Hu Chunming / vpt_ascend

Commit 29b64a886460151f1638251fe2eb09ae99a934ce

Authored by Hu Chunming
1 parent 9b4d4adf

添加行人逆行算法

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Showing 15 changed files with 1241 additions and 78 deletions
bin/libvpt_det.so
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src/ai_engine_module/ai_engine_header.h 0 → 100644
  View file @29b64a8
  1 +/*
  2 + * @Author: yangzilong
  3 + * @Date: 2021-12-01 15:14:02
  4 + * @Last Modified by: yangzilong
  5 + * @Last Modified time: Do not edit
  6 + * @Email: yangzilong@objecteye.com
  7 + * @Description:
  8 + */
  9 +
  10 +#pragma once
  11 +
  12 +#include <cmath>
  13 +#include <type_traits>
  14 +#include <string>
  15 +#include "../ai_platform/det_obj_header.h"
  16 +#include "../util/vpc_util.h"
  17 +#include "../ai_platform/common_header.h"
  18 +
  19 +namespace ai_engine_module {
  20 +template <typename T> T clip(const T &val, const T &min, const T &max) {
  21 + if (std::is_integral<T>::value)
  22 + return std::min(std::max(val, min), max);
  23 + return val;
  24 +}
  25 +
  26 +using obj_id_t = long;
  27 +using task_id_t = std::string;
  28 +
  29 +enum class direction_t {
  30 + NEGATIVE = 0,
  31 + POSITIVE = 1,
  32 +};
  33 +
  34 +struct unique_obj_id_t {
  35 + obj_id_t obj_id;
  36 + task_id_t task_id;
  37 +
  38 + bool operator<(const unique_obj_id_t &obj) const {
  39 + if (obj_id < obj.obj_id)
  40 + return true;
  41 +
  42 + else if (obj_id == obj.obj_id) {
  43 + if (strcmp(task_id.c_str(), obj.task_id.c_str()) < 0)
  44 + return true;
  45 + }
  46 + return false;
  47 + }
  48 +
  49 +};
  50 +
  51 +struct obj_key_t {
  52 + obj_id_t obj_id;
  53 + task_id_t task_id;
  54 + algorithm_type_t algor_type;
  55 +
  56 + bool operator<(const obj_key_t &obj) const {
  57 + if (obj_id < obj.obj_id)
  58 + return true;
  59 +
  60 + else if (obj_id == obj.obj_id) {
  61 + if (strcmp(task_id.c_str(), obj.task_id.c_str()) < 0)
  62 + return true;
  63 +
  64 + else if (strcmp(task_id.c_str(), obj.task_id.c_str()) == 0) {
  65 + if (static_cast<int>(algor_type) < static_cast<int>(obj.algor_type))
  66 + return true;
  67 + else
  68 + return false;
  69 + }
  70 + }
  71 + return false;
  72 + }
  73 +};
  74 +
  75 +struct trace_t {
  76 + box_t box;
  77 + point_t point;
  78 +};
  79 +
  80 +typedef struct result_data_t {
  81 + box_t box;
  82 + acldvppPicDesc* origin_img_desc{nullptr};
  83 + acldvppPicDesc* roi_img_desc{nullptr};
  84 +} result_data_t;
  85 +
  86 +} // namespace ai_engine_module
... ...
src/ai_engine_module/pedestrian_vehicle_retrograde.cpp 0 → 100644
  View file @29b64a8
  1 +/*
  2 + * File: pedestrian_vehicle_retrograde.cpp
  3 + * Created Date: Tuesday February 22nd 2022
  4 + * Author: yangzilong (yangzilong@objecteye.com)
  5 + * Description:
  6 + * -----
  7 + * Last Modified: Tuesday, 22nd February 2022 4:38:48 pm
  8 + * Modified By: yangzilong (yangzilong@objecteye.com>)
  9 + * -----
  10 + * Copyright 2022
  11 + */
  12 +
  13 +#include "./pedestrian_vehicle_retrograde.h"
  14 +#include <cmath>
  15 +#include "../decoder/interface/DeviceMemory.hpp"
  16 +#include "../common/logger.hpp"
  17 +#include "../ai_platform/mvpt_process_assist.h"
  18 +
  19 +namespace ai_engine_module {
  20 +namespace pedestrian_vehicle_retrograde {
  21 +
  22 +#define MAX_TRACE_NUM 5
  23 +#define MINIMUM_DISTANCE 10
  24 +
  25 +static std::set<algorithm_type_t> algor_type_list_ = {
  26 + algorithm_type_t::PEDESTRIAN_RETROGRADE,
  27 + algorithm_type_t::VEHICLE_RETROGRADE,
  28 +};
  29 +
  30 +std::set<det_class_label_t> algor_type_to_det_label_set(const algorithm_type_t &algor_type) {
  31 + if (algorithm_type_t::PEDESTRIAN_RETROGRADE == algor_type) {
  32 + return {det_class_label_t::HUMAN};
  33 + } else if (algorithm_type_t::VEHICLE_RETROGRADE == algor_type) {
  34 + return {
  35 + det_class_label_t::LARGE_CAR, det_class_label_t::MEDIUM_BUS, det_class_label_t::SMALL_CAR,
  36 + det_class_label_t::TRUCK, det_class_label_t::TRACTOR,
  37 +
  38 + // det_class_label_t::BICYCLE,
  39 + // det_class_label_t::MOTOCYCLE,
  40 + // det_class_label_t::TRICYCLE,
  41 + };
  42 + } else {
  43 + return {};
  44 + }
  45 +}
  46 +
  47 +bool is_valid_box(const int &cls, const algorithm_type_t &algor_type) {
  48 + return algor_type_to_det_label_set(algor_type).count(static_cast<det_class_label_t>(cls));
  49 +}
  50 +
  51 +bool is_valid_box(const box_t &box, const algorithm_type_t &algor_type,
  52 + const task_param_manager::algo_param_type_t_ *params_ptr = nullptr) {
  53 + if (!params_ptr)
  54 + return false;
  55 +
  56 + if (!snapshot_legal_inarea(params_ptr->basic_param->algor_valid_rect, box.left, box.top, box.right, box.bottom))
  57 + return false;
  58 +
  59 + if (params_ptr->algor_param == nullptr)
  60 + return false;
  61 +
  62 + if (box.width() == 0 || box.height() == 0)
  63 + return false;
  64 +
  65 + using data_t = algor_config_param_retrograde_basic;
  66 + data_t *algor_params_ptr = (data_t *)(params_ptr->algor_param);
  67 +
  68 + if (box.score < algor_params_ptr->conf_threshold || box.width() < algor_params_ptr->minmum_width ||
  69 + box.height() < algor_params_ptr->minmum_height)
  70 + return false;
  71 +
  72 + return is_valid_box(box.cls, algor_type);
  73 +}
  74 +
  75 +const task_param_manager::algo_param_type_t_ *get_task_param_ptr(const task_id_t &task_id,
  76 + const algorithm_type_t &algor_type,
  77 + task_param_manager *const task_param_manager) {
  78 + if (!task_param_manager)
  79 + return nullptr;
  80 +
  81 + auto &&algor_param_wrap = task_param_manager->get_task_other_param(task_id, algor_type);
  82 + if (!algor_param_wrap)
  83 + LOG_ERROR("{} is nullptr when get algor param from task_param", task_id);
  84 + return algor_param_wrap;
  85 +}
  86 +
  87 +std::vector<algorithm_type_t> task_id_to_algorithm_type_seq(const task_id_t &task_id,
  88 + task_param_manager *const task_param) {
  89 + std::vector<algorithm_type_t> seq;
  90 + auto &&algor_map = task_param->get_task_other_param(task_id);
  91 + for (auto iter = algor_map->begin(); iter != algor_map->end(); ++iter) {
  92 + // LOG_TRACE("task id is {} algor type is {}", task_id, int(iter->first));
  93 + if (algor_type_list_.count(iter->first) > 0)
  94 + seq.emplace_back(iter->first);
  95 + }
  96 + return seq; // N(RVO)
  97 +}
  98 +
  99 +// ############################################################ //
  100 +// ! Class Member ! //
  101 +// ############################################################ //
  102 +
  103 +PedestrianVehicleRetrograde::PedestrianVehicleRetrograde() : task_param_manager_(nullptr) {
  104 + if (!task_param_manager_)
  105 + task_param_manager_ = task_param_manager::getInstance();
  106 +}
  107 +
  108 +PedestrianVehicleRetrograde::~PedestrianVehicleRetrograde() = default;
  109 +
  110 +void PedestrianVehicleRetrograde::force_release_result(const task_id_t &task_id) {
  111 + for (auto iter = obj_to_alarm_boxes_.begin(); iter != obj_to_alarm_boxes_.end();) {
  112 + const auto &key = iter->first;
  113 + if (key.task_id == task_id) {
  114 + auto &values = iter->second;
  115 + for (auto &value : values) {
  116 +
  117 + if (value.roi_img_desc) {
  118 + VPCUtil::vpc_pic_desc_release(value.roi_img_desc);
  119 + }
  120 +
  121 + if (value.origin_img_desc) {
  122 + VPCUtil::vpc_pic_desc_release(value.origin_img_desc);
  123 + }
  124 + }
  125 + values.clear();
  126 + iter = obj_to_alarm_boxes_.erase(iter);
  127 + } else {
  128 + ++iter;
  129 + }
  130 + }
  131 + //-221024 byzsh删除存储的轨迹信息--------------------------------------------------
  132 + for (auto iter = obj_to_traces_.begin(); iter != obj_to_traces_.end();) {
  133 + const auto &key = iter->first;
  134 + if (key.task_id == task_id) {
  135 + auto &values = iter->second;
  136 + values.clear();
  137 + iter = obj_to_traces_.erase(iter);
  138 + } else {
  139 + ++iter;
  140 + }
  141 + }
  142 + //-------------------------------------------------------------------------
  143 +
  144 +
  145 +}
  146 +
  147 +vector<result_data_t> PedestrianVehicleRetrograde::get_results_by_id(const obj_key_t &id, bool do_erase) {
  148 + LOG_DEBUG("obj_to_alarm_boxes_ size:{}", obj_to_alarm_boxes_.size());
  149 +
  150 + vector<result_data_t> res;
  151 +
  152 + auto it = obj_to_alarm_boxes_.find(id);
  153 + if (it == obj_to_alarm_boxes_.end()) {
  154 + return res;
  155 + }
  156 +
  157 + res = it->second;
  158 + if (do_erase)
  159 + obj_to_alarm_boxes_.erase(id);
  160 +
  161 + if (obj_to_traces_.find(id) != obj_to_traces_.end()) {
  162 + obj_to_traces_.erase(id); //221009 !不删除会出现轨迹已消失但继续报警的情况，导致内存泄露
  163 + }
  164 +
  165 + return res;
  166 +}
  167 +
  168 +vector<obj_key_t> PedestrianVehicleRetrograde::retrograde_aux() {
  169 + /**
  170 + * @brief 使用box的历史轨迹点和当前轨迹点结合超参中的线段进行逻辑判断出是否逆行.
