Hu Chunming / vpt_ascend_arm

Commit fa8183035cd924444e5c5fcfba9f11f3e6b4cb7e

Authored by Zhao Shuaihua
1 parent b5aaf53a

增加闯红灯功能(特定场景);优化货车载人效果(检测框行人及非机动车过滤)

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Showing 17 changed files with 995 additions and 36 deletions
bin/libSYTSLSystemInfoNativeJNI.so
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bin/libtraffic_light_vdec.so 0 → 100755
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bin/models/village/trlight_det_310p.om 0 → 100644
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src/Makefile
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... ... @@ -38,7 +38,7 @@ lib=-lacl_dvpp -lascendcl -lacl_dvpp_mpi -lruntime -lascendalog -lc_sec -lmsprof
38 38 -lplatform -lgraph_base -lqos_manager
39 39  
40 40 LIBS= -L $(SPDLOG_ROOT)/lib -l:libspdlog.a \
41   - -L $(DEPEND_DIR) -lvpt_det_vdec -lsycheck -lface_det_vdec -lhs_tri_process -lhs_truck_process -lphone_motor_det -lhcp_vdec -lmotor_rainshed_vdec -lhs_motor_process\
  41 + -L $(DEPEND_DIR) -lvpt_det_vdec -lsycheck -lface_det_vdec -lhs_tri_process -lhs_truck_process -lphone_motor_det -lhcp_vdec -lmotor_rainshed_vdec -ltraffic_light_vdec -lhs_motor_process\
42 42 -L $(OPENCV_ROOT)/lib -lopencv_world\
43 43 -L $(JSON_ROOT)/lib -ljsoncpp \
44 44 -L $(FFMPEG_ROOT)/lib -lavformat -lavcodec -lswscale -lavutil -lavfilter -lswresample -lavdevice \
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src/ai_engine_module/ai_engine_module.h 0 → 100644
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  1 +#pragma once
  2 +
  3 +#include "./VPTProcess.h"
  4 +#include "./face_det_ai_engine.h"
  5 +#include "./pedestrian_vehicle_retrograde.h"
  6 +#include "./pedestrian_vehicle_trespass.h"
  7 +#include "./tricycle_manned_process.h"
  8 +#include "./truck_manned_process.h"
  9 +#include "./motocycle_hs_process.h"
  10 +#include "./motocycle_refit_phone_process.h"
  11 +#include "./motocycle_phone_process.h"
  12 +#include "./motocycle_refit_process.h"
  13 +#include "./traffic_light_process.h"
0 14 \ No newline at end of file
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src/ai_engine_module/traffic_light_det.h 0 → 100644
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  1 +/*******************************************************************************************
  2 +* Version: triffic_light_det_x64_v0.0.1
  3 +* CopyRight: 中科视语（北京）科技有限公司
  4 +* UpdateDate: 20230922
  5 +* Content：头肩检测_货车
  6 +********************************************************************************************/
  7 +#ifndef TRAFFIC_LIGHT_H_
  8 +#define TRAFFIC_LIGHT_H_
  9 +
  10 +#ifdef _MSC_VER
  11 +#ifdef TRAFFIC_LIGHT_EXPORTS
  12 +#define TRAFFIC_LIGHT_API __declspec(dllexport)
  13 +#else
  14 +#define TRAFFIC_LIGHT_API __declspec(dllimport)
  15 +#endif
  16 +#else
  17 +#define TRAFFIC_LIGHT_API __attribute__ ((visibility ("default")))
  18 +#endif
  19 +
  20 +#include "sy_common.h"
  21 +
  22 +#define MAX_OBJ_COUNT 1000
  23 +
  24 +#ifdef __cplusplus
  25 +extern "C"
  26 +{
  27 +#endif
  28 +
  29 + typedef struct traffic_light_info //结果结构体
  30 + {
  31 + int left;
  32 + int top;
  33 + int right;
  34 + int bottom;
  35 + double confidence; // 置信度
  36 + int index; // 类别索引
  37 + }traffic_light_info;
  38 +
  39 + typedef struct traffic_light_result
  40 + {
  41 + traffic_light_info objinfo[MAX_OBJ_COUNT];
  42 + int objcount;
  43 + };
  44 +
  45 + typedef struct traffic_light_param
  46 + {
  47 + //int mode; //运行模式 GPU_MODE 或者 CPU_MODE
  48 + int devId; //运行卡号 GPU模式下有效
  49 + char* modelNames;
  50 + float thresld; //检测阈值 默认为0.3
  51 +
  52 + //int engine; //指定运行引擎(ENGINE_MCAFFE2 / ENGINE_TENSORRT)
  53 + //int max_batch; //ָ指定trt最大batch数
  54 + //char* trt_serialize_file;
  55 + //traffic_light_param() :mode(DEVICE_GPU), gpuid(0), thresld(0.4), engine(ENGINE_MCAFFE2), max_batch(10){};
  56 + }traffic_light_param;
  57 +
  58 + /*************************************************************************
  59 + * FUNCTION: hst_init
  60 + * PURPOSE: 初始化
  61 + * PARAM:
  62 + [in] handle -处理句柄
  63 + [in] param -初始化参数
  64 + * RETURN: handle
  65 + * NOTES:成功(0)或者错误代码(<0)
  66 + *************************************************************************/
  67 + TRAFFIC_LIGHT_API int traffic_light_init(void **handle, traffic_light_param param);
  68 + TRAFFIC_LIGHT_API int traffic_light_process_batch(void * handle, sy_img *image_data_array, int batchsize, traffic_light_result *result);
  69 +
  70 + /*************************************************************************
  71 + * FUNCTION: hst_release
  72 + * PURPOSE: 资源释放
  73 + * PARAM:
  74 + [in] handle - 处理句柄
  75 + * RETURN: NULL
  76 + * NOTES:
  77 + *************************************************************************/
  78 + TRAFFIC_LIGHT_API void traffic_light_release(void **handle);
  79 +
  80 +
  81 + /*************************************************************************
  82 + * FUNCTION: hst_process_gpu
  83 + * PURPOSE:
  84 + * PARAM:
  85 + [in] handle - 处理句柄
  86 + [in] rgb - 图片数据（3通道BGR数据 cv::Mat格式）
  87 + [in] width - 图片宽度
  88 + [in] height - 图片高度
  89 + [in] result - 搜索结果，在外部申请足够内存
  90 + * RETURN: -1：图像错误； 其他：检测到的个数
  91 + * NOTES:
  92 + *************************************************************************/
  93 + TRAFFIC_LIGHT_API int traffic_light_process(void * handle, sy_img image, traffic_light_result *result);
  94 +
  95 + /*************************************************************************
  96 + * FUNCTION: hst_getversion
  97 + * PURPOSE: 释放
  98 + * PARAM: NULL
  99 + * RETURN: 版本号
  100 + * NOTES:
  101 + *************************************************************************/
  102 + TRAFFIC_LIGHT_API const char * traffic_light_getversion();
  103 +
  104 +#ifdef __cplusplus
  105 +};
  106 +#endif
  107 +
  108 +#endif
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src/ai_engine_module/traffic_light_process.cpp 0 → 100644
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  1 +#include <algorithm>
  2 +#include "./traffic_light_process.h"
  3 +#include <cmath>
  4 +#include "../decoder/interface/DeviceMemory.hpp"
  5 +#include "../common/logger.hpp"
  6 +#include "../ai_platform/mvpt_process_assist.h"
  7 +
  8 +#if 0
  9 +#include "opencv2/opencv.hpp"
  10 +#include "opencv2/imgcodecs/legacy/constants_c.h"
  11 +#endif
  12 +
  13 +namespace ai_engine_module
  14 +{
  15 + namespace traffic_light_process
  16 + {
  17 + static std::set<algorithm_type_t> algor_type_list_ = {
  18 + algorithm_type_t::PERSON_RUNNING_REDLIGHTS,
  19 + algorithm_type_t::NONMOTOR_RUNNING_REDLIGHTS,
  20 + };
  21 +
  22 + inline bool is_valid_label(const label_t &label) {
  23 + return ((label == label_t::red));
  24 + }
  25 +
  26 + std::set<algorithm_type_t> task_id_to_algorithm_type_seq(const task_id_t &task_id,
  27 + task_param_manager *const task_param) {
  28 + std::set<algorithm_type_t> seq;
  29 + auto &&algor_map = task_param->get_task_other_param(task_id);
  30 + if (algor_map) {
  31 + // LOG_TRACE("task id is {} size algor type {}", task_id, algor_map->size());
  32 + for (auto iter = algor_map->begin(); iter != algor_map->end(); ++iter) {
  33 + if (algor_type_list_.count(iter->first) > 0)
  34 + seq.emplace(iter->first);
  35 + }
  36 + }
  37 + return seq; // N(RVO)
  38 + }
  39 +
  40 + bool is_valid_box(const int top, const int left, const int right, const int bottom, const float score,
  41 + const algorithm_type_t &algor_type,
  42 + const task_param_manager::algo_param_type_t_ *params_ptr = nullptr) {
  43 + if (!params_ptr)
  44 + return false;
  45 +
  46 + if (!snapshot_legal_inarea(params_ptr->basic_param->algor_valid_rect, left, top, right, bottom))
  47 + return false;
  48 +
  49 + if (params_ptr->algor_param == nullptr)
  50 + return false;
  51 +
  52 +
  53 + const unsigned width = right - left;
  54 + const unsigned height = bottom - top;
  55 +
  56 + if (width == 0 || height == 0)
  57 + return false;
  58 +
  59 + //! TODO: use switch to replace.
