//
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// Created by Scheaven on 2019/11/19.
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//
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#include "detecter_manager.h"
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#include <thread>
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#include <unistd.h>
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#include <cstdlib>
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DetecterManager* DetecterManager::instance = NULL;
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DetecterManager* DetecterManager::getInstance()
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{
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if(instance==NULL)
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{
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instance = new DetecterManager();
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}
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return instance;
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}
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DetecterManager::DetecterManager()
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{
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Config config;
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config.net_type = YOLOV4;
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config.file_model_cfg = m_staticStruct::model_cfg;
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config.file_model_weights = m_staticStruct::model_wts;
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config.calibration_image_list_file_txt = "../configs/calibration_images.txt";
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config.inference_precison = INT8;
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config.detect_thresh = 0.5;
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//if(m_staticStruct::type==2)
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// config.net_type = SMALL;
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//else
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// config.net_type = COMMON;
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this->detector = std::shared_ptr<Detector>(new Detector());
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this->detector->init(config);
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std::cout << "loading detector model......" << std::endl;
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}
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DetecterManager::~DetecterManager()
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{
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}
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void DetecterManager::release()
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{
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// Detector::getInstance()->release();
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delete DetecterManager::instance;
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DetecterManager::instance = NULL;
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}
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void DetecterManager::detecter_main(cv::Mat &mat_image, DETECTIONS& detection)
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{
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std::vector<BatchResult> batch_res;
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std::vector<cv::Mat> batch_img;
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batch_img.push_back(mat_image.clone());
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this->detector->detect(batch_img, batch_res);
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encoder_features(batch_res, detection);
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// show_result(result_vec);
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// draw_boxes(mat_image, result_vec);
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}
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void DetecterManager::encoder_features(std::vector<BatchResult> boxes, DETECTIONS &detection)
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{
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std::vector<float> confidences;
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std::vector<int> human_index;
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int result_index=0;
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for (const auto &result_box:boxes[0])
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{
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// #ifdef S_DEBUG
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// printf("--%d-%d-%d-%d-%d---result_box-----\n", result_box.obj_id, result_box.x, result_box.y, result_box.w, result_box.h);
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// #endif
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if(result_box.id == 1)
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{
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// cv::Rect box = cv::Rect(result_box.x,result_box.y,result_box.w,result_box.h);
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// get_detections(DETECTBOX(box.x, box.y,box.width, box.height), confidences[idx],d);
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DETECTION_ROW tmpRow;
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tmpRow.tlwh = DETECTBOX(result_box.rect.x,result_box.rect.y,result_box.rect.width,result_box.rect.height); //DETECTBOX(x, y, w, h);
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tmpRow.confidence = result_box.prob*100;
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tmpRow.obj_id = 0;
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tmpRow.is_hat = true;
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tmpRow.is_mask = true;
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tmpRow.is_smoke = true;
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tmpRow.hatScore = 0;
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tmpRow.maskScore = 0;
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tmpRow.smokeScore = 0;
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// tmpRow.img_time = this->img_time;
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tmpRow.isFall = false;
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tmpRow.fallScore = 0;
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tmpRow.runScore = 0;
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tmpRow.isRun = false;
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// tmpRow.human_face = nullptr;
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int sub_box_index=0;
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human_index.push_back(result_index);
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detection.push_back(tmpRow);
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}
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result_index++;
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}
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}
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// bool DetecterManager::sort_score(bbox_t box1, bbox_t box2)
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// {
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// return (box1.prob>box2.prob);
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// }
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// float DetecterManager::box_iou(bbox_t box1, bbox_t box2)
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// {
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// int x1 = std::max(box1.x, box2.x);
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// int y1 = std::max(box1.y, box2.y);
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// int x2 = std::min((box1.x+box1.w),(box2.x+box2.w));
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// int y2 = std::min((box1.y+box1.h),(box2.y+box2.h));
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// float over_area = (x2-x1)*(y2-y1);
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// // printf("over_ares---%f ----%d----%d\n", over_area, box1.w*box1.h, box2.w*box2.h);
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// float iou = over_area/((box1.w*box1.h<box2.w*box2.h)?box1.w*box1.h:box2.w*box2.h);
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// return iou;
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// }
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void DetecterManager::set_imgTime(long img_time)
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{
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this->img_time = img_time;
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}
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