  171 + *
  172 + */
  173 + // LOG_TRACE("---> retrograde_aux called.");
  174 +
  175 + vector<obj_key_t> ret;
  176 + const unsigned minimum_boxes_num = MAX_TRACE_NUM - 1;
  177 + for (auto &obj_to_trace : obj_to_traces_) {
  178 +
  179 + auto &obj_key = obj_to_trace.first;
  180 + auto &task_id = obj_key.task_id;
  181 + auto &algor_type = obj_key.algor_type;
  182 + auto &&algor_type_seq = task_id_to_algorithm_type_seq(task_id, task_param_manager_);
  183 + // LOG_DEBUG("55555555555 {} {} {}", obj_key.task_id, obj_key.obj_id, obj_key.algor_type);
  184 + // LOG_TRACE("---> Ckpt-0");
  185 +
  186 + const task_param_manager::algo_param_type_t_ *param_ptr_wrap =
  187 + get_task_param_ptr(task_id, algor_type, task_param_manager_);
  188 + if (!param_ptr_wrap)
  189 + continue;
  190 +
  191 + using param_type_t = algor_config_param_retrograde_basic;
  192 + const param_type_t *param_ptr = (param_type_t *)(param_ptr_wrap->algor_param);
  193 +
  194 + // LOG_TRACE("---> Ckpt-1");
  195 +
  196 + auto &boxes = obj_to_trace.second;
  197 + const auto box_size = boxes.size();
  198 +
  199 + if (box_size < minimum_boxes_num)
  200 + continue;
  201 +
  202 + // LOG_TRACE("---> Ckpt-2");
  203 +
  204 + int point_x = boxes[box_size - minimum_boxes_num].cx();
  205 + const int point_y = boxes[box_size - minimum_boxes_num].cy();
  206 +
  207 + double k = 0.0, b = 0.0;
  208 + double dist_c = 0.0, dist_p = 0.0; // current point and prev(history) point.
  209 +
  210 + //! 使用超参中的点 连成的线水平还是垂直.
  211 + const bool is_horizontal_line = std::abs(int(param_ptr->px1 - param_ptr->px2)) >= 1;
  212 + if (is_horizontal_line) {
  213 + k = double(param_ptr->py1 - param_ptr->py2) / (param_ptr->px1 - param_ptr->px2);
  214 + b = double(param_ptr->px1 * param_ptr->py2 - param_ptr->px2 * param_ptr->py1) / (param_ptr->px1 - param_ptr->px2);
  215 +
  216 + dist_c = fabs(k * boxes[box_size - 1].cx() - boxes[box_size - 1].cy() + b) / sqrt(k * k + 1.0);
  217 + dist_p = fabs(k * point_x - point_y + b) / sqrt(k * k + 1.0);
  218 + } else {
  219 + k = 0.0;
  220 + b = double(param_ptr->px1);
  221 +
  222 + dist_c = fabs(boxes[box_size - 1].cx() - b);
  223 + dist_p = fabs(point_x - b);
  224 + }
  225 +
  226 + // 从历史轨迹点中找到当前点距离超过阈值的最小点.
  227 + bool flag = true;
  228 + if (abs(dist_c - dist_p) < MINIMUM_DISTANCE) {
  229 + flag = false;
  230 + int prev_idx = box_size - MAX_TRACE_NUM;
  231 + while (prev_idx >= 0) {
  232 + point_x = boxes[prev_idx].cx();
  233 + dist_p = is_horizontal_line ? fabs(k * point_x - point_y + b) / sqrt(k * k + 1.0) : fabs(point_x - b);
  234 + if (abs(dist_c - dist_p) >= MINIMUM_DISTANCE) {
  235 + flag = true;
  236 + break;
  237 + }
  238 + --prev_idx;
  239 + }
  240 + }
  241 +
  242 + // LOG_TRACE("---> Ckpt-10");
  243 +
  244 + if (!flag)
  245 + continue;
  246 +
  247 + // 当前轨迹点和历史轨迹点是否越线
  248 + bool flag_c = is_horizontal_line ? (k * boxes[box_size - 1].cx() + b >= boxes[box_size - 1].cy())
  249 + : (boxes[box_size - 1].cx() >= b);
  250 + bool flag_p = is_horizontal_line ? (k * point_x + b >= point_y) : (point_x >= b);
  251 +
  252 + /**
  253 + * PS. 拌线: 使用超参中的两点模拟的线段.
  254 + * 1. POSITIVE && is_horizontal_line: 方向点在拌线上方，正常方向为从下到上(↑)，越界方向为从上到下(↓)
  255 + * 2. NEGATIVE && is_horizontal_line: 方向点在拌线下方，正常方向为从上到下(↓)，越界方向为从下到上(↑)
  256 + * 3. POSITIVE && !is_horizontal_line: 方向点在拌线右边，正常方向为从左到右(→)，越界方向为从右到左(←)
  257 + * 4. NEGATIVE && !is_horizontal_line: 方向点在拌线左边，正常方向为从右到左(←)，越界方向为从左到右(→)
  258 + */
  259 + bool is_alarmed = false;
  260 + if (direction_t::POSITIVE == static_cast<direction_t>(param_ptr->direction)) {
  261 + if (flag_c * flag_p == 1) {
  262 + if (dist_c <= dist_p) {
  263 + is_alarmed = true;
  264 + }
  265 + } else if (flag_c == 0 && flag_p == 1) {
  266 + is_alarmed = true;
  267 + } else if (flag_c == 0 && flag_p == 0) {
  268 + if (dist_p <= dist_c) {
  269 + is_alarmed = true;
  270 + }
  271 + }
  272 + } else {
  273 + if (flag_c == 0 && flag_p == 0) {
  274 + if (dist_c <= dist_p) {
  275 + is_alarmed = true;
  276 + }
  277 + } else if (flag_c == 1 && flag_p == 0) {
  278 + is_alarmed = true;
  279 + } else if (flag_c == 1 && flag_p == 1) {
  280 + if (dist_p <= dist_c) {
  281 + is_alarmed = true;
  282 + }
  283 + }
  284 + }
  285 +
  286 + if (is_alarmed) {
  287 + ret.emplace_back(obj_key);
  288 + }
  289 + }
  290 + return ret;
  291 +}
  292 +
  293 +bool PedestrianVehicleRetrograde::update_mstreams(const std::vector<task_id_t> &tasks_id, vector<DeviceMemory*> vec_det_input_images,
  294 + const std::vector<onelevel_det_result> &det_results) {
  295 + //! check.
  296 + if (tasks_id.empty() || tasks_id.size() != det_results.size())
  297 + return false;
  298 +
  299 + //! loop.