  60 + using data_t = algor_config_param_manned_incident;
  61 + data_t *algor_params_ptr = (data_t *) (params_ptr->algor_param);
  62 +
  63 + if ((width < algor_params_ptr->obj_min_width || height < algor_params_ptr->obj_min_height || score < algor_params_ptr->obj_confidence_threshold))
  64 + return false;
  65 +
  66 + return true;
  67 + }
  68 +
  69 + vector<tr_point> Mbuild_area(vector<int> args)
  70 + {
  71 + vector<tr_point> result;
  72 + int points_check = args.size();
  73 + //需x y作为一组，是偶数
  74 + if (points_check % 2 == 1) {
  75 + LOG_ERROR("points need x and y, but only get one");
  76 + exit(0);
  77 + }
  78 +
  79 + for (int i = 0; i < points_check; i++) {
  80 + if (i % 2 == 0) {
  81 + tr_point tmp_point;
  82 + tmp_point.x = args[i];
  83 + result.push_back(tmp_point);
  84 + }
  85 + else {
  86 + result[result.size() - 1].y = args[i];
  87 + }
  88 + }
  89 +
  90 + return result;
  91 + }
  92 +
  93 + bool McheckPointPolygon(vector<tr_point> tr_boxes, tr_point pCur) {
  94 + //任意四边形有4个顶点
  95 + int nCount = tr_boxes.size();
  96 + tr_point RectPoints[MAX_LANE_NUM];
  97 +
  98 + // std::cout << "ponits: ";
  99 + for (int i = 0; i < nCount; i++) {
  100 + RectPoints[i] = tr_boxes[i];
  101 + // std::cout << tr_boxes[i].x << " " << tr_boxes[i].y << " ";
  102 + }
  103 + // std::cout << std::endl;
  104 +
  105 + int nCross = 0;
  106 + pCur.y += 0.1;
  107 + for (int i = 0; i < nCount; i++) {
  108 + //依次取相邻的两个点
  109 + tr_point pStart = RectPoints[i];
  110 + tr_point pEnd = RectPoints[(i + 1) % nCount];
  111 +
  112 + //相邻的两个点是平行于x轴的，肯定不相交，忽略
  113 + if (pStart.y == pEnd.y) continue;
  114 +
  115 + //交点在pStart,pEnd的延长线上，pCur肯定不会与pStart.pEnd相交，忽略
  116 + if (pCur.y < min(pStart.y, pEnd.y) || pCur.y > max(pStart.y, pEnd.y)) continue;
  117 +
  118 + //求当前点和x轴的平行线与pStart,pEnd直线的交点的x坐标
  119 + double x = (double)(pCur.y - pStart.y) * (double)(pEnd.x - pStart.x) / (double)(pEnd.y - pStart.y) + pStart.x;
  120 +
  121 + //若x坐标大于当前点的坐标，则有交点
  122 + if (x > pCur.x) nCross++;
  123 + }
  124 +
  125 + // 单边交点为偶数，点在多边形之外
  126 + return (nCross % 2 == 1);
  127 + }
  128 +
  129 +#if 0
  130 + void CvtYuvToBgr(sy_img src, sy_img dst) {
  131 + const int uvStart = src.w_ * src.h_;
  132 + for (int h = 0; h < dst.h_; h++) {
  133 + for (int w = 0; w < dst.w_; w++) {
  134 + int uvIndex = h / 2 * src.w_ + w - w % 2;
  135 + unsigned char y = *(src.data_ + w + h * src.w_);
  136 + unsigned char u = *(src.data_ + uvStart + uvIndex);
  137 + unsigned char v = *(src.data_ + uvStart + uvIndex + 1);
  138 +
  139 + int r = (int)(y + 1.402 * (v - 128));
  140 + int g = (int)(y - 0.34414 * (u - 128) - 0.71414 * (v - 128));
  141 + int b = (int)(y + 1.772 * (u -128));
  142 +
  143 + if (r > 255) r = 255;
  144 + if (g > 255) g = 255;
  145 + if (b > 255) b = 255;
  146 + if (r < 0) r = 0;
  147 + if (g < 0) g = 0;
  148 + if (b < 0) b = 0;
  149 + *(dst.data_ + h * dst.w_ * 3 + w * 3) = b;
  150 + *(dst.data_ + h * dst.w_ * 3 + w * 3 + 1) = g;
  151 + *(dst.data_ + h * dst.w_ * 3 + w * 3 + 2) = r;
  152 + }
  153 + }
  154 + }
  155 +#endif
  156 +
  157 + TrafficLightProcess::TrafficLightProcess()
  158 + : task_param_manager_(nullptr)
  159 + {
  160 +
  161 + }
  162 +
  163 + TrafficLightProcess::~TrafficLightProcess()
  164 + {
  165 + if (tools_) {
  166 + traffic_light_release(&tools_);
  167 + tools_ = nullptr;
  168 + }
  169 + if (m_algorthim_ctx) {
  170 + aclrtDestroyContext(m_algorthim_ctx);
  171 + }
  172 + }
  173 +
  174 + bool TrafficLightProcess::init(int gpu_id, string models_dir)
  175 + {
  176 + init_ = false;
  177 +
  178 + string model_path = models_dir + "/models/village/trlight_det_310p.om" ;
  179 + LOG_INFO("traffic_light 版本：{} 模型路径：{}", traffic_light_getversion(), model_path);
  180 +
  181 + traffic_light_param param;
  182 + char modelNames[100];
  183 + strcpy(modelNames, model_path.c_str());
  184 + param.modelNames = modelNames;
  185 + param.thresld = 0.25;
  186 + param.devId = gpu_id;
  187 +
  188 + m_devId = param.devId;
  189 + ACL_CALL(aclrtSetDevice(m_devId), ACL_SUCCESS, -1);
  190 + ACL_CALL(aclrtCreateContext(&m_algorthim_ctx, m_devId), ACL_SUCCESS, -1);
  191 +
  192 + int status;
  193 + if (!(init_ = (0 == (status = traffic_light_init(&tools_, param)))))
  194 + LOG_ERROR("Init TrafficLightProcessSdk failed error code is {}", status);
  195 + else
  196 + if (!task_param_manager_)
  197 + task_param_manager_ = task_param_manager::getInstance();
  198 + return init_;
  199 + }
  200 +
  201 +
  202 + bool TrafficLightProcess::check_initied()
  203 + {
  204 + if (!init_)
  205 + LOG_ERROR("[%s:%d] call init function please.", __FILE__, __LINE__);
  206 + return init_;
  207 + }
  208 +
  209 +
  210 + void TrafficLightProcess::force_release_result(const task_id_t& task_id) {
  211 + for (auto iter = id_to_result_.begin(); iter != id_to_result_.end();) {
  212 + const auto& key = iter->first;
  213 + if (key.task_id == task_id) {
  214 + auto& value = iter->second;
  215 + if (value.origin_img_desc != nullptr) {
  216 + VPCUtil::vpc_pic_desc_release(value.origin_img_desc);
  217 + }
  218 +
  219 + if (value.roi_img_desc != nullptr) {
  220 + VPCUtil::vpc_pic_desc_release(value.roi_img_desc);
  221 + }
  222 + iter = id_to_result_.erase(iter);
  223 + }
  224 + else {
  225 + ++iter;
  226 + }
  227 +
  228 + }
  229 + }
  230 +
  231 + std::shared_ptr<results_data_t> TrafficLightProcess::get_result_by_objectid(const id_t& id, bool do_erase)
  232 + {
  233 + auto it = id_to_result_.find(id);
  234 + if (it == id_to_result_.end())
  235 + return std::shared_ptr<results_data_t>(nullptr);
  236 + std::shared_ptr<results_data_t> res = std::make_shared<results_data_t>(it->second);
  237 + if (do_erase)
  238 + id_to_result_.erase(id);
  239 + return res;
  240 + }
  241 +
  242 + bool TrafficLightProcess::update_mstreams(const std::vector<task_id_t>& taskIds, vector<sy_img> src_interest_imgs, vector<DeviceMemory*> vec_det_input_images, const std::vector<onelevel_det_result> &det_results)
  243 + {
  244 + if (!check_initied())
  245 + return false;
  246 +
  247 + if (det_results.empty())
  248 + {
  249 + LOG_DEBUG("detection result is empty.");
  250 + return false;
  251 + }
  252 +
  253 + struct stream_idx_and_algor_seq_t {
  254 + unsigned stream_idx;
  255 + std::set<algorithm_type_t> algors;
  256 + };
  257 +
  258 + int n_images = det_results.size(); // or n_stream
  259 +
  260 + unsigned flattened_idx = 0;
  261 + std::map<int, int> flattened_idx_to_batch_idx;
  262 + //! 记录每个box对应的算法以及流id.
