_result_[c].info[i].yaw) << " " << fabs(fd_result_[c].info[i].pitch) << endl;
//--------------------------------------------------------
detectResult[c].push_back(obj);
#if 0
if (fd_result_[img_index].count > 1)
{
//选择居中且靠上的人脸作为唯一的结果
float min_dis = numeric_limits<float>::max();
int min_index = 0;
float person_center_x = (float)(cur_persondet_result[c]->obj[i].right - cur_persondet_result[c]->obj[i].left) / 2.0;
float person_center_y = (float)(cur_persondet_result[c]->obj[i].bottom - cur_persondet_result[c]->obj[i].top) / 6.0;
for (int j = 0; j < fd_result_[img_index].count; ++j)
{
float cx = (float)fd_result_[img_index].info[j].face_position.left_ + (float)(fd_result_[img_index].info[j].face_position.width_) / 2.0;
float cy = (float)fd_result_[img_index].info[j].face_position.top_ + (float)(fd_result_[img_index].info[j].face_position.height_) / 2.0;
float dis = (person_center_x - cx) * (person_center_x - cx) + (person_center_y - cy) * (person_center_y - cy);
if (dis < min_dis)
{
min_dis = dis;
min_index = j;
}
}
//姿态角控制
if (fabs(fd_result_[img_index].info[min_index].roll) < pose_thresld[c] && fabs(fd_result_[img_index].info[min_index].yaw) < pose_thresld[c] && fabs(fd_result_[img_index].info[min_index].pitch) < pose_thresld[c])
{
cur_res.count = 1;
cur_res.info = new fd_info[1];
memcpy(&cur_res.info[0], &fd_result_[img_index].info[min_index], sizeof(fd_info));
}
else
{
cur_res.info = new fd_info[1];
cur_res.count = 0;
}
}
else if (fd_result_[img_index].count == 1 && fabs(fd_result_[img_index].info[0].roll) < pose_thresld[c] && fabs(fd_result_[img_index].info[0].yaw) < pose_thresld[c] && fabs(fd_result_[img_index].info[0].pitch) < pose_thresld[c]) //姿态角控制
{
cur_res.count = 1;
cur_res.info = new fd_info[1];
memcpy(&cur_res.info[0], &fd_result_[img_index].info[0], sizeof(fd_info));
}
else
{
cur_res.info = new fd_info[1];
cur_res.count = 0;
}
_fd_result[vec_ids[c]].push_back(cur_res);
for (int j = 0; j < cur_res.count; ++j)
{
++cur_index;
}
#endif
}
}
// added by zsh
#if 0
for (int b = 0; b < total_batchsize; b++)
{
// printf("batch: %d, %d %d %d \n", b, image_data_array[b].c_ , image_data_array[b].h_ , image_data_array[b].w_);
int data_size = image_data_array[b].c_ * image_data_array[b].h_ * image_data_array[b].w_;
unsigned char *imgdata = new unsigned char[data_size];
cudaMemcpy(imgdata, image_data_array[b].data_, sizeof(unsigned char) * data_size, cudaMemcpyDeviceToHost);
cv::Mat big_img = cv::Mat(image_data_array[b].h_, image_data_array[b].w_, CV_8UC3, imgdata);
for (int c = 0; c < detectResult[b].size(); c++)
{
// printf("%d %d %d %d\n", 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::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);
}
std::string file_path = "res/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";
cv::imwrite(img_filename, big_img);
delete[] imgdata;
}
#endif
//跟踪
int real_index = 0;
std::set<std::string>::iterator iter = task_ids.cbegin();
while (iter != task_ids.cend())
{
if (!task_trackers[*iter].tracker.GetState())
continue;
bool isUseDet = true;
vector<int> delete_ids;
const float maxLen = std::sqrt(image_data_array[real_index].w_ * image_data_array[real_index].w_ + image_data_array[real_index].h_ * image_data_array[real_index].h_); //-modified by zsh 220719
// printf("maxLen: %f\n", maxLen);
for (int j = 0; j < task_trackers[*iter].fusion_interval; ++j)
{
if (j == 0)
{
// int objCount = task_trackers[*iter].tracker.update(isUseDet, /*save lk = */true, detectResult[real_index], result[real_index].obj, deleteObjectID[real_index]);
//-modified by zsh 220719
int objCount = task_trackers[*iter].tracker.update_v2(isUseDet, /*save lk = */true, /*center_dist = */true, maxLen, detectResult[real_index], result[real_index].obj, deleteObjectID[real_index]);
result[real_index].obj_count = objCount;
vector<vector<float>>().swap(detectResult[real_index]);
detectResult[real_index].clear();
isUseDet = false;
}
else
{
onelevel_det_result unresult;
// unresult.obj_count = task_trackers[*iter].tracker.update(isUseDet, true, detectResult[real_index], unresult.obj, deleteObjectID[real_index]);
//-modified by zsh 220719
unresult.obj_count = task_trackers[*iter].tracker.update_v2(isUseDet, true, true, maxLen, detectResult[real_index], unresult.obj, deleteObjectID[real_index]);
}
}
++real_index;
++iter;
}
// added by zsh
#if 0
for (int b = 0; b < total_batchsize; b++)
{
int data_size = image_data_array[b].c_ * image_data_array[b].h_ * image_data_array[b].w_;
unsigned char *imgdata = new unsigned char[data_size];
cudaMemcpy(imgdata, image_data_array[b].data_, sizeof(unsigned char) * data_size, cudaMemcpyDeviceToHost);
cv::Mat big_img = cv::Mat(image_data_array[b].h_, image_data_array[b].w_, CV_8UC3, imgdata);
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);
}
std::string file_path = "res/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";
cv::imwrite(img_filename, big_img);
delete[] imgdata;
}
#endif
vector <vector< vector <float>>>().swap(detectResult); // free memory.
if (fd_result_)
{
for (int i = 0; i < total_batchsize; ++i)
{
delete[] fd_result_[i].info;
fd_result_[i].info = nullptr;
}
delete[] fd_result_;
fd_result_ = nullptr;
}
}
return 0;
}
void face_det_ai_engine::clear()
{
for (auto it = _fd_result.begin(); it != _fd_result.end();)
{
for (auto &fd : it->second)
{
delete[] fd.info;
fd.info = nullptr;
}
_fd_result.erase(it++);
}
}
void face_det_ai_engine::operator_tracker(std::string task_id, const int &oper, int m_fusion_interval)
{
//if (get_status())
{
switch (oper)
{
case ADDTASK:
{
LOG_INFO("face: tracker add task {}", task_id.c_str());
task_tracker t;
t.task_id = task_id;
t.fusion_interval = m_fusion_interval;
task_trackers.insert(std::make_pair(task_id, t));
break;
}
case PAUSETASK:
{
auto iter = task_trackers.find(task_id);
if (iter != task_trackers.end())
iter->second.tracker.Pause();
break;
}
case RESTARTTASK:
{
auto iter = task_trackers.find(task_id);
if (iter != task_trackers.end())
iter->second.tracker.ReSet();
break;
}
case FINISHTASK:
{
LOG_INFO("face: tracker finish task {}", task_id.c_str());
auto iter = task_trackers.find(task_id);
if (iter != task_trackers.end())
{
task_trackers.erase(task_id);
}
break;
}
default:
break;
}
}
}
void face_det_ai_engine::finish_task(std::string task_id)
{
auto iter = id_frame_count.find(task_id);
if (iter != id_frame_count.end())
{
id_frame_count.erase(task_id);
}
frame_count = 0;
}
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