  300 + unsigned stream_idx = 0;
  301 + std::map<task_id_t, unsigned> task_id_to_stream_idx;
  302 + for (auto task_id_iter = tasks_id.begin(); task_id_iter != tasks_id.end(); ++task_id_iter, ++stream_idx) {
  303 + auto task_id = *task_id_iter;
  304 + task_id_to_stream_idx[task_id] = stream_idx;
  305 + auto &&algor_type_seq = task_id_to_algorithm_type_seq(task_id, task_param_manager_);
  306 + if (algor_type_seq.empty())
  307 + continue;
  308 +
  309 + auto &det_result = det_results[stream_idx];
  310 + for (unsigned box_idx = 0; box_idx < det_result.obj_count; ++box_idx) {
  311 + auto &box = det_result.obj[box_idx];
  312 + // LOG_DEBUG("333333333333 {} {}", task_id, box.id);
  313 + box_t unique_box;
  314 + {
  315 + unique_box.id = box.id;
  316 + unique_box.cls = box.index;
  317 +
  318 + unique_box.top = box.top;
  319 + unique_box.left = box.left;
  320 + unique_box.right = box.right;
  321 + unique_box.bottom = box.bottom;
  322 + unique_box.score = box.confidence;
  323 + }
  324 +
  325 + //! loop algor
  326 + for (auto algor_type : algor_type_seq) {
  327 + obj_key_t obj_key{box.id, task_id, algor_type};
  328 + if (!is_valid_box(unique_box, algor_type, get_task_param_ptr(task_id, algor_type, task_param_manager_)))
  329 + continue;
  330 +
  331 + if (obj_to_traces_.find(obj_key) == obj_to_traces_.end()) {
  332 + obj_to_traces_[obj_key].emplace_back(std::move(unique_box));
  333 + } else {
  334 + auto &traces = obj_to_traces_[obj_key];
  335 + traces.emplace_back(std::move(unique_box));
  336 + if (traces.size() > MAX_TRACE_NUM)
  337 + traces.pop_front();
  338 + }
  339 + }
  340 + }
  341 + }
  342 +
  343 + vector<obj_key_t> &&alarm_objs = retrograde_aux(); // 右值引用
  344 +
  345 + VPCUtil* pVpcUtil = VPCUtil::getInstance();
  346 +
  347 + for (const auto &obj_key : alarm_objs) {
  348 + auto &traces = obj_to_traces_[obj_key];
  349 +
  350 + if (traces.empty())
  351 + continue;
  352 +
  353 + if (obj_to_alarm_boxes_.find(obj_key) != obj_to_alarm_boxes_.end() && obj_to_alarm_boxes_[obj_key].size() >= 10)
  354 + continue;
  355 +
  356 + auto &trace = traces.at(0);
  357 + auto &&it = task_id_to_stream_idx.find(obj_key.task_id);
  358 + if (it == task_id_to_stream_idx.end())
  359 + continue;
  360 +
  361 + const unsigned stream_idx = it->second;
  362 + auto &src_img = vec_det_input_images[stream_idx];
  363 +
  364 + result_data_t result_data;
  365 + result_data.box = trace;
  366 +
  367 + // 原图
  368 + vpc_img_info src_img_info = VPCUtil::vpc_devMem2vpcImg(src_img);
  369 + result_data.origin_img_desc = src_img_info.pic_desc;
  370 +
  371 + // 抠图
  372 + int width = src_img->getWidth();
  373 + int height = src_img->getHeight();
  374 + video_object_info obj;
  375 + strcpy(obj.task_id, obj_key.task_id.c_str());
  376 + obj.object_id = obj_key.obj_id;
  377 + obj.left = clip(trace.left, 0, width);
  378 + obj.top = clip(trace.top, 0, height);
  379 + obj.right = clip(trace.right, 0, width);
  380 + obj.bottom = clip(trace.bottom, 0, height);
  381 +
  382 + vpc_img_info img_info = pVpcUtil->crop(src_img, obj);
  383 + result_data.roi_img_desc = img_info.pic_desc;
  384 +
  385 + // 保存结果
  386 + obj_to_alarm_boxes_[obj_key].emplace_back(std::move(result_data));
  387 + }
  388 +
  389 + LOG_DEBUG("obj_to_alarm_boxes_ size: {}", obj_to_alarm_boxes_.size());
  390 +
  391 + return true;
  392 +}
  393 +
  394 +} // namespace pedestrian_vehicle_retrograde
  395 +} // namespace ai_engine_module
... ...
src/ai_engine_module/pedestrian_vehicle_retrograde.h 0 → 100644
  View file @29b64a8
  1 +/*
  2 + * File: pedestrian_vehicle_retrograde.hpp
  3 + * Created Date: Tuesday February 22nd 2022
  4 + * Author: yangzilong (yangzilong@objecteye.com)
  5 + * Description:
  6 + * -----
  7 + * Last Modified: Tuesday, 22nd February 2022 4:35:04 pm
  8 + * Modified By: yangzilong (yangzilong@objecteye.com>)
  9 + * -----
  10 + * Copyright 2022
  11 + */
  12 +
  13 +#pragma once
  14 +
  15 +#include <deque>
  16 +#include <map>
  17 +#include <vector>
  18 +#include "../util/vpc_util.h"
  19 +#include "../ai_platform/task_param_manager.h"
  20 +#include "ai_engine_header.h"
  21 +
  22 +class DeviceMemory;
  23 +
  24 +namespace ai_engine_module {
  25 +namespace pedestrian_vehicle_retrograde {
  26 +
  27 +
  28 +class PedestrianVehicleRetrograde {
  29 + /**
  30 + * @brief
  31 + * 1. move able
  32 + */
  33 +public:
  34 + PedestrianVehicleRetrograde();
  35 +
  36 + ~PedestrianVehicleRetrograde();
  37 +
  38 + bool update_mstreams(const std::vector<task_id_t> &tasks_id, vector<DeviceMemory*> vec_det_input_images,
  39 + const std::vector<onelevel_det_result> &det_result);
  40 +
  41 + vector<result_data_t> get_results_by_id(const obj_key_t &id, bool do_erase = true);
  42 +
  43 + void force_release_result(const task_id_t &task_id);
  44 +
  45 + PedestrianVehicleRetrograde(const PedestrianVehicleRetrograde &) = delete;
  46 + PedestrianVehicleRetrograde &operator=(const PedestrianVehicleRetrograde &) = delete;
  47 +
  48 + PedestrianVehicleRetrograde(PedestrianVehicleRetrograde &&) = default;
  49 + PedestrianVehicleRetrograde &operator=(PedestrianVehicleRetrograde &&) = default;
  50 +
  51 +private:
  52 + vector<obj_key_t> retrograde_aux();
  53 +
  54 + task_param_manager *task_param_manager_;
  55 + std::map<obj_key_t, vector<result_data_t> > obj_to_alarm_boxes_;
  56 + std::map<obj_key_t, std::deque<box_t>> obj_to_traces_;
  57 +};
  58 +} // namespace pedestrian_vehicle_retrograde
  59 +} // namespace ai_engine_module
... ...
src/ai_engine_module/pedestrian_vehicle_trespass.cpp 0 → 100644
  View file @29b64a8
  1 +/*
  2 + * File: pedestrian_vehicle_trespass.cpp
  3 + * Created Date: Tuesday February 22nd 2022
  4 + * Author: yangzilong (yangzilong@objecteye.com)
  5 + * Description:
  6 + * -----
  7 + * Last Modified: Tuesday, 22nd February 2022 4:38:48 pm
  8 + * Modified By: yangzilong (yangzilong@objecteye.com>)
  9 + * -----
  10 + * Copyright 2022
  11 + */
  12 +
  13 +#include "./pedestrian_vehicle_trespass.h"
  14 +#include "opencv2/imgproc/imgproc.hpp"
  15 +#include "opencv2/opencv.hpp"
  16 +#include <cmath>
  17 +#include "../decoder/interface/DeviceMemory.hpp"
  18 +#include "../common/logger.hpp"
  19 +#include "../ai_platform/mvpt_process_assist.h"
  20 +
  21 +
  22 +namespace ai_engine_module {
  23 +namespace pedestrian_vehicle_trespass {
  24 +
  25 +#define MAX_TRACE_NUM 5
  26 +#define MINIMUM_DISTANCE 10
  27 +
  28 +static std::set<algorithm_type_t> algor_type_list_ = {
  29 + algorithm_type_t::PEDESTRIAN_TRESPASS,
  30 + algorithm_type_t::VEHICLE_TRESPASS,
  31 +};
  32 +
  33 +// void show_algorthim_result(sy_img img, box_t cur_box, const obj_key_t &key);
  34 +// ############################################################ //
  35 +// ! Auxiliary Function ! //
  36 +// ############################################################ //
  37 +
  38 +std::set<det_class_label_t> algor_type_to_det_label_set(const algorithm_type_t &algor_type) {
  39 + if (algorithm_type_t::PEDESTRIAN_TRESPASS == algor_type) {
  40 + return {det_class_label_t::HUMAN};
  41 + } else if (algorithm_type_t::VEHICLE_TRESPASS == algor_type) {
  42 + return {
  43 + det_class_label_t::LARGE_CAR, det_class_label_t::MEDIUM_BUS, det_class_label_t::SMALL_CAR,
  44 + det_class_label_t::TRUCK, det_class_label_t::TRACTOR,
  45 + };
  46 + } else {
  47 + return {};
  48 + }
  49 +}
  50 +
  51 +/* 是否是有效目标框的辅助判断函数 */
  52 +bool is_valid_box(const int &cls, const algorithm_type_t &algor_type) {
  53 + return algor_type_to_det_label_set(algor_type).count(static_cast<det_class_label_t>(cls));
  54 +}
  55 +
  56 +bool is_valid_box(const box_t &box, const algorithm_type_t &algor_type,
  57 + const task_param_manager::algo_param_type_t_ *params_ptr = nullptr) {
  58 + if (!params_ptr)
  59 + return false;
  60 +
  61 + if (!snapshot_legal_inarea(params_ptr->basic_param->algor_valid_rect, box.left, box.top, box.right, box.bottom))
  62 + return false;
  63 +