  263 + std::map<unsigned, stream_idx_and_algor_seq_t> flattened_idx_to_algor_seq;
  264 +
  265 + /* 1. Crop & keep some interest class. */
  266 + auto taskId_iter = taskIds.begin();
  267 + std::vector<sy_img> flattened_imgs(0);
  268 + std::vector<vpc_img_info> flattened_vpc_imgs(0);
  269 + std::vector<input_data_wrap_t> flattened_interest_data(0); //
  270 + VPCUtil* pVpcUtil = VPCUtil::getInstance();
  271 + for (int n = 0; n < n_images; ++n)
  272 + {
  273 + int n_interest_obj = 0;
  274 + auto& src_img = vec_det_input_images[n];
  275 + int src_img_w = src_img->getWidth();
  276 + int src_img_h = src_img->getHeight();
  277 +
  278 + auto& boxes_of_one_image = det_results[n].obj;
  279 + for (int i = 0; i < det_results[n].obj_count; ++i)
  280 + {
  281 + auto& box = boxes_of_one_image[i];
  282 + if (static_cast<det_class_label_t>(box.index) == det_class_label_t::MOTOCYCLE || static_cast<det_class_label_t>(box.index) == det_class_label_t::BICYCLE || static_cast<det_class_label_t>(box.index) == det_class_label_t::HUMAN)
  283 + {
  284 + auto& taskId = *taskId_iter;
  285 + input_data_wrap_t data;
  286 + int top = std::max(int(box.top - (IMAGE_CROP_EXPAND_RATIO * box.top)), 0);
  287 + int left = std::max(int(box.left - (IMAGE_CROP_EXPAND_RATIO * box.left)), 0);
  288 + int right = std::min(int(box.right + (IMAGE_CROP_EXPAND_RATIO * box.right)), src_img_w);
  289 + int bottom = std::min(int(box.bottom + (IMAGE_CROP_EXPAND_RATIO * box.bottom)), src_img_h);
  290 +
  291 + //! loop per algor from set.
  292 + stream_idx_and_algor_seq_t stream_idx_and_algor_seq{n, {}};
  293 + std::set<algorithm_type_t> algorithm_type_seq = task_id_to_algorithm_type_seq(taskId,
  294 + task_param_manager_); // N(RVO).
  295 +
  296 + for (auto algor_iter = algorithm_type_seq.begin();algor_iter != algorithm_type_seq.end(); ++algor_iter) {
  297 + const algorithm_type_t algor_type = *algor_iter;
  298 + auto &&algor_param_wrap = task_param_manager_->get_task_other_param(taskId, algor_type);
  299 + if (!algor_param_wrap) {
  300 + LOG_ERROR("{} is nullptr when get algor param from task_param", taskId.c_str());
  301 + continue;
  302 + }
  303 +
  304 + if (!is_valid_box(top, left, right, bottom, box.confidence, algor_type, algor_param_wrap))
  305 + continue;
  306 +
  307 + //DEBUG增加多边形区域选择及判断================================================================
  308 + tr_point curpos;
  309 + curpos.x = (left + right) * 0.5; curpos.y = bottom;
  310 + vector<int> args = {1552,435,1756,537,1915,537,1915,499,1725,435}; //区域(泰兴黄桥锦润福府路口)
  311 + // vector<int> args = {0,0,0,1080,1920,1080,1920,0}; //区域
  312 + vector<tr_point> tr_boxes = Mbuild_area(args);
  313 + int cur_flag = McheckPointPolygon(tr_boxes, curpos); //cur_flag==true表示在区域内
  314 + if (!cur_flag) continue;
  315 + //DEBUG END==================================================================================
  316 + stream_idx_and_algor_seq.algors.emplace(algor_type);
  317 + }
  318 +
  319 + if (stream_idx_and_algor_seq.algors.empty())
  320 + continue;
  321 +
  322 + int width = right - left;
  323 + int height = bottom - top;
  324 +
  325 + data.box.top = top; data.box.left = left;
  326 + data.box.right = right; data.box.bottom = bottom;
  327 + data.box.score = box.confidence; data.box.cls = box.index;
  328 + data.taskId = taskId; data.objId = box.id;
  329 +
  330 + // 抠图
  331 + video_object_info obj;
  332 + strcpy(obj.task_id, taskId.c_str());
  333 + obj.object_id = box.id;
  334 + obj.left = left; obj.top = top;
  335 + obj.right = right; obj.bottom = bottom;
  336 +
  337 + vpc_img_info img_info = pVpcUtil->crop(src_img, obj);
  338 +
  339 + sy_img img;
  340 + img.w_ = width;
  341 + img.h_ = height;
  342 + img.c_ = src_img->getChannel();
  343 +
  344 + if (img_info.pic_desc != nullptr) {
  345 + void *outputDataDev = acldvppGetPicDescData(img_info.pic_desc);
  346 + img.data_ = reinterpret_cast<unsigned char*>(outputDataDev);
  347 + }
  348 + else {
  349 + LOG_ERROR("Crop image NPU failed wh is [{}, {}] ltrb is [{} {} {} {}]",
  350 + src_img_w, src_img_h, data.box.left, data.box.top, data.box.right, data.box.bottom);
  351 + continue;
  352 + }
  353 +
  354 + flattened_imgs.emplace_back(std::move(img));
  355 + flattened_vpc_imgs.emplace_back(std::move(img_info));
  356 + flattened_interest_data.emplace_back(std::move(data));
  357 + flattened_idx_to_algor_seq[flattened_idx] = std::move(stream_idx_and_algor_seq);
  358 + flattened_idx_to_batch_idx[flattened_idx++] = n;
  359 + }
  360 + }
  361 + ++taskId_iter;
  362 + }
  363 +
  364 + int ret = aclrtSetCurrentContext(m_algorthim_ctx);
  365 + if (ACL_SUCCESS != ret) {
  366 + return false;
  367 + }
  368 + /* 2. collection result. */
  369 + int n_input_image = flattened_imgs.size();
  370 + int n_input_src_image = src_interest_imgs.size();
  371 + traffic_light_result model_results[n_input_src_image];
  372 + {
  373 + int steps = (n_input_src_image + MAX_BATCH - 1) / MAX_BATCH;
  374 + for (int step = 0; step < steps; ++step)
  375 + {
  376 + int offset = step * MAX_BATCH;
  377 + int batch_size = (step == steps - 1) ? n_input_src_image - offset : MAX_BATCH;
  378 + traffic_light_process_batch(tools_, src_interest_imgs.data() + offset, batch_size, model_results + offset);
  379 + }
  380 + }
  381 +
  382 + /* 3. postprocess. */
  383 + {
  384 + for (int n = 0; n < n_input_image; ++n)
  385 + {
  386 + auto& det_result = flattened_interest_data[n];
  387 + auto& objId = det_result.objId;
  388 + auto& task_id = det_result.taskId;
  389 +
  390 + auto &stream_idx_and_algor_seq = flattened_idx_to_algor_seq[n];
  391 + auto &algors = stream_idx_and_algor_seq.algors;
  392 + // auto &steram_idx = stream_idx_and_algor_seq.stream_idx;
  393 +
  394 + const auto& src_img = vec_det_input_images[flattened_idx_to_batch_idx[n]];
  395 + auto &model_result = model_results[flattened_idx_to_batch_idx[n]];
  396 + int red_cnt = 0; //统计直行红灯个数