  64 + if (params_ptr->algor_param == nullptr)
  65 + return false;
  66 +
  67 + if (box.width() == 0 || box.height() == 0)
  68 + return false;
  69 +
  70 + using data_t = algor_config_param_trespass_basic;
  71 + auto *algor_params_ptr = (data_t *)(params_ptr->algor_param);
  72 +
  73 + if (box.score < algor_params_ptr->conf_threshold || box.width() < algor_params_ptr->minmum_width ||
  74 + box.height() < algor_params_ptr->minmum_height)
  75 + return false;
  76 +
  77 + return is_valid_box(box.cls, algor_type);
  78 +}
  79 +
  80 +/* 获取指定任务的算法配置参数 */
  81 +const task_param_manager::algo_param_type_t_ *get_task_param_ptr(const task_id_t &task_id,
  82 + const algorithm_type_t &algor_type,
  83 + task_param_manager *const task_param_manager) {
  84 + if (!task_param_manager)
  85 + return nullptr;
  86 +
  87 + auto &&algor_param_wrap = task_param_manager->get_task_other_param(task_id, algor_type);
  88 + if (!algor_param_wrap)
  89 + LOG_ERROR("{} is nullptr when get algor param from task_param", task_id);
  90 + return algor_param_wrap;
  91 +}
  92 +
  93 +/* 按照目标任务 检索指定任务的算法配置列表 */
  94 +std::vector<algorithm_type_t> task_id_to_algorithm_type_seq(const task_id_t &task_id,
  95 + task_param_manager *const task_param) {
  96 + std::vector<algorithm_type_t> seq;
  97 + auto &&algor_map = task_param->get_task_other_param(task_id);
  98 + for (auto iter = algor_map->begin(); iter != algor_map->end(); ++iter) {
  99 + // LOG_TRACE("task id is {} algor type is {}", task_id, int(iter->first));
  100 + if (algor_type_list_.count(iter->first) > 0)
  101 + seq.emplace_back(iter->first);
  102 + }
  103 + return seq; // N(RVO)
  104 +}
  105 +
  106 +// ############################################################ //
  107 +// ! Class Member ! //
  108 +// ############################################################ //
  109 +
  110 +PedestrianVehicleTrespass::PedestrianVehicleTrespass() : task_param_manager_(nullptr) {
  111 + if (!task_param_manager_)
  112 + task_param_manager_ = task_param_manager::getInstance();
  113 +}
  114 +
  115 +PedestrianVehicleTrespass::~PedestrianVehicleTrespass() = default;
  116 +
  117 +/* 根据目标id 获取该目标的算法分析结果 */
  118 +vector<result_data_t> PedestrianVehicleTrespass::get_results_by_id(const obj_key_t &id, bool do_erase) {
  119 +
  120 + vector<result_data_t> res;
  121 + auto it = obj_to_alarm_boxes_.find(id);
  122 + if (it == obj_to_alarm_boxes_.end()) {
  123 + // printf("cant find %s\n", id.task_id.c_str());
  124 + return res;
  125 + }
  126 +
  127 + res = it->second;
  128 + if (do_erase)
  129 + obj_to_alarm_boxes_.erase(id);
  130 +
  131 + return res;
  132 +}
  133 +
  134 +/* 目标在禁区内外的辅助判断函数 */
  135 +bool PedestrianVehicleTrespass::in_rect_analysis(const obj_key_t &id, const box_t &cur_bos) {
  136 + int center_x = int((cur_bos.left + cur_bos.right) / 2.0);
  137 + int center_y = int((cur_bos.top + cur_bos.bottom) / 2.0);
  138 +
  139 + obj_key_t tmp_id = {0, id.task_id, id.algor_type};
  140 + cv::Mat &dst_mat = trespass_regions[tmp_id];
  141 + // printf("id=%d center: %d %d ", id.obj_id, center_x, center_y);
  142 + if (dst_mat.data[center_y * dst_mat.cols + center_x] && dst_mat.data[center_y * dst_mat.cols + center_x + 1] &&
  143 + dst_mat.data[center_y * dst_mat.cols + center_x - 1] && dst_mat.data[(center_y + 1) * dst_mat.cols + center_x] &&
  144 + dst_mat.data[(center_y - 1) * dst_mat.cols + center_x]) {
  145 + // printf(" true\n");
  146 + return true; // 进入禁区
  147 + } else {
  148 + // printf(" false\n");
  149 + return false; // 未进入禁区
  150 + }
  151 +}
  152 +
  153 +/* 根据用户输入的点 初始化禁区区域mask */
  154 +void PedestrianVehicleTrespass::pedestrianvehicletrespass_init_region(const string &task_id,
  155 + const algorithm_type_t algor_type,
  156 + const int width, const int height) {
  157 + obj_key_t obj_key = {0, task_id, algor_type};
  158 +
  159 + auto &&algor_type_seq = task_id_to_algorithm_type_seq(task_id, task_param_manager_);
  160 +
  161 + const task_param_manager::algo_param_type_t_ *param_ptr_wrap =
  162 + get_task_param_ptr(task_id, algor_type, task_param_manager_);
  163 + if (!param_ptr_wrap) {
  164 + printf("cant find %s algorthim params\n", task_id.c_str());
  165 + return;
  166 + }
  167 +
  168 + using param_type_t = algor_config_param_trespass_basic;
  169 + const param_type_t *param_ptr = (param_type_t *)(param_ptr_wrap->algor_param);
  170 +
  171 + cv::Mat src(height, width, CV_8UC3);
  172 + src.setTo(0);
  173 +
  174 + std::vector<cv::Point> contour;
  175 + contour.reserve(param_ptr->points_count);
  176 + // printf("region points count: %d\n", param_ptr->points_count);
  177 + for (int idx = 0; idx < param_ptr->points_count; idx++) {
  178 + contour.emplace_back(param_ptr->points[idx].x_, param_ptr->points[idx].y_);
  179 + // printf(" =point:%d x:%d y:%d\n", idx, param_ptr->points[idx].x_, param_ptr->points[idx].y_);
  180 + }
  181 +
  182 + std::vector<std::vector<cv::Point>> contours;
  183 + contours.push_back(contour);
  184 +
  185 + cv::polylines(src, contours, true, cv::Scalar(255, 255, 255), 2, 8); // 第2个参数可以采用contour或者contours，均可
  186 + cv::fillPoly(src, contours, cv::Scalar(255, 255, 255)); // fillPoly函数的第二个参数是二维数组
  187 +
  188 + cv::Mat &dst_mat = trespass_regions[obj_key];
  189 + cv::cvtColor(src, trespass_regions[obj_key], cv::COLOR_BGR2GRAY);
  190 + cv::threshold(trespass_regions[obj_key], trespass_regions[obj_key], 100, 255, cv::THRESH_BINARY);
  191 +
  192 + if (false) {
  193 + cv::imwrite("ori.jpg", src);
  194 + cv::imwrite("region.jpg", trespass_regions[obj_key]);
  195 + }
  196 +}
  197 +
  198 +/* 非法闯入禁区的 算法判断函数 */
  199 +bool PedestrianVehicleTrespass::update_mstreams(const std::vector<task_id_t> &tasks_id, vector<DeviceMemory*> det_input_images,
  200 + const std::vector<onelevel_det_result> &det_results,
  201 + const vector<vector<int>> &delete_objs) {
  202 + //! check.
  203 + if (tasks_id.empty() || tasks_id.size() != det_results.size())
  204 + return false;
  205 +
  206 + vector<obj_key_t> alarm_objs;
  207 + //! loop.
  208 + unsigned stream_idx = 0U;
  209 + std::map<task_id_t, unsigned> task_id_to_stream_idx;
  210 + for (auto task_id_iter = tasks_id.begin(); task_id_iter != tasks_id.end(); ++task_id_iter, ++stream_idx) {
  211 + const auto &task_id = *task_id_iter;
  212 + task_id_to_stream_idx[task_id] = stream_idx;
  213 + // printf("\nbegin judge: %s\n", task_id.c_str());
  214 +
  215 + /* 判断该路任务 是否开启该算法 */
  216 + auto &&algor_type_seq = task_id_to_algorithm_type_seq(task_id, task_param_manager_);
  217 + if (algor_type_seq.empty())
  218 + continue;
  219 +
  220 + // 删除 已经删除的目标
  221 + for (auto obj_idx : delete_objs[stream_idx]) {
  222 + for (auto algor_type : algor_type_seq) {
  223 + obj_key_t obj_key{obj_idx, task_id, algor_type};
  224 +
  225 + if (obj_to_position_.find(obj_key) != obj_to_position_.end()) {
  226 + // printf("delete obj: %s %d\n", task_id.c_str(), obj_idx);
  227 + obj_to_position_.erase(obj_key);
  228 + }
  229 + }
  230 +
  231 + // delete obj
  232 + }
  233 +
  234 + /* 依次判断检测目标框 是否有非法闯入 判断逻辑：之前帧在禁区外 当前帧进入禁区 */
  235 + auto &det_result = det_results[stream_idx];
  236 + // printf("det count: %d\n", det_result.obj_count);
  237 + for (unsigned box_idx = 0; box_idx < det_result.obj_count; ++box_idx) {
  238 + auto &box = det_result.obj[box_idx];
  239 +
  240 + box_t unique_box{};
  241 + {
  242 + unique_box.id = box.id;
  243 + unique_box.cls = box.index;
  244 +
  245 + unique_box.top = box.top;
  246 + unique_box.left = box.left;
  247 + unique_box.right = box.right;
  248 + unique_box.bottom = box.bottom;
  249 + unique_box.score = box.confidence;
  250 + }
  251 +
  252 + //! loop algor
  253 + for (auto algor_type : algor_type_seq) {
  254 + obj_key_t obj_key{box.id, task_id, algor_type};
  255 +
  256 + if (!is_valid_box(unique_box, algor_type, get_task_param_ptr(task_id, algor_type, task_param_manager_)))
  257 + obj_to_position_.erase(obj_key); // 如果不满足条件 非 合法框 依然删除
  258 +
  259 + //! add or update.