  397 + for (unsigned i = 0; i < model_result.objcount; ++i) {
  398 + auto &box = model_result.objinfo[i];
  399 + const label_t label = static_cast<label_t>(box.index);
  400 + if (!is_valid_label(label))
  401 + continue;
  402 + if (box.left < 1200 || box.top < 159 || box.right > 1307 || box.bottom > 212) continue; // 限制红绿灯的出现位置(泰兴黄桥锦润福府路口)
  403 + LOG_TRACE("task id is {} obj_id {} label {} index {} score {}", task_id, objId, label, box.index, box.confidence);
  404 + red_cnt ++;
  405 + }
  406 +#if 0
  407 + if (red_cnt > 0) {
  408 + sy_img img = src_interest_imgs[flattened_idx_to_batch_idx[n]];
  409 + int dataSize = img.w_ * img.h_ * 3 / 2;
  410 + uint8_t* buffer = new uint8_t[dataSize];
  411 + uint8_t* imgBgr = new uint8_t[dataSize];
  412 + aclError aclRet = aclrtMemcpy(buffer, dataSize, img.data_, dataSize, ACL_MEMCPY_DEVICE_TO_HOST);
  413 +
  414 + sy_img imgyuv_local, tmpbgr;
  415 + imgyuv_local.data_ = (unsigned char*)buffer; imgyuv_local.w_ = img.w_; imgyuv_local.h_ = img.h_;
  416 + tmpbgr.w_ = img.w_; tmpbgr.h_ = img.h_; tmpbgr.data_ = imgBgr;
  417 + CvtYuvToBgr(imgyuv_local, tmpbgr);
  418 +
  419 + cv::Mat cvImg = cv::Mat(tmpbgr.h_, tmpbgr.w_, CV_8UC3, tmpbgr.data_);
  420 + string jpgSaveName1 = "result/oral/" + task_id + "_" + to_string(objId) + ".jpg";
  421 + cv::imwrite(jpgSaveName1, cvImg);
  422 + for (unsigned i = 0; i < model_result.objcount; ++i) {
  423 + cv::Point lt(model_result.objinfo[i].left, model_result.objinfo[i].top);
  424 + cv::Point rb(model_result.objinfo[i].right, model_result.objinfo[i].bottom);
  425 + cv::rectangle(cvImg, lt, rb, cv::Scalar(0, 0, 255), 3);
  426 +
  427 + char buffer[50]; int fontface = cv::FONT_HERSHEY_SIMPLEX; double scale = 0.8; int thickness = 2; int baseline = 0;
  428 + snprintf(buffer, sizeof(buffer), "%d:%.2f", model_result.objinfo[i].index, model_result.objinfo[i].confidence);
  429 + cv::Size text = cv::getTextSize(buffer, fontface, scale, thickness, &baseline);
  430 + cv::putText(cvImg, buffer, lt - cv::Point(0, baseline), fontface, scale, cv::Scalar(0, 0, 255), thickness, 8);
  431 + }
  432 + string jpgSaveName2 = "result/draw/" + task_id + "_" + to_string(objId) + ".jpg";
  433 + cv::imwrite(jpgSaveName2, cvImg);
  434 +
  435 + delete[] buffer; buffer = NULL;
  436 + delete[] imgBgr; imgBgr = NULL;
  437 + }
  438 +#endif
  439 +
  440 + for (auto algor_type_iter = algors.begin();algor_type_iter != algors.end(); ++algor_type_iter) {
  441 + const algorithm_type_t algor_type = *algor_type_iter;
  442 +
  443 + auto &&algor_param_wrap = task_param_manager_->get_task_other_param(task_id, algor_type);
  444 + if (!algor_param_wrap) {
  445 + LOG_ERROR("{} is nullptr when get algor param from task_param", task_id);
  446 + continue;
  447 + }
  448 + auto algor_param = ((algor_param_type)algor_param_wrap->algor_param);
  449 +
  450 + id_t obj_key = obj_key_t{ objId, task_id, algor_type};
  451 + if (id_to_result_.find(obj_key) != id_to_result_.end())
  452 + continue;
  453 +
  454 + // LOG_TRACE("task id is {} algor type is {} obj_id {}", task_id, int(algor_type), objId);
  455 + if (algor_type == algorithm_type_t::PERSON_RUNNING_REDLIGHTS && static_cast<det_class_label_t>(det_result.box.cls) != det_class_label_t::HUMAN)
  456 + continue;
  457 + if (algor_type == algorithm_type_t::NONMOTOR_RUNNING_REDLIGHTS && (static_cast<det_class_label_t>(det_result.box.cls) != det_class_label_t::MOTOCYCLE ||
  458 + static_cast<det_class_label_t>(det_result.box.cls) != det_class_label_t::BICYCLE))
  459 + continue;
  460 +
  461 + auto& e = id_to_mn_[obj_key];
  462 + ++e.m_frame;
  463 +
  464 + // 数量小于设定阈值不报警
  465 + if (red_cnt < 1)
  466 + continue;
  467 +
  468 + {
  469 + if (++e.n_frame == algor_param->n)
  470 + {
  471 + results_data_t result;
  472 + { LOG_TRACE("task id is {} obj_id {} red_cnt {}", task_id, det_result.objId, red_cnt);
  473 + result.box = det_result.box;
  474 + result.taskId = det_result.taskId;
  475 + result.objId = det_result.objId;
  476 + result.algor_type = algor_type;
  477 + // 原图
  478 + vpc_img_info src_img_info = VPCUtil::vpc_devMem2vpcImg(src_img);
  479 + result.origin_img_desc = src_img_info.pic_desc;
  480 + // 抠图--拷贝后赋值
  481 + void *outputDataDev = acldvppGetPicDescData(flattened_vpc_imgs[n].pic_desc);
  482 + int nBufferSize = acldvppGetPicDescSize(flattened_vpc_imgs[n].pic_desc);
  483 +
  484 + void *devBuffer = nullptr;
  485 + auto ret = acldvppMalloc(&devBuffer, nBufferSize);
  486 + if (ret != ACL_SUCCESS) {
  487 + LOG_ERROR("acldvppMalloc failed, size = %u, errorCode = %d.", nBufferSize, static_cast<int32_t>(ret));
  488 + return false;
  489 + }
  490 + aclrtMemcpy(devBuffer, nBufferSize, outputDataDev, nBufferSize, ACL_MEMCPY_DEVICE_TO_DEVICE);
  491 +
  492 + acldvppPicDesc *vpcInputDesc_= acldvppCreatePicDesc();
  493 + acldvppSetPicDescData(vpcInputDesc_, devBuffer);
  494 + acldvppSetPicDescFormat(vpcInputDesc_, PIXEL_FORMAT_YUV_SEMIPLANAR_420);
  495 + acldvppSetPicDescWidth(vpcInputDesc_, acldvppGetPicDescWidth(flattened_vpc_imgs[n].pic_desc));
  496 + acldvppSetPicDescHeight(vpcInputDesc_, acldvppGetPicDescHeight(flattened_vpc_imgs[n].pic_desc));
  497 + acldvppSetPicDescWidthStride(vpcInputDesc_, acldvppGetPicDescWidthStride(flattened_vpc_imgs[n].pic_desc));
  498 + acldvppSetPicDescHeightStride(vpcInputDesc_, acldvppGetPicDescHeightStride(flattened_vpc_imgs[n].pic_desc));
  499 + acldvppSetPicDescSize(vpcInputDesc_, nBufferSize);
  500 +
  501 + result.roi_img_desc = vpcInputDesc_; //需复制
  502 + }
  503 + id_to_result_.emplace(obj_key, std::move(result));
  504 + }
  505 + }
  506 +
  507 + if (e.m_frame == algor_param->m)
  508 + e.reset();
  509 +
  510 + }
  511 +
  512 + VPCUtil::vpc_img_release(flattened_vpc_imgs[n]); //flattened_imgs[n].data_
  513 +
  514 + }
  515 + }
  516 +
  517 + return true;
  518 + }
  519 +
  520 + } // namespace traffic_light_process
  521 +
  522 +} // namespace ai_engine_module
  523 +
... ...