  260 + if (!in_rect_analysis(obj_key, unique_box)) // 禁区外
  261 + {
  262 + // printf("push in: %s %d\n", task_id.c_str(), box.id);
  263 + obj_to_position_[obj_key] = unique_box;
  264 + }
  265 +
  266 + else { // 进入禁区
  267 + if (obj_to_position_.find(obj_key) != obj_to_position_.end()) // 之前在禁区外，可报警
  268 + {
  269 + obj_to_position_[obj_key] = unique_box;
  270 +
  271 + alarm_objs.emplace_back(obj_key);
  272 + }
  273 +
  274 + }
  275 + }
  276 + }
  277 + }
  278 +
  279 + /* 针对需要报警的目标 缓存当前大图&抠图 等待报警返回 */
  280 + VPCUtil* pVpcUtil = VPCUtil::getInstance();
  281 + for (const auto &obj_key : alarm_objs) {
  282 + auto &&it = task_id_to_stream_idx.find(obj_key.task_id);
  283 + if (it == task_id_to_stream_idx.end())
  284 + continue;
  285 +
  286 + // 221009 byzsh记录10条即可--------------------------------------------------------------------------------------
  287 + if (obj_to_alarm_boxes_.find(obj_key) != obj_to_alarm_boxes_.end() && obj_to_alarm_boxes_[obj_key].size() >= 10)
  288 + continue;
  289 + //--------------------------------------------------------------------------------------------------------------
  290 + const unsigned stream_idx = it->second;
  291 + auto &src_img = det_input_images[stream_idx];
  292 +
  293 + result_data_t result_data;
  294 + result_data.box = obj_to_position_[obj_key];
  295 +
  296 + // 原图
  297 + vpc_img_info src_img_info = VPCUtil::vpc_devMem2vpcImg(src_img);
  298 + result_data.origin_img_desc = src_img_info.pic_desc;
  299 +
  300 + // 抠图
  301 + int width = src_img->getWidth();
  302 + int height = src_img->getHeight();
  303 + video_object_info obj;
  304 + strcpy(obj.task_id, obj_key.task_id.c_str());
  305 + // obj.task_id = obj_key.task_id.c_str();
  306 + obj.object_id = obj_key.obj_id;
  307 + obj.left = clip(result_data.box.left, 0, width);
  308 + obj.top = clip(result_data.box.top, 0, height);
  309 + obj.right = clip(result_data.box.right, 0, width);
  310 + obj.bottom = clip(result_data.box.bottom, 0, height);
  311 +
  312 + vpc_img_info img_info = pVpcUtil->crop(src_img, obj);
  313 + result_data.roi_img_desc = img_info.pic_desc;
  314 +
  315 + obj_to_alarm_boxes_[obj_key].emplace_back(std::move(result_data));
  316 + obj_to_position_.erase(obj_key);
  317 + }
  318 +
  319 + return true;
  320 +}
  321 +
  322 +/* 辅助函数 显示算法结果 */
  323 +// void show_algorthim_result(sy_img img, box_t cur_box, const obj_key_t &key) {
  324 +// const unsigned size = img.c_ * img.h_ * img.w_;
  325 +// auto *img_data = new unsigned char[size];
  326 +
  327 +// CHECK(cudaMemcpy(img_data, img.data_, size * sizeof(unsigned char), cudaMemcpyDeviceToHost));
  328 +// cv::Mat show_image(img.h_, img.w_, CV_8UC3, img_data);
  329 +
  330 +// std::vector<cv::Point> contour;
  331 +// /*
  332 +// contour.push_back(cv::Point(200, 200));
  333 +// contour.push_back(cv::Point(600, 200));
  334 +// contour.push_back(cv::Point(600, 500));
  335 +// contour.push_back(cv::Point(200, 500));
  336 +// */
  337 +// contour.emplace_back(500, 500);
  338 +// contour.emplace_back(1500, 500);
  339 +// contour.emplace_back(1500, 900);
  340 +// contour.emplace_back(500, 900);
  341 +
  342 +// std::vector<std::vector<cv::Point>> contours;
  343 +// contours.push_back(contour);
  344 +
  345 +// cv::polylines(show_image, contours, true, cv::Scalar(255, 255, 255), 2,
  346 +// 8); // 第2个参数可以采用contour或者contours，均可
  347 +
  348 +// cv::rectangle(show_image, cv::Point(cur_box.left, cur_box.top), cv::Point(cur_box.right, cur_box.bottom),
  349 +// cv::Scalar(0, 250, 0), 2, 8);
  350 +
  351 +// char filename[256];
  352 +// sprintf(filename, "res_image/%s_%ld.jpg", key.task_id.c_str(), key.obj_id);
  353 +// cv::imwrite(filename, show_image);
  354 +// printf("\n *****ERROR finish save %s %ld\n", key.task_id.c_str(), key.obj_id);
  355 +// }
  356 +
  357 +} // namespace pedestrian_vehicle_trespass
  358 +} // namespace ai_engine_module
... ...
src/ai_engine_module/pedestrian_vehicle_trespass.h 0 → 100644
  View file @29b64a8
  1 +/*
  2 + * File: pedestrian_vehicle_trespass.hpp
  3 + * Created Date: Tuesday February 22nd 2022
  4 + * Author: yangzilong (yangzilong@objecteye.com)
  5 + * Description:
  6 + * -----
  7 + * Last Modified: Tuesday, 22nd February 2022 4:35:04 pm
  8 + * Modified By: yangzilong (yangzilong@objecteye.com>)
  9 + * -----
  10 + * Copyright 2022
  11 + */
  12 +
  13 +#pragma once
  14 +#include "opencv2/highgui/highgui.hpp"
  15 +#include <deque>
  16 +#include <map>
  17 +#include <vector>
  18 +#include "../util/vpc_util.h"
  19 +#include "../ai_platform/task_param_manager.h"
  20 +#include "ai_engine_header.h"
  21 +
  22 +class DeviceMemory;
  23 +
  24 +namespace ai_engine_module {
  25 +namespace pedestrian_vehicle_trespass {
  26 +
  27 +class PedestrianVehicleTrespass {
  28 + /**
  29 + * @brief
  30 + * 1. move able
  31 + */
  32 +public:
  33 + PedestrianVehicleTrespass();
  34 +
  35 + ~PedestrianVehicleTrespass();
  36 +
  37 + void pedestrianvehicletrespass_init_region(const string &task_id, const algorithm_type_t algor_type, const int width,
  38 + const int height);
  39 +
  40 + bool update_mstreams(const std::vector<task_id_t> &tasks_id, vector<DeviceMemory*> det_input_images,
  41 + const std::vector<onelevel_det_result> &det_result, const vector<vector<int>> &delete_objs);
  42 +
  43 + vector<result_data_t> get_results_by_id(const obj_key_t &id, bool do_erase = true);
  44 +
  45 + PedestrianVehicleTrespass(const PedestrianVehicleTrespass &) = delete;
  46 + PedestrianVehicleTrespass &operator=(const PedestrianVehicleTrespass &) = delete;
  47 +
  48 + PedestrianVehicleTrespass(PedestrianVehicleTrespass &&) = default;
  49 + PedestrianVehicleTrespass &operator=(PedestrianVehicleTrespass &&) = default;
  50 +
  51 +private:
  52 + bool in_rect_analysis(const obj_key_t &id, const box_t &cur_bos);
  53 +
  54 + task_param_manager *task_param_manager_;
  55 + std::map<obj_key_t, vector<result_data_t> > obj_to_alarm_boxes_;
  56 + std::map<obj_key_t, box_t> obj_to_position_; // 保存物体上一帧的位置，基于非法闯入判断逻辑，上一帧在框外，下一帧闯入禁区
  57 + std::map<obj_key_t, cv::Mat> trespass_regions;
  58 +};
  59 +} // namespace pedestrian_vehicle_trespass
  60 +} // namespace ai_engine_module
... ...
src/ai_platform/MultiSourceProcess.cpp
  View file @29b64a8
... ... @@ -17,6 +17,8 @@
17 17 #include "macro_definition.h"
18 18 #include "SourceSingleton.hpp"
19 19  
  20 +#include "../util/vpc_util.h"
  21 +
20 22 // #define VEHICLE_MULTI_BOXES
21 23  
22 24 using namespace std;
... ... @@ -72,7 +74,6 @@ CMultiSourceProcess::CMultiSourceProcess(){
72 74 }
73 75  
74 76 CMultiSourceProcess::~CMultiSourceProcess(){
75   - vpc_util.release();
76 77 }
77 78  
78 79 int CMultiSourceProcess::InitAlgorthim(tsl_aiplatform_param vptParam){
... ... @@ -103,7 +104,8 @@ int CMultiSourceProcess::InitAlgorthim(tsl_aiplatform_param vptParam){
103 104 m_snapshot_reprocessing = new snapshot_reprocessing(m_devId);
104 105 m_save_snapshot_reprocessing = new save_snapshot_reprocessing(m_devId);
105 106  
106   - vpc_util.init(m_devId);
  107 + VPCUtil* pVpcUtil = VPCUtil::getInstance();
  108 + pVpcUtil->init(m_devId);
107 109  
108 110 m_pAlgorthimThread = new thread([](void* arg) {
109 111 CMultiSourceProcess* process = (CMultiSourceProcess*)arg ;
... ... @@ -499,23 +501,32 @@ int CMultiSourceProcess::algorthim_vpt(vector&lt;DeviceMemory*&gt; vec_gpuMem){
499 501 /* 一级检测器，内部已完成跟踪操作 */
500 502 vpt_process.process_gpu(vpt_interest_imgs.data(), vpt_interest_task_id, vptResult, deleteObjectID, unUsedResult); // do det & track.