src/ai_engine_module/traffic_light_process.h 0 → 100644
  View file @fa81830
  1 +#pragma once
  2 +#include <deque>
  3 +#include <map>
  4 +#include <vector>
  5 +#include <memory>
  6 +#include "../util/vpc_util.h"
  7 +#include "../ai_platform/task_param_manager.h"
  8 +#include "../ai_platform/macro_definition.h"
  9 +#include "ai_engine_header.h"
  10 +#include "traffic_light_det.h"
  11 +#include "acl/acl.h"
  12 +#include "acl/ops/acl_dvpp.h"
  13 +
  14 +#define MAX_BATCH 20
  15 +#define IMAGE_CROP_EXPAND_RATIO 0
  16 +#define MAX_OBJ_BOX_COUNT 100
  17 +#define MAX_LANE_NUM 100
  18 +
  19 +namespace ai_engine_module
  20 +{
  21 + namespace traffic_light_process
  22 + {
  23 + // typedef long id_t;
  24 + using id_t = obj_key_t;
  25 + using task_id_t = std::string;
  26 + using algor_param_type = algor_config_param_manned_incident*;
  27 +
  28 + enum class label_t {
  29 + PLACEHOLDER = -1,
  30 + red = 0, //直行红灯
  31 + green = 1, //直行绿灯
  32 + yellow = 2, //直行黄灯
  33 + wred = 3, //转向红灯
  34 + wgreen = 4, //转向绿灯
  35 + wyellow = 5, //转向黄灯
  36 + pred = 6, //行人红灯
  37 + pyellow = 7, //行人黄灯
  38 + pgreen = 8, //行人绿灯
  39 + bred = 9, //自行车红灯
  40 + byellow = 10, //自行车黄灯
  41 + bgreen = 11, //自行车绿灯
  42 + no = 12, //灭灯
  43 + };
  44 +
  45 + typedef struct input_data_wrap_t
  46 + {
  47 + id_t id;
  48 + long objId;
  49 + std::string taskId;
  50 + box_t box;
  51 + } input_data_wrap_t;
  52 +
  53 + typedef struct tr_point {
  54 + float x, y;
  55 + }tr_point;
  56 +
  57 +
  58 + typedef struct mn_frame_t
  59 + {
  60 + uint m_frame;
  61 + uint n_frame;
  62 +
  63 + // explicit
  64 + mn_frame_t(uint m = 0, uint n = 0)
  65 + : m_frame(m)
  66 + , n_frame(n)
  67 + {}
  68 +
  69 + void reset()
  70 + {
  71 + m_frame = 0;
  72 + n_frame = 0;
  73 + }
  74 +
  75 + } mn_frame_t;
  76 +
  77 +
  78 + typedef struct results_data_t
  79 + {
  80 + box_t box;
  81 + acldvppPicDesc* origin_img_desc{nullptr};
  82 + acldvppPicDesc* roi_img_desc{nullptr};
  83 + id_t id;
  84 + long objId;
  85 + std::string taskId;
  86 + algorithm_type_t algor_type;
  87 + } results_data_t;
  88 +
  89 + class TrafficLightProcess
  90 + {
  91 + /**
  92 + * @brief
  93 + * 1. move able
  94 + */
  95 + public:
  96 + TrafficLightProcess();
  97 +
  98 + ~TrafficLightProcess();
  99 +
  100 + bool check_initied();
  101 + bool init(int gpu_id, string models_dir);
  102 + bool update_mstreams(const std::vector<task_id_t>& taskIds, vector<sy_img> src_interest_imgs, vector<DeviceMemory*> vec_det_input_images, const std::vector<onelevel_det_result> &det_results);
  103 + std::shared_ptr<results_data_t> get_result_by_objectid(const id_t& id, bool do_erase = true);
  104 +
  105 + void force_release_result(const task_id_t& task_id);
  106 +
  107 + TrafficLightProcess(const TrafficLightProcess&) = delete;
  108 + TrafficLightProcess& operator=(const TrafficLightProcess&) = delete;
  109 +
  110 + private:
  111 + static algorithm_type_t algor_type_;
  112 + int m_devId;
  113 + aclrtContext m_algorthim_ctx;
  114 +
  115 + bool init_;
  116 + void* tools_;
  117 + task_param_manager* task_param_manager_;
  118 + std::map<id_t, mn_frame_t> id_to_mn_;
  119 + std::map<id_t, results_data_t> id_to_result_;
  120 + };
  121 + } // namespace traffic_light_process
  122 +} // namespace ai_engine_module
  123 +
... ...
src/ai_engine_module/truck_manned_process.cpp
  View file @fa81830
... ... @@ -12,6 +12,28 @@ namespace ai_engine_module
12 12 {
13 13 algorithm_type_t TruckMannedProcess::algor_type_ = algorithm_type_t::TRUCK_MANNED;
14 14  
  15 + int legal_person_motocycle_inarea(const std::vector<input_data_wrap_t>& person_motocycle_data, int left, int top, int right, int bottom) {
  16 + int legal_person_motocycle_count = 0;
  17 + for (const auto& det_result : person_motocycle_data) {
  18 + int x1_intersection = std::max(det_result.box.left, left);
  19 + int y1_intersection = std::max(det_result.box.top, top);
  20 + int x2_intersection = std::min(det_result.box.right, right);
  21 + int y2_intersection = std::min(det_result.box.bottom, bottom);
  22 +
  23 + if (x2_intersection <= x1_intersection || y2_intersection <= y1_intersection) continue; // 没有交集
  24 + float area_a = float(det_result.box.right - det_result.box.left) * float(det_result.box.bottom - det_result.box.top);
  25 + float area_b = float(right - left) * float(bottom - top);
  26 + float area_intersection = float(x2_intersection - x1_intersection) * float(y2_intersection - y1_intersection);
  27 +
  28 + if (area_a > area_b || area_a <= 0) continue; //暂不考虑非机动车目标比货车大的情况
  29 + // float iou = area_intersection / (area_a + area_b - area_intersection);
  30 + float small_overlap_ratio = area_intersection / area_a; //计算非机动车目标相对于自身的重叠程度
  31 + if (small_overlap_ratio > 0.2) legal_person_motocycle_count ++;
  32 + }
  33 + return legal_person_motocycle_count;
  34 +
  35 + }
  36 +
15 37 TruckMannedProcess::TruckMannedProcess()
16 38 : task_param_manager_(nullptr)
17 39 {
... ... @@ -127,6 +149,34 @@ namespace ai_engine_module
127 149 int src_img_h = src_img->getHeight();
128 150  
129 151 auto& boxes_of_one_image = det_results[n].obj;
  152 +
  153 + //汇总当前帧的行人/非机动车目标
  154 + std::vector<input_data_wrap_t> person_motocycle_data(0);
  155 + for (int i = 0; i < det_results[n].obj_count; ++i)
  156 + {
  157 + auto& box = boxes_of_one_image[i];
  158 + if (static_cast<det_class_label_t>(box.index) == det_class_label_t::MOTOCYCLE || static_cast<det_class_label_t>(box.index) == det_class_label_t::BICYCLE ||
  159 + static_cast<det_class_label_t>(box.index) == det_class_label_t::HUMAN || static_cast<det_class_label_t>(box.index) == det_class_label_t::TRICYCLE)
  160 + {
  161 + auto& taskId = *taskId_iter;
  162 + input_data_wrap_t data;
  163 + int top = std::max(int(box.top), 0); int left = std::max(int(box.left), 0);
  164 + int right = std::min(int(box.right), src_img_w); int bottom = std::min(int(box.bottom), src_img_h);
  165 + int width = right - left; int height = bottom - top;
  166 +
  167 + if (static_cast<det_class_label_t>(box.index) == det_class_label_t::HUMAN && width >= 0.9*height) //基于载人只能看到半身的假设
  168 + continue;
  169 +
  170 + data.box.top = top; data.box.left = left;
  171 + data.box.right = right; data.box.bottom = bottom;
  172 + data.box.score = box.confidence; data.box.cls = box.index;
  173 + data.taskId = taskId; data.objId = box.id;
  174 +
  175 + person_motocycle_data.emplace_back(std::move(data));
  176 + }
  177 + }
  178 +
  179 +
130 180 for (int i = 0; i < det_results[n].obj_count; ++i)
131 181 {
132 182 auto& box = boxes_of_one_image[i];
... ... @@ -154,14 +204,15 @@ namespace ai_engine_module
154 204 !snapshot_legal_inarea(algor_param_wrap->basic_param->algor_valid_rect, left, top, right, bottom))
155 205 continue;
156 206  
157   - data.box.top = top;
158   - data.box.left = left;
159   - data.box.right = right;
160   - data.box.bottom = bottom;
  207 + //统计货车检测框内行人及非机动车的数量
  208 + int person_motocycle_inarea = legal_person_motocycle_inarea(person_motocycle_data, left, top, right, bottom);
  209 +
  210 + data.box.top = top; data.box.left = left;
  211 + data.box.right = right; data.box.bottom = bottom;
161 212 data.box.score = box.confidence;
162   - data.taskId = taskId;
163   - data.objId = box.id;
  213 + data.taskId = taskId; data.objId = box.id;
164 214 data.id = obj_key_t{ box.id, taskId, algorithm_type_t::TRUCK_MANNED };
  215 + data.person_motocycle_cnt = person_motocycle_inarea;
165 216  
166 217 // 抠图
167 218 video_object_info obj;
... ... @@ -193,6 +244,7 @@ namespace ai_engine_module
193 244 flattened_idx_to_batch_idx[flattened_idx++] = n;
194 245 }
195 246 }
  247 + std::vector<input_data_wrap_t>().swap(person_motocycle_data);
196 248 ++taskId_iter;
197 249 }
198 250  
... ... @@ -246,7 +298,8 @@ namespace ai_engine_module
246 298 auto& e = id_to_mn_[obj_key];
247 299 ++e.m_frame;
248 300  
249   - if (hs_count >= algor_param->hs_count_threshold)
  301 + // if (hs_count >= algor_param->hs_count_threshold)
  302 + if (hs_count - det_result.person_motocycle_cnt >= algor_param->hs_count_threshold) //头肩数量去除包含的行人和非机动车数量
250 303 {
251 304 if (++e.n_frame == algor_param->n)
252 305 {
... ...
src/ai_engine_module/truck_manned_process.h
  View file @fa81830
... ... @@ -28,6 +28,7 @@ namespace ai_engine_module
28 28 {
29 29 id_t id;
30 30 long objId;
  31 + int person_motocycle_cnt;
31 32 std::string taskId;
32 33 box_t box;
33 34 } input_data_wrap_t;
... ...
src/ai_platform/MultiSourceProcess.cpp
  View file @fa81830
... ... @@ -195,6 +195,11 @@ int CMultiSourceProcess::InitAlgorthim(tsl_aiplatform_param vptParam){
195 195 LOG_FATAL("Init motor_refit failed");
196 196 return -1;
197 197 }
  198 + // 行人/二轮车闯红灯
  199 + if (!traffic_lightprocess_.init(vptParam.gpuid, models_dir)) {
  200 + LOG_FATAL("Init traffic_light failed");
  201 + return -1;
  202 + }
198 203 #endif
199 204  
200 205 #ifdef WITH_FACE_DET_SS
... ... @@ -711,6 +716,7 @@ bool CMultiSourceProcess::finish_task(const string taskID, const bool delete_sna
711 716 motor_refit_phoneprocess_.force_release_result(taskID);
712 717 // motor_phoneprocess_.force_release_result(taskID);
713 718 motor_refitprocess_.force_release_result(taskID);
  719 + traffic_lightprocess_.force_release_result(taskID);
714 720  
715 721 m_task_param_manager->delete_task_param(taskID);
716 722 #endif
... ... @@ -905,6 +911,8 @@ int CMultiSourceProcess::algorthim_vpt(vector&lt;DeviceMemory*&gt; vec_gpuMem){
905 911 algorithm_motor_phone_process(vpt_interest_task_id, vec_vptMem, vptResult);*/
906 912 // 电动车改装(加雨棚)
907 913 algorithm_motor_refit_process(vpt_interest_task_id, vec_vptMem, vptResult);
  914 + // 行人/二轮车闯红灯
  915 + algorithm_traffic_light_process(vpt_interest_task_id, vec_vptMem, vptResult);
908 916 village_snapshot(vpt_interest_task_id, vec_vptMem, deleteObjectID);
909 917 #endif
910 918  
... ... @@ -1439,6 +1447,42 @@ void CMultiSourceProcess::algorithm_motor_refit_process(vector&lt;string&gt;&amp; vpt_inte
1439 1447 }
1440 1448 }
1441 1449  
  1450 +
  1451 +// 行人/二轮车闯红灯
  1452 +void CMultiSourceProcess::algorithm_traffic_light_process(vector<string>& vpt_interest_task_id, vector<DeviceMemory*> vpt_interest_imgs,
  1453 + vector<onelevel_det_result>& vptResult) {
  1454 +
  1455 + vector<string> interest_task_id;
  1456 + vector<onelevel_det_result> interest_vpt_result;
  1457 + vector<DeviceMemory*> interest_imgs;
  1458 + vector<sy_img> sy_interest_imgs;
  1459 +
  1460 + int _idx = 0;
  1461 + for (auto _task_id_iter = vpt_interest_task_id.begin(); _task_id_iter != vpt_interest_task_id.end();
  1462 + ++_task_id_iter, ++_idx) // loop task_id;
  1463 + {
  1464 + auto task_id = *_task_id_iter;
  1465 + auto algor_map = m_task_param_manager->get_task_other_param(task_id);
  1466 +
  1467 + if (algor_map->find(algorithm_type_t::PERSON_RUNNING_REDLIGHTS) != algor_map->end() ||
  1468 + algor_map->find(algorithm_type_t::NONMOTOR_RUNNING_REDLIGHTS) != algor_map->end()) {
  1469 + DeviceMemory* mem = vpt_interest_imgs[_idx];
  1470 + sy_img img;
  1471 + img.w_ = mem->getWidth(); img.h_ = mem->getHeight();
  1472 + img.c_ = mem->getChannel(); img.data_ = mem->getMem();
  1473 + sy_interest_imgs.push_back(img);
  1474 +
  1475 + interest_task_id.emplace_back(task_id);
  1476 + interest_imgs.emplace_back(vpt_interest_imgs[_idx]);
  1477 + interest_vpt_result.emplace_back(vptResult[_idx]);
  1478 + }
  1479 + }
  1480 +
  1481 + if (!interest_imgs.empty()){
  1482 + traffic_lightprocess_.update_mstreams(interest_task_id, sy_interest_imgs, interest_imgs, interest_vpt_result);
  1483 + }
  1484 +}
  1485 +
1442 1486 // for snapshot algorithm. 轨迹结束目标 做最后的结果返回（当前返回算法结果+快照保存路径）
1443 1487 void CMultiSourceProcess::village_snapshot(vector<string>& vpt_interest_task_id, vector<DeviceMemory*> vec_vptMem, vector<vector<int>> deleteObjectID) {
1444 1488 auto task_iter = vpt_interest_task_id.begin();
... ... @@ -1472,8 +1516,7 @@ void CMultiSourceProcess::village_snapshot(vector&lt;string&gt;&amp; vpt_interest_task_id,
1472 1516 auto json_str = helpers::gen_json::gen_manned_json(obj_key.video_id, obj_key.obj_id, result->box, algorithm_type_t::TRICYCLE_MANNED);
1473 1517 save_snapshot_process(obj_key, algorithm_type_t::TRICYCLE_MANNED, src_img, roi_img, 0, json_str);
1474 1518 } else {
1475   - VPCUtil::vpc_img_release(src_img);
1476   - VPCUtil::vpc_img_release(roi_img);
  1519 + VPCUtil::vpc_img_release(src_img); VPCUtil::vpc_img_release(roi_img);
1477 1520 }
1478 1521  
1479 1522 }
... ... @@ -1496,8 +1539,7 @@ void CMultiSourceProcess::village_snapshot(vector&lt;string&gt;&amp; vpt_interest_task_id,
1496 1539 auto json_str = helpers::gen_json::gen_manned_json(obj_key.video_id, obj_key.obj_id, result->box, algorithm_type_t::TRUCK_MANNED);
1497 1540 save_snapshot_process(obj_key, algorithm_type_t::TRUCK_MANNED, src_img, roi_img, 0, json_str);
1498 1541 } else {
1499   - VPCUtil::vpc_img_release(src_img);
1500   - VPCUtil::vpc_img_release(roi_img);
  1542 + VPCUtil::vpc_img_release(src_img); VPCUtil::vpc_img_release(roi_img);
1501 1543 }
1502 1544  
1503 1545 }
... ... @@ -1520,8 +1562,7 @@ void CMultiSourceProcess::village_snapshot(vector&lt;string&gt;&amp; vpt_interest_task_id,
1520 1562 auto json_str = helpers::gen_json::gen_manned_json(obj_key.video_id, obj_key.obj_id, result->box, algorithm_type_t::NONMOTOR_VEHICLE_NOHELMET);
1521 1563 save_snapshot_process(obj_key, algorithm_type_t::NONMOTOR_VEHICLE_NOHELMET, src_img, roi_img, 0, json_str);
1522 1564 } else {
1523   - VPCUtil::vpc_img_release(src_img);
1524   - VPCUtil::vpc_img_release(roi_img);
  1565 + VPCUtil::vpc_img_release(src_img); VPCUtil::vpc_img_release(roi_img);
1525 1566 }
1526 1567  
1527 1568 }
... ... @@ -1544,8 +1585,7 @@ void CMultiSourceProcess::village_snapshot(vector&lt;string&gt;&amp; vpt_interest_task_id,
1544 1585 auto json_str = helpers::gen_json::gen_manned_json(obj_key.video_id, obj_key.obj_id, result->box, algorithm_type_t::NONMOTOR_VEHICLE_OVERMAN);
1545 1586 save_snapshot_process(obj_key, algorithm_type_t::NONMOTOR_VEHICLE_OVERMAN, src_img, roi_img, 0, json_str);
1546 1587 } else {
1547   - VPCUtil::vpc_img_release(src_img);
1548   - VPCUtil::vpc_img_release(roi_img);
  1588 + VPCUtil::vpc_img_release(src_img); VPCUtil::vpc_img_release(roi_img);
1549 1589 }
1550 1590  
1551 1591 }
... ... @@ -1569,8 +1609,7 @@ void CMultiSourceProcess::village_snapshot(vector&lt;string&gt;&amp; vpt_interest_task_id,
1569 1609 auto json_str = helpers::gen_json::gen_manned_json(obj_key.video_id, obj_key.obj_id, result->box, algorithm_type_t::NONMOTOR_VEHICLE_USEPHONE);
1570 1610 save_snapshot_process(obj_key, algorithm_type_t::NONMOTOR_VEHICLE_USEPHONE, src_img, roi_img, 0, json_str);
1571 1611 } else {
1572   - VPCUtil::vpc_img_release(src_img);
1573   - VPCUtil::vpc_img_release(roi_img);
  1612 + VPCUtil::vpc_img_release(src_img); VPCUtil::vpc_img_release(roi_img);
1574 1613 }
1575 1614  
1576 1615 }
... ... @@ -1594,8 +1633,53 @@ void CMultiSourceProcess::village_snapshot(vector&lt;string&gt;&amp; vpt_interest_task_id,