501 503  
502   -// m_snapshot_reprocessing->screen_effective_snapshot(vptResult);
  504 + m_snapshot_reprocessing->screen_effective_snapshot(vptResult);
  505 +
  506 +#ifndef VEHICLE_MULTI_BOXES
  507 + /* 快照优选（内部可实现不同的快照优选策略） */
  508 + m_snapshot_reprocessing->update_bestsnapshot(vec_vptMem, vptResult, deleteObjectID);
  509 +
  510 + /* 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）*/
  511 + vehicle_snapshot(vpt_interest_task_id, deleteObjectID);
  512 +#else
  513 + algorithm_vehicle_relult(vec_vptMem, vptResult, deleteObjectID);
  514 +
  515 + send_locus_finished_msg(vpt_interest_task_id, deleteObjectID);
  516 +#endif
503 517  
504   -// #ifndef VEHICLE_MULTI_BOXES
505   -// /* 快照优选（内部可实现不同的快照优选策略） */
506   -// m_snapshot_reprocessing->update_bestsnapshot(vec_vptMem, vptResult, deleteObjectID);
  518 +// #ifdef WITH_SECOND_PROCESS
  519 + /* for pedestrian safety det. 行人安全分析算法模块 */
  520 + // algorthim_pedestrian_safety(vpt_interest_task_id, vpt_interest_imgs,vptResult);
507 521  
508   -// /* 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）*/
509   -// vehicle_snapshot(vpt_interest_task_id, deleteObjectID);
510   -// #else
511   -// algorithm_vehicle_relult(vec_vptMem, vptResult, deleteObjectID);
  522 + /* for retrograde & trespass algor 逆行&非法闯入算法模块 */
  523 + algorthim_retrograde_trespass(vpt_interest_task_id, vec_vptMem, vptResult, deleteObjectID);
512 524  
513   -// send_locus_finished_msg(vpt_interest_task_id, deleteObjectID);
514 525 // #endif
515 526  
516   -// if(vptResult.size() > 0){
517   -// cout << vptResult[0].obj_count<< endl;
518   -// }
  527 + if(vptResult.size() > 0){
  528 + cout << vptResult[0].obj_count<< endl;
  529 + }
519 530 vptResult.clear();
520 531 unUsedResult.clear();
521 532 deleteObjectID.clear();
... ... @@ -532,6 +543,7 @@ int CMultiSourceProcess::algorithm_vehicle_relult(vector&lt;DeviceMemory*&gt; vec_devM
532 543  
533 544 vector<multi_obj_data_t> results = m_snapshot_reprocessing->get_vehicle_snapshot(vec_devMem, vptResult, skip_frame_);
534 545  
  546 + VPCUtil* pVPCUtil = VPCUtil::getInstance();
535 547 for (auto &result : results) {
536 548 if(result.objs.size() <= 0){
537 549 continue;
... ... @@ -551,13 +563,13 @@ int CMultiSourceProcess::algorithm_vehicle_relult(vector&lt;DeviceMemory*&gt; vec_devM
551 563  
552 564 ImgSaveInfo saveInfo;
553 565 saveInfo.file_path = fpath_origin;
554   - saveInfo.img_info = vpc_util.vpc_devMem2vpcImg(result.memPtr);
  566 + saveInfo.img_info = VPCUtil::vpc_devMem2vpcImg(result.memPtr);
555 567 m_save_snapshot_reprocessing->reprocessing_process_wo_locus_async(saveInfo);
556 568  
557   - vector<vpc_img_info> vec_obj_info_list = vpc_util.crop_batch(result.memPtr, result.objs);
  569 + vector<vpc_img_info> vec_obj_info_list = pVPCUtil->crop_batch(result.memPtr, result.objs);
558 570 if(vec_obj_info_list.size() != result.objs.size()){
559 571 LOG_ERROR("vpc_crop size error !");
560   - vpc_util.vpc_imgList_release(vec_obj_info_list);
  572 + VPCUtil::vpc_imgList_release(vec_obj_info_list);
561 573 continue;
562 574 }
563 575  
... ... @@ -645,22 +657,73 @@ void CMultiSourceProcess::vehicle_snapshot(vector&lt;string&gt;&amp; vpt_interest_task_id,
645 657 }
646 658  
647 659 /* 轨迹结束帧需要做的算法模块 */
648   -/* 轨迹结束帧需要做的算法模块 */
649 660 int CMultiSourceProcess::endframe_obj_process(const OBJ_KEY &obj_key, algorithm_type_t algor_type) {
  661 +
  662 + // 该路任务开启了抓拍功能 开始抓拍保存；若未开启抓拍，清空显存资源
  663 + vehicle_locus_finished(obj_key);
  664 +
  665 + /* 开启行人&机动车逆行算法模块，获取该目标的算法分析结果 返回结果+快照 最后释放资源 */
  666 + endframe_retrograde_obj_process(obj_key);
  667 +}
  668 +
  669 +int CMultiSourceProcess::endframe_retrograde_obj_process(const OBJ_KEY &obj_key) {
  670 + auto task_param_ptr = m_task_param_manager->get_task_algor_param(obj_key.video_id);
  671 +
  672 + /* 开启行人&机动车逆行算法模块，获取该目标的算法分析结果 返回结果+快照 最后释放资源 */
  673 + if (task_param_ptr->human_algors.find(algorithm_type_t::PEDESTRIAN_RETROGRADE) !=
  674 + task_param_ptr->human_algors.end())
  675 + retrograde_alarm(obj_key, algorithm_type_t::PEDESTRIAN_RETROGRADE);
  676 +
  677 + if (task_param_ptr->vehicle_algors.find(algorithm_type_t::VEHICLE_RETROGRADE) !=
  678 + task_param_ptr->vehicle_algors.end())
  679 + retrograde_alarm(obj_key, algorithm_type_t::VEHICLE_RETROGRADE);
  680 +}
  681 +
  682 +void CMultiSourceProcess::retrograde_alarm(const OBJ_KEY &obj_key, const algorithm_type_t &algor_type) {
  683 +
  684 + auto results = pedestrian_vehicle_retrograde_.get_results_by_id(
  685 + ai_engine_module::obj_key_t{obj_key.obj_id, obj_key.video_id, algor_type});
  686 +
  687 + bool bRetroGrade = true ;
  688 + for (unsigned idx = 0; idx < results.size(); ++idx) {
  689 + auto &result = results[idx];
  690 +
  691 + vpc_img_info src_img;
  692 + src_img.pic_desc = result.origin_img_desc;
  693 + src_img.task_id = obj_key.video_id;
  694 +
  695 + vpc_img_info roi_img;
  696 + roi_img.pic_desc = result.roi_img_desc;
  697 + roi_img.task_id = obj_key.video_id;
  698 + roi_img.object_id = obj_key.obj_id;
  699 +
  700 + if(bRetroGrade){
  701 + auto &&json_str = helpers::gen_json::gen_retrograde_json(obj_key.video_id, obj_key.obj_id, result.box, algor_type);
  702 + save_snapshot_process(obj_key, algor_type, src_img, roi_img, idx, json_str);
  703 + } else {
  704 + VPCUtil::vpc_img_release(src_img);
  705 + VPCUtil::vpc_img_release(roi_img);
  706 + }
  707 +
  708 + if (bRetroGrade == true) {
  709 + bRetroGrade = false;
  710 + }
  711 +
  712 + }
  713 +
  714 +}
  715 +
  716 +void CMultiSourceProcess::vehicle_locus_finished(const OBJ_KEY obj_key) {
650 717 auto task_param_ptr = m_task_param_manager->get_task_algor_param(obj_key.video_id);
651 718 auto task_other_param_ptr = m_task_param_manager->get_task_other_param(obj_key.video_id);
652 719  
653 720 // 该路任务开启了抓拍功能 开始抓拍保存；若未开启抓拍，清空显存资源
654   - if ((task_param_ptr->human_algors.find(algorithm_type_t::HUMAN_SNAPSHOT) != task_param_ptr->human_algors.end() ||
655   - task_param_ptr->vehicle_algors.find(algorithm_type_t::VEHICLE_SNAPSHOT) != task_param_ptr->vehicle_algors.end() ||
  721 + if ((task_param_ptr->human_algors.find(algorithm_type_t::HUMAN_SNAPSHOT) == task_param_ptr->human_algors.end() &&
  722 + task_param_ptr->vehicle_algors.find(algorithm_type_t::VEHICLE_SNAPSHOT) != task_param_ptr->vehicle_algors.end() &&
656 723 task_param_ptr->nonmotor_vehicle_algors.find(algorithm_type_t::NONMOTOR_VEHICLE_SNAPSHOT) != task_param_ptr->nonmotor_vehicle_algors.end())) {
657   -
658   - vehicle_locus_finished(obj_key);
659   -
  724 + return;
660 725 }
661   -}
662 726  
663   -void CMultiSourceProcess::vehicle_locus_finished(const OBJ_KEY obj_key){
664 727 map<OBJ_KEY, OBJ_VALUE> _total_snapshot_info = m_snapshot_reprocessing->get_total_snapshot_info();
665 728  
666 729 LOG_DEBUG("_total_snapshot_info size: {}", _total_snapshot_info.size());
... ... @@ -780,4 +843,88 @@ void CMultiSourceProcess::timing_snapshot_thread(){
780 843 jpegUtil.jpeg_release();
781 844  
782 845 LOG_INFO("timing_snapshot_thread end.");
  846 +}
  847 +
  848 +void CMultiSourceProcess::algorthim_retrograde_trespass(vector<string>& vpt_interest_task_id, vector<DeviceMemory*> vpt_interest_imgs,
  849 + vector<onelevel_det_result>& vptResult ,vector<vector<int>>& deleteObjectID){
  850 + vector<string> interest_task_id;
  851 + vector<onelevel_det_result> interest_vpt_result;
  852 + vector<DeviceMemory*> interest_imgs;
  853 +
  854 + vector<string> trespass_interest_task_id;
  855 + vector<onelevel_det_result> trespass_interest_vpt_result;
  856 + vector<vector<int>> trespass_interest_deleteobjs;
  857 + vector<DeviceMemory*> trespass_interest_imgs;
  858 +
  859 + int _idx = 0;
  860 + for (auto _task_id_iter = vpt_interest_task_id.begin(); _task_id_iter != vpt_interest_task_id.end();
  861 + ++_task_id_iter, ++_idx) // loop task_id;
  862 + {
  863 + auto task_id = *_task_id_iter;
  864 + auto algor_map = m_task_param_manager->get_task_other_param(task_id);
  865 +
  866 + if (algor_map->find(algorithm_type_t::PEDESTRIAN_RETROGRADE) != algor_map->end() ||
  867 + algor_map->find(algorithm_type_t::VEHICLE_RETROGRADE) != algor_map->end()) {
  868 + interest_task_id.emplace_back(task_id);
  869 + interest_imgs.emplace_back(vpt_interest_imgs[_idx]);
  870 + interest_vpt_result.emplace_back(vptResult[_idx]);
  871 + }
  872 +
  873 + if (algor_map->find(algorithm_type_t::PEDESTRIAN_TRESPASS) != algor_map->end() ||
  874 + algor_map->find(algorithm_type_t::VEHICLE_TRESPASS) != algor_map->end()) {
  875 + trespass_interest_task_id.emplace_back(task_id);
  876 + trespass_interest_imgs.emplace_back(vpt_interest_imgs[_idx]);
  877 + trespass_interest_vpt_result.emplace_back(vptResult[_idx]);
  878 + trespass_interest_deleteobjs.emplace_back(deleteObjectID[_idx]);
  879 + }
  880 + }
  881 +
  882 + LOG_DEBUG("trespass_interest_vpt_result size: {}", trespass_interest_vpt_result.size());
  883 +
  884 + if (!interest_imgs.empty())
  885 + pedestrian_vehicle_retrograde_.update_mstreams(interest_task_id, interest_imgs,
  886 + interest_vpt_result);
  887 +
  888 + if (!trespass_interest_imgs.empty()) {
  889 + pedestrian_vehicle_trespass_.update_mstreams(
  890 + trespass_interest_task_id, trespass_interest_imgs, trespass_interest_vpt_result,
  891 + trespass_interest_deleteobjs);
  892 + }
  893 +}
  894 +
  895 +bool CMultiSourceProcess::save_snapshot_process(const OBJ_KEY &obj_key, const algorithm_type_t &algorithm_type, vpc_img_info src_img, vpc_img_info roi_img,
  896 + const long long id,const std::string &json_str) {
  897 + auto task_other_params = m_task_param_manager->get_task_other_param(obj_key.video_id);
  898 + const auto &algor_other_params = task_other_params->find(algorithm_type);
  899 + if (algor_other_params == task_other_params->end()) {
  900 + LOG_ERROR("task_id {} not found {} error", obj_key.video_id, int(algorithm_type));
  901 + return false;
  902 + }
  903 +
  904 + const algor_basic_config_param_t *basic_param = algor_other_params->second->basic_param;
  905 +
  906 + std::string cur_timestamp_ms = std::to_string(helpers::timer::get_timestamp<std::chrono::milliseconds>());
  907 + const std::string fpath_origin = basic_param->result_folder + helpers::os::sep + obj_key.video_id + "_" +
  908 + std::to_string(obj_key.obj_id) + "_" + std::to_string(id) + "_" + cur_timestamp_ms + ".jpg";
  909 +
  910 + ImgSaveInfo obj_save_info;
  911 + obj_save_info.file_path = fpath_origin;
  912 + obj_save_info.img_info = src_img;
  913 + m_save_snapshot_reprocessing->reprocessing_process_wo_locus_async(obj_save_info);
  914 +
  915 + {
  916 + // 抠图保存
  917 + const std::string fpath_roi = basic_param->result_folder_little + helpers::os::sep + obj_key.video_id + "_" +
  918 + std::to_string(obj_key.obj_id) + "_" + std::to_string(id) + "_" + cur_timestamp_ms + ".jpg";
  919 +
  920 + // 调用快照保存后处理模块 将快照保存
  921 + ImgSaveInfo obj_save_info;
  922 + obj_save_info.file_path = fpath_roi;
  923 + obj_save_info.img_info = roi_img;
  924 + obj_save_info.json_str = json_str;
  925 + m_save_snapshot_reprocessing->reprocessing_process_wo_locus_async(obj_save_info);
  926 + }
  927 +
  928 +
  929 + return true;
783 930 }
784 931 \ No newline at end of file
... ...