1594 1633 auto json_str = helpers::gen_json::gen_manned_json(obj_key.video_id, obj_key.obj_id, result->box, algorithm_type_t::NONMOTOR_VEHICLE_REFIT);
1595 1634 save_snapshot_process(obj_key, algorithm_type_t::NONMOTOR_VEHICLE_REFIT, src_img, roi_img, 0, json_str);
1596 1635 } else {
1597   - VPCUtil::vpc_img_release(src_img);
1598   - VPCUtil::vpc_img_release(roi_img);
  1636 + VPCUtil::vpc_img_release(src_img); VPCUtil::vpc_img_release(roi_img);
  1637 + }
  1638 +
  1639 + }
  1640 + }
  1641 +
  1642 + if (task_param_ptr->nonmotor_vehicle_algors.find(algorithm_type_t::NONMOTOR_RUNNING_REDLIGHTS) != task_param_ptr->nonmotor_vehicle_algors.end()) {
  1643 + const auto &algor_other_params = task_other_params->find(algorithm_type_t::NONMOTOR_RUNNING_REDLIGHTS);
  1644 + const algor_basic_config_param_t *basic_param = algor_other_params->second->basic_param;
  1645 +
  1646 + auto result = traffic_lightprocess_.get_result_by_objectid(ai_engine_module::obj_key_t{obj_key.obj_id, obj_key.video_id, algorithm_type_t::NONMOTOR_RUNNING_REDLIGHTS});
  1647 + if (result.get()) {
  1648 + village_alarm = true;
  1649 + algorithm_types.push_back((int)algorithm_type_t::NONMOTOR_RUNNING_REDLIGHTS);
  1650 + video_folder = basic_param->video_folder; result_folder = basic_param->result_folder; result_folder_little = basic_param->result_folder_little;
  1651 + // 原图及抠图
  1652 + vpc_img_info src_img; src_img.pic_desc = result->origin_img_desc; src_img.task_id = obj_key.video_id;
  1653 + vpc_img_info roi_img; roi_img.pic_desc = result->roi_img_desc; roi_img.task_id = obj_key.video_id; roi_img.object_id = obj_key.obj_id;
  1654 +
  1655 + if (save_single_algor_pic) {
  1656 + auto json_str = helpers::gen_json::gen_manned_json(obj_key.video_id, obj_key.obj_id, result->box, algorithm_type_t::NONMOTOR_RUNNING_REDLIGHTS);
  1657 + save_snapshot_process(obj_key, algorithm_type_t::NONMOTOR_RUNNING_REDLIGHTS, src_img, roi_img, 0, json_str);
  1658 + } else {
  1659 + VPCUtil::vpc_img_release(src_img); VPCUtil::vpc_img_release(roi_img);
  1660 + }
  1661 +
  1662 + }
  1663 + }
  1664 +
  1665 + if (task_param_ptr->human_algors.find(algorithm_type_t::PERSON_RUNNING_REDLIGHTS) != task_param_ptr->human_algors.end()) {
  1666 + const auto &algor_other_params = task_other_params->find(algorithm_type_t::PERSON_RUNNING_REDLIGHTS);
  1667 + const algor_basic_config_param_t *basic_param = algor_other_params->second->basic_param;
  1668 +
  1669 + auto result = traffic_lightprocess_.get_result_by_objectid(ai_engine_module::obj_key_t{obj_key.obj_id, obj_key.video_id, algorithm_type_t::PERSON_RUNNING_REDLIGHTS});
  1670 + if (result.get()) {
  1671 + village_alarm = true;
  1672 + algorithm_types.push_back((int)algorithm_type_t::PERSON_RUNNING_REDLIGHTS);
  1673 + video_folder = basic_param->video_folder; result_folder = basic_param->result_folder; result_folder_little = basic_param->result_folder_little;
  1674 + // 原图及抠图
  1675 + vpc_img_info src_img; src_img.pic_desc = result->origin_img_desc; src_img.task_id = obj_key.video_id;
  1676 + vpc_img_info roi_img; roi_img.pic_desc = result->roi_img_desc; roi_img.task_id = obj_key.video_id; roi_img.object_id = obj_key.obj_id;
  1677 +
  1678 + if (save_single_algor_pic) {
  1679 + auto json_str = helpers::gen_json::gen_manned_json(obj_key.video_id, obj_key.obj_id, result->box, algorithm_type_t::PERSON_RUNNING_REDLIGHTS);
  1680 + save_snapshot_process(obj_key, algorithm_type_t::PERSON_RUNNING_REDLIGHTS, src_img, roi_img, 0, json_str);
  1681 + } else {
  1682 + VPCUtil::vpc_img_release(src_img); VPCUtil::vpc_img_release(roi_img);
1599 1683 }
1600 1684  
1601 1685 }
... ... @@ -1966,7 +2050,7 @@ bool CMultiSourceProcess::CheckTime() {
1966 2050 nYear = info->tm_year + 1900;
1967 2051 nMonth = info->tm_mon + 1;
1968 2052 nDay = info->tm_mday;
1969   - if ((nYear == 2023 && nMonth <= 9) || (nYear == 2023 && nMonth <= 10 && nDay <= 31))
  2053 + if ((nYear == 2023 && nMonth <= 10) || (nYear == 2023 && nMonth <= 11 && nDay <= 30))
1970 2054 {
1971 2055 return true;
1972 2056 }
... ...
src/ai_platform/MultiSourceProcess.h
  View file @fa81830
... ... @@ -12,16 +12,7 @@
12 12 #include "task_param_manager.h"
13 13 #include "../reprocessing_module/snapshot_reprocessing.h"
14 14 #include "../reprocessing_module/save_snapshot_reprocessing.h"
15   -#include "../ai_engine_module/VPTProcess.h"
16   -#include "../ai_engine_module/face_det_ai_engine.h"
17   -#include "../ai_engine_module/pedestrian_vehicle_retrograde.h"
18   -#include "../ai_engine_module/pedestrian_vehicle_trespass.h"
19   -#include "../ai_engine_module/tricycle_manned_process.h"
20   -#include "../ai_engine_module/truck_manned_process.h"
21   -#include "../ai_engine_module/motocycle_hs_process.h"
22   -#include "../ai_engine_module/motocycle_refit_phone_process.h"
23   -#include "../ai_engine_module/motocycle_phone_process.h"
24   -#include "../ai_engine_module/motocycle_refit_process.h"
  15 +#include "../ai_engine_module/ai_engine_module.h"
25 16 #include "../util/JpegUtil.h"
26 17 #include "atlas_licence.h"//授权文件
27 18  
... ... @@ -84,6 +75,8 @@ private:
84 75 void algorithm_motor_phone_process(vector<string>& vpt_interest_task_id, vector<DeviceMemory*> vpt_interest_imgs, vector<onelevel_det_result>& vptResult);
85 76 // 电动车改装(加雨棚)
86 77 void algorithm_motor_refit_process(vector<string>& vpt_interest_task_id, vector<DeviceMemory*> vpt_interest_imgs, vector<onelevel_det_result>& vptResult);
  78 + // 行人/二轮车闯红灯
  79 + void algorithm_traffic_light_process(vector<string>& vpt_interest_task_id, vector<DeviceMemory*> vpt_interest_imgs, vector<onelevel_det_result>& vptResult);
87 80  
88 81  
89 82 private:
... ... @@ -152,6 +145,7 @@ private:
152 145 ai_engine_module::motocycle_refit_phone_process::MotorRefitPhoneProcess motor_refit_phoneprocess_;
153 146 // ai_engine_module::motocycle_phone_process::MotorPhoneProcess motor_phoneprocess_;
154 147 ai_engine_module::motocycle_refit_process::MotorRefitProcess motor_refitprocess_;
  148 + ai_engine_module::traffic_light_process::TrafficLightProcess traffic_lightprocess_;
155 149  
156 150 face_det_ai_engine m_face_det_ai_engine; // 人脸检测
157 151  
... ...
src/ai_platform/header.h
  View file @fa81830
... ... @@ -46,7 +46,9 @@ enum class algorithm_type_t {
46 46 TRICYCLE_MANNED = 503, // 三轮车载人
47 47 TRUCK_MANNED = 504, // 货车货箱载人
48 48 NONMOTOR_VEHICLE_USEPHONE = 505,// 电动/摩托车驾乘人员使用手机
49   - NONMOTOR_VEHICLE_REFIT = 506, // 电动车改装(加雨棚)
  49 + NONMOTOR_VEHICLE_REFIT = 506, // 电动车改装(加雨棚)
  50 + PERSON_RUNNING_REDLIGHTS = 507, // 行人闯红灯
  51 + NONMOTOR_RUNNING_REDLIGHTS = 508, // 非机动车闯红灯
50 52 };
51 53  
52 54  
... ...