src/ai_platform/MultiSourceProcess.h
  View file @29b64a8
... ... @@ -5,7 +5,8 @@
5 5 #include "../ai_engine_module/VPTProcess.h"
6 6 #include "../reprocessing_module/snapshot_reprocessing.h"
7 7 #include "../reprocessing_module/save_snapshot_reprocessing.h"
8   -#include "../util/vpc_util.h"
  8 +#include "../ai_engine_module/pedestrian_vehicle_retrograde.h"
  9 +#include "../ai_engine_module/pedestrian_vehicle_trespass.h"
9 10 #include "../util/JpegUtil.h"
10 11  
11 12 #include <map>
... ... @@ -48,6 +49,9 @@ public:
48 49 private:
49 50 // 算法相关
50 51 int algorthim_vpt(vector<DeviceMemory*> vec_gpuMem);
  52 + // 逆行&非法闯入算法模块
  53 + void algorthim_retrograde_trespass(vector<string>& vpt_interest_task_id, vector<DeviceMemory*> vpt_interest_imgs,
  54 + vector<onelevel_det_result>& vptResult ,vector<vector<int>>& deleteObjectID);
51 55  
52 56 private:
53 57 // 工具处理函数
... ... @@ -61,6 +65,12 @@ private:
61 65  
62 66 int endframe_obj_process(const OBJ_KEY &obj_key, algorithm_type_t algor_type);
63 67  
  68 + bool save_snapshot_process(const OBJ_KEY &obj_key, const algorithm_type_t &algorithm_type, vpc_img_info img_info, vpc_img_info roi_img,
  69 + const long long id,const std::string &json_str);
  70 +
  71 + int endframe_retrograde_obj_process(const OBJ_KEY &obj_key);
  72 + void retrograde_alarm(const OBJ_KEY &obj_key, const algorithm_type_t &algor_type) ;
  73 +
64 74 private:
65 75 int m_devId;
66 76  
... ... @@ -87,11 +97,14 @@ private:
87 97 set<OBJ_KEY> m_total_snapshot_info_multi_object;
88 98 mutex m_total_mutex;
89 99  
90   - VPCUtil vpc_util;
91 100 JpegUtil jpegUtil;
92 101  
93 102 #ifdef POST_USE_RABBITMQ
94 103 mq::Manager *mq_manager_{nullptr};
95 104 #endif
96 105  
  106 +
  107 + ai_engine_module::pedestrian_vehicle_retrograde::PedestrianVehicleRetrograde pedestrian_vehicle_retrograde_;
  108 + ai_engine_module::pedestrian_vehicle_trespass::PedestrianVehicleTrespass pedestrian_vehicle_trespass_;
  109 +
97 110 };
98 111 \ No newline at end of file
... ...
src/demo/demo.cpp
  View file @29b64a8
... ... @@ -478,9 +478,9 @@ static long long get_cur_time(){
478 478 string createTask(void *handle, std::vector<algorithm_type_t> algor_vec, int gi){
479 479 task_param tparam;
480 480 // tparam.ipc_url = "rtsp://admin:ad123456@192.168.60.108:554/cam/realmonitor?channel=1&subtype=0";
481   - // tparam.ipc_url = "/home/cmhu/data/bayue.mp4";
482   - // tparam.ipc_url = "/home/cmhu/data/Street.uvf";
483   - tparam.ipc_url = "rtsp://admin:ad123456@192.168.60.165:554/cam/realmonitor?channel=1&subtype=0";
  481 + // tparam.ipc_url = "/data1/cmhu/data/bayue.mp4";
  482 + tparam.ipc_url = "/data1/cmhu/data/Street.uvf";
  483 + // tparam.ipc_url = "rtsp://admin:ad123456@192.168.60.165:554/cam/realmonitor?channel=1&subtype=0";
484 484 tparam.algor_counts = algor_vec.size();
485 485 tparam.dec_type = 2;
486 486  
... ... @@ -521,7 +521,7 @@ void test_gpu(int gpuID){
521 521 printf("Init Success\n");
522 522 }
523 523  
524   - std::vector<algorithm_type_t> algor_vec = {algorithm_type_t::FACE_SNAPSHOT, algorithm_type_t::HUMAN_SNAPSHOT,algorithm_type_t::ROAD_WORK_DET,
  524 + std::vector<algorithm_type_t> algor_vec = {algorithm_type_t::FACE_SNAPSHOT, algorithm_type_t::HUMAN_SNAPSHOT,algorithm_type_t::ROAD_WORK_DET, algorithm_type_t::PEDESTRIAN_RETROGRADE, algorithm_type_t::VEHICLE_RETROGRADE,
525 525 algorithm_type_t::VEHICLE_SNAPSHOT, algorithm_type_t::NONMOTOR_VEHICLE_SNAPSHOT, algorithm_type_t::VIDEO_TIMING_SNAPSHOT};
526 526  
527 527 string task_id = createTask(handle, algor_vec, 0 + gpuID * 10);
... ...
src/reprocessing_module/save_snapshot_reprocessing.cpp
  View file @29b64a8
... ... @@ -5,6 +5,7 @@
5 5 #include <opencv2/imgproc/types_c.h>
6 6 #include <algorithm>
7 7 #include "../common/logger.hpp"
  8 +#include "../util/vpc_util.h"
8 9  
9 10 const bool DRAW_ON_IMG = false;
10 11  
... ... @@ -46,7 +47,7 @@ void save_snapshot_reprocessing::save_snapshot_reprocessing_release() {
46 47 waitforsave_img_queue.pop();
47 48  
48 49 if(!cur_image.file_path.empty()){
49   - vpc_util.vpc_img_release(cur_image.img_info);
  50 + VPCUtil::vpc_img_release(cur_image.img_info);
50 51 }
51 52 }
52 53  
... ... @@ -96,7 +97,7 @@ void save_snapshot_reprocessing::save_img_process() {
96 97 if(!cur_image.file_path.empty()){
97 98 jpegUtil.jpeg_encode(cur_image.img_info.pic_desc, cur_image.file_path);
98 99 }
99   - vpc_util.vpc_img_release(cur_image.img_info);
  100 + VPCUtil::vpc_img_release(cur_image.img_info);
100 101  
101 102 #ifdef POST_USE_RABBITMQ
102 103 if (callback_ != nullptr && cur_image.json_str.length() > 0) {
... ...
src/reprocessing_module/save_snapshot_reprocessing.h
  View file @29b64a8
... ... @@ -15,8 +15,8 @@
15 15 #include <thread>
16 16  
17 17 #include "../ai_platform/det_obj_header.h"
18   -#include "../util/vpc_util.h"
19 18 #include "../util/JpegUtil.h"
  19 +#include "../util/vpc_util.h"
20 20  
21 21 #ifdef POST_USE_RABBITMQ
22 22 #include "post_reprocessing.hpp"
... ... @@ -60,7 +60,6 @@ private:
60 60 int m_devId;
61 61  
62 62 JpegUtil jpegUtil;
63   - VPCUtil vpc_util;
64 63  
65 64 #ifdef POST_USE_RABBITMQ
66 65 callback_t callback_;
... ...