src/ai_platform/task_param_manager.cpp
  View file @fa81830
... ... @@ -58,9 +58,15 @@ bool copy_algor_param_aux(const algorithm_type_t &amp;algor_type, const std::string
58 58 case algorithm_type_t::NONMOTOR_VEHICLE_REFIT:
59 59 m_algor_config_params[task_id].nonmotor_vehicle_algors.insert(algor_type);
60 60 goto _manned_param_copy;
  61 + case algorithm_type_t::NONMOTOR_RUNNING_REDLIGHTS:
  62 + m_algor_config_params[task_id].nonmotor_vehicle_algors.insert(algor_type);
  63 + goto _manned_param_copy;
61 64 case algorithm_type_t::TRICYCLE_MANNED:
62 65 m_algor_config_params[task_id].nonmotor_vehicle_algors.insert(algor_type);
63 66 goto _manned_param_copy;
  67 + case algorithm_type_t::PERSON_RUNNING_REDLIGHTS:
  68 + m_algor_config_params[task_id].human_algors.insert(algor_type);
  69 + goto _manned_param_copy;
64 70 case algorithm_type_t::TRUCK_MANNED: {
65 71 m_algor_config_params[task_id].vehicle_algors.insert(algor_type);
66 72 _manned_param_copy : {
... ...
src/demo/Makefile
  View file @fa81830
... ... @@ -33,7 +33,7 @@ lib_dir=-L/usr/local/Ascend/ascend-toolkit/6.3.RC1/runtime/lib64 \
33 33 lib=-lacl_dvpp -lascendcl -lacl_dvpp_mpi -lruntime -lascendalog -lc_sec -lmsprofiler -lgert -lmmpa -lascend_hal -lexe_graph -lge_executor -lgraph -lprofapi -lascend_protobuf -lerror_manager -lhybrid_executor -lregister -ldavinci_executor -lge_common -lge_common_base \
34 34 -lplatform -lgraph_base -lqos_manager
35 35  
36   -LIBS= -L $(DEPEND_DIR) -lvpt_det_vdec -lsycheck -lface_det_vdec -lhs_tri_process -lhs_truck_process -lhs_motor_process -lphone_motor_det -lhcp_vdec -lmotor_rainshed_vdec -latlaslic -lvpt_ascend\
  36 +LIBS= -L $(DEPEND_DIR) -lvpt_det_vdec -lsycheck -lface_det_vdec -lhs_tri_process -lhs_truck_process -lhs_motor_process -lphone_motor_det -lhcp_vdec -lmotor_rainshed_vdec -ltraffic_light_vdec -latlaslic -lvpt_ascend\
37 37 -L $(OPENCV_ROOT)/lib -lopencv_world\
38 38 -L $(JSON_ROOT)/lib -ljsoncpp \
39 39 -L $(FFMPEG_ROOT)/lib -lavformat -lavcodec -lswscale -lavutil -lavfilter -lswresample -lavdevice \
... ...
src/demo/demo.cpp
  View file @fa81830
... ... @@ -223,6 +223,56 @@ void set_task_params(task_param &amp;tparam, const unsigned &amp;idx, const algorithm_ty
223 223 algor_init_params->basic_param = basic_params;
224 224 } break;
225 225  
  226 + case algorithm_type_t::PERSON_RUNNING_REDLIGHTS: {
  227 + auto algor_params = new algor_config_param_manned_incident;
  228 + {
  229 + algor_params->m = 10;
  230 + algor_params->n = 8;
  231 + algor_params->obj_confidence_threshold = 0.5f;
  232 + algor_params->obj_min_height = 6;
  233 + algor_params->obj_min_width = 32;
  234 + }
  235 +
  236 + auto basic_params = new algor_basic_config_param_t;
  237 + {
  238 + // basic_params->algor_valid_rect.top_ = 0;
  239 + // basic_params->algor_valid_rect.left_ = 0;
  240 + // basic_params->algor_valid_rect.width_ = 1920;
  241 + // basic_params->algor_valid_rect.height_ = 1080;
  242 + basic_params->video_folder = "res/video_recode";
  243 + basic_params->result_folder = "res/person_runred";
  244 + basic_params->result_folder_little = "res/person_runred_little";
  245 + }
  246 +
  247 + algor_init_params->algor_param = algor_params;
  248 + algor_init_params->basic_param = basic_params;
  249 + } break;
  250 +
  251 + case algorithm_type_t::NONMOTOR_RUNNING_REDLIGHTS: {
  252 + auto algor_params = new algor_config_param_manned_incident;
  253 + {
  254 + algor_params->m = 10;
  255 + algor_params->n = 8;
  256 + algor_params->obj_confidence_threshold = 0.5f;
  257 + algor_params->obj_min_height = 6;
  258 + algor_params->obj_min_width = 32;
  259 + }
  260 +
  261 + auto basic_params = new algor_basic_config_param_t;
  262 + {
  263 + // basic_params->algor_valid_rect.top_ = 0;
  264 + // basic_params->algor_valid_rect.left_ = 0;
  265 + // basic_params->algor_valid_rect.width_ = 1920;
  266 + // basic_params->algor_valid_rect.height_ = 1080;
  267 + basic_params->video_folder = "res/video_recode";
  268 + basic_params->result_folder = "res/motor_runred";
  269 + basic_params->result_folder_little = "res/motor_runred_little";
  270 + }
  271 +
  272 + algor_init_params->algor_param = algor_params;
  273 + algor_init_params->basic_param = basic_params;
  274 + } break;
  275 +
226 276 case algorithm_type_t::FACE_SNAPSHOT: {
227 277 auto basic_params = new algor_basic_config_param_t;
228 278 {
... ... @@ -721,7 +771,7 @@ string createTask(void *handle, std::vector&lt;algorithm_type_t&gt; algor_vec, int gi,
721 771 tparam.ipc_url = "/data/share/data/hczr1.mp4";
722 772 break;
723 773 case 8:
724   - tparam.ipc_url = "/opt/share/data/1-00000001d9.mp4";
  774 + tparam.ipc_url = "/data/share/data/燕高路口高点_CVR_2015-12-30_09-00-00_2015-12-30.mp4";
725 775 break;
726 776 case 9:
727 777 tparam.ipc_url = "/opt/share/data/1-00000002d55_h265.mp4";
... ... @@ -843,7 +893,7 @@ void test_gpu(int gpuID){
843 893  
844 894  
845 895 std::vector<algorithm_type_t> algor_vec2 = {algorithm_type_t::NONMOTOR_VEHICLE_NOHELMET, algorithm_type_t::NONMOTOR_VEHICLE_OVERMAN, algorithm_type_t::TRICYCLE_MANNED, algorithm_type_t::TRUCK_MANNED, algorithm_type_t::NONMOTOR_VEHICLE_USEPHONE,
846   - algorithm_type_t::NONMOTOR_VEHICLE_REFIT};
  896 + algorithm_type_t::NONMOTOR_VEHICLE_REFIT, algorithm_type_t::PERSON_RUNNING_REDLIGHTS, algorithm_type_t::NONMOTOR_RUNNING_REDLIGHTS};
847 897 std::vector<algorithm_type_t> algor_vec3 = {algorithm_type_t::FACE_SNAPSHOT};
848 898  
849 899 /*
... ... @@ -870,7 +920,7 @@ void test_gpu(int gpuID){
870 920 createTask(handle, algor_vec2, 5);
871 921 createTask(handle, algor_vec2, 6);
872 922 createTask(handle, algor_vec2, 7);
873   - // createTask(handle, algor_vec, 8);
  923 + createTask(handle, algor_vec2, 8);
874 924 // createTask(handle, algor_vec, 9);
875 925 // createTask(handle, algor_vec, 10);
876 926 // createTask(handle, algor_vec, 11);
... ...
src/tsl_aiplatform_jni/AiEngineNativeInterface.cpp
  View file @fa81830
... ... @@ -382,6 +382,8 @@ JNIEXPORT jint JNICALL Java_com_objecteye_nativeinterface_TSLAiEngineNativeInter
382 382 case algorithm_type_t::NONMOTOR_VEHICLE_OVERMAN:
383 383 case algorithm_type_t::NONMOTOR_VEHICLE_USEPHONE:
384 384 case algorithm_type_t::NONMOTOR_VEHICLE_REFIT:
  385 + case algorithm_type_t::NONMOTOR_RUNNING_REDLIGHTS:
  386 + case algorithm_type_t::PERSON_RUNNING_REDLIGHTS:
385 387 case algorithm_type_t::TRICYCLE_MANNED:
386 388 case algorithm_type_t::TRUCK_MANNED: {
387 389 jfieldID fid = env->GetFieldID(cls_AlgorConfigParam, "hs_threshold", "I");
... ...