src/reprocessing_module/snapshot_reprocessing.cpp
  View file @29b64a8
... ... @@ -12,13 +12,10 @@ snapshot_reprocessing::snapshot_reprocessing(int devId)
12 12 algor_index_table["human"] = { (int)det_class_label_t::HUMAN };
13 13 algor_index_table["nonmotor_vehicle"] = { (int)det_class_label_t::BICYCLE, (int)det_class_label_t::MOTOCYCLE, (int)det_class_label_t::TRICYCLE };
14 14 algor_index_table["vehicle"] = { (int)det_class_label_t::SMALL_CAR, (int)det_class_label_t::LARGE_CAR, (int)det_class_label_t::TRUCK, (int)det_class_label_t::TRACTOR, (int)det_class_label_t::MEDIUM_BUS };
15   -
16   - vpcUtil.init(devId);
17 15 }
18 16  
19 17 snapshot_reprocessing::~snapshot_reprocessing()
20 18 {
21   - vpcUtil.release();
22 19 }
23 20  
24 21 static void box_expansion(video_object_info& obj_info, float expand_ratio, int frame_width, int frame_height){
... ... @@ -175,6 +172,8 @@ void snapshot_reprocessing::update_bestsnapshot(vector&lt;DeviceMemory*&gt; vec_devMem
175 172 map<string, algor_open_config_param> && algor_config_param = m_task_param_manager->get_task_algor_params();
176 173 map<string, map<algo_type, task_param_manager::algo_param_type_t_*>> && algor_param = m_task_param_manager->get_task_other_params();
177 174  
  175 + VPCUtil* pVpcUtil = VPCUtil::getInstance();
  176 +
178 177 for (size_t i = 0; i < vec_devMem.size(); i++){
179 178  
180 179 onelevel_det_result det_result = ol_det_result[i];
... ... @@ -316,15 +315,15 @@ void snapshot_reprocessing::update_bestsnapshot(vector&lt;DeviceMemory*&gt; vec_devMem
316 315 }
317 316 }
318 317  
319   - vector<vpc_img_info> imgList = vpcUtil.crop_batch(memPtr, vec_obj_info);
  318 + vector<vpc_img_info> imgList = pVpcUtil->crop_batch(memPtr, vec_obj_info);
320 319 vec_obj_info.clear();
321 320  
322 321 for (size_t i = 0; i < imgList.size(); i++) {
323 322 vpc_img_info obj_info = imgList[i];
324 323 OBJ_KEY objKey = { obj_info.task_id, obj_info.object_id };
325   - vpcUtil.vpc_img_release(total_snapshot_info[objKey].snapShot);
326   - total_snapshot_info[objKey].snapShot = vpcUtil.vpc_devMem2vpcImg(memPtr);
327   - vpcUtil.vpc_img_release(total_snapshot_info[objKey].snapShotLittle);
  324 + VPCUtil::vpc_img_release(total_snapshot_info[objKey].snapShot);
  325 + total_snapshot_info[objKey].snapShot = VPCUtil::vpc_devMem2vpcImg(memPtr);
  326 + VPCUtil::vpc_img_release(total_snapshot_info[objKey].snapShotLittle);
328 327 total_snapshot_info[objKey].snapShotLittle = obj_info;
329 328 }
330 329 imgList.clear();
... ... @@ -360,8 +359,8 @@ void snapshot_reprocessing::release_finished_locus_snapshot(const string taskid,
360 359 if (bRelease){
361 360 OBJ_VALUE ss = total_snapshot_info[cur_key];
362 361  
363   - vpcUtil.vpc_img_release(ss.snapShot);
364   - vpcUtil.vpc_img_release(ss.snapShotLittle);
  362 + VPCUtil::vpc_img_release(ss.snapShot);
  363 + VPCUtil::vpc_img_release(ss.snapShotLittle);
365 364 }
366 365  
367 366 total_snapshot_info.erase(cur_key);
... ... @@ -373,8 +372,8 @@ void snapshot_reprocessing::release_finished_locus_snapshot(const string taskid,
373 372 if (strcmp(ss->first.video_id.c_str(), taskid.c_str()) == 0)
374 373 {
375 374 if (bRelease){
376   - vpcUtil.vpc_img_release(ss->second.snapShot);
377   - vpcUtil.vpc_img_release(ss->second.snapShotLittle);
  375 + VPCUtil::vpc_img_release(ss->second.snapShot);
  376 + VPCUtil::vpc_img_release(ss->second.snapShotLittle);
378 377 }
379 378 total_snapshot_info.erase(ss);
380 379 }
... ...
src/reprocessing_module/snapshot_reprocessing.h
  View file @29b64a8
... ... @@ -82,6 +82,4 @@ private:
82 82  
83 83 map<string, set<int>> algor_index_table;
84 84 task_param_manager *m_task_param_manager;
85   -
86   - VPCUtil vpcUtil;
87 85 };
88 86 \ No newline at end of file
... ...
src/util/vpc_util.cpp
  View file @29b64a8
... ... @@ -28,15 +28,6 @@ void VPCUtil::release()
28 28 ret = acldvppDestroyChannel(dvppChannelDesc_);
29 29 ret = acldvppDestroyChannelDesc(dvppChannelDesc_);
30 30  
31   - if (stream_ != nullptr) {
32   - ret = aclrtDestroyStream(stream_);
33   - if (ret != ACL_SUCCESS) {
34   - LOG_ERROR("destroy stream failed");
35   - }
36   - stream_ = nullptr;
37   - }
38   - LOG_INFO("end to destroy stream");
39   -
40 31 if (context_ != nullptr) {
41 32 ret = aclrtDestroyContext(context_);
42 33 if (ret != ACL_SUCCESS) {
... ... @@ -54,8 +45,17 @@ void VPCUtil::release()
54 45 }
55 46  
56 47  
57   -int VPCUtil::vpc_crop(acldvppPicDesc *input_pic_desc, video_object_info obj)
58   -{
  48 +vpc_img_info VPCUtil::crop(DeviceMemory *devMem, video_object_info obj) {
  49 +
  50 + acldvppPicDesc *vpcInputDesc_ = acldvppCreatePicDesc();
  51 + acldvppSetPicDescData(vpcInputDesc_, devMem->getMem());
  52 + acldvppSetPicDescFormat(vpcInputDesc_, PIXEL_FORMAT_YUV_SEMIPLANAR_420);
  53 + acldvppSetPicDescWidth(vpcInputDesc_, devMem->getWidth());
  54 + acldvppSetPicDescHeight(vpcInputDesc_, devMem->getHeight());
  55 + acldvppSetPicDescWidthStride(vpcInputDesc_, devMem->getWidthStride());
  56 + acldvppSetPicDescHeightStride(vpcInputDesc_, devMem->getHeightStride());
  57 + acldvppSetPicDescSize(vpcInputDesc_, devMem->getSize());
  58 +
59 59 const int orimodelInputWidth = obj.right - obj.left; // cur model shape is 224 * 224
60 60 const int orimodelInputHeight = obj.bottom - obj.top;
61 61 const int modelInputLeft = obj.left; // cur model shape is 224 * 224
... ... @@ -87,22 +87,39 @@ int VPCUtil::vpc_crop(acldvppPicDesc *input_pic_desc, video_object_info obj)
87 87 acldvppSetPicDescHeightStride(vpcOutputDesc_, modelInputHeight);
88 88 acldvppSetPicDescSize(vpcOutputDesc_, vpcOutBufferSize_);
89 89  
90   - int ret = acldvppVpcCropAsync(dvppChannelDesc_, input_pic_desc, vpcOutputDesc_, cropArea_, stream_);
91   -
  90 + aclrtStream stream_;
  91 + aclrtCreateStream(&stream_);
  92 + int ret = acldvppVpcCropAsync(dvppChannelDesc_, vpcInputDesc_, vpcOutputDesc_, cropArea_, stream_);
92 93 ret = aclrtSynchronizeStream(stream_);
93 94  
  95 + if (stream_ != nullptr) {
  96 + aclrtDestroyStream(stream_);
  97 + }
  98 +
  99 + acldvppDestroyPicDesc(vpcInputDesc_);
  100 +
94 101 /* DestroycropResource */
95 102 (void)acldvppDestroyRoiConfig(cropArea_);
96 103 cropArea_ = nullptr;
97   - (void)acldvppDestroyPicDesc(vpcOutputDesc_);
98   - vpcOutputDesc_ = nullptr;
99 104  
100   - if (vpcOutBufferDev_ != nullptr) {
101   - (void)acldvppFree(vpcOutBufferDev_);
102   - vpcOutBufferDev_ = nullptr;
103   - }
  105 + vpc_img_info img_info ;
  106 + img_info.pic_desc = vpcOutputDesc_;
  107 + img_info.object_id = obj.object_id;
  108 + img_info.task_id = obj.task_id; //该物体属于的任务ID号
  109 + img_info.task_frame_count = obj.task_frame_count; //该物体当前出现的帧号
  110 + img_info.index = obj.index; //该物体所属类别的编号
  111 + img_info.confidence = obj.confidence; //该物体的置信度
  112 +
  113 +
  114 + // (void)acldvppDestroyPicDesc(vpcOutputDesc_);
  115 + // vpcOutputDesc_ = nullptr;
  116 +
  117 + // if (vpcOutBufferDev_ != nullptr) {
  118 + // (void)acldvppFree(vpcOutBufferDev_);
  119 + // vpcOutBufferDev_ = nullptr;
  120 + // }
104 121  
105   - return 0;
  122 + return img_info;
106 123 }
107 124  
108 125 int VPCUtil::init(int32_t devId){
... ... @@ -112,7 +129,6 @@ int VPCUtil::init(int32_t devId){
112 129 /* 2.Run the management resource application, including Device, Context, Stream */
113 130 aclrtSetDevice(deviceId_);
114 131 aclrtCreateContext(&context_, deviceId_);
115   - aclrtCreateStream(&stream_);
116 132  
117 133 // channel 准备
118 134 dvppChannelDesc_ = acldvppCreateChannelDesc();
... ... @@ -153,6 +169,10 @@ vector&lt;vpc_img_info&gt; VPCUtil::crop_batch(DeviceMemory *devMem, vector&lt;video_obje
153 169  
154 170 // 输入
155 171 acldvppBatchPicDesc *vpcInputBatchDesc_ = acldvppCreateBatchPicDesc(1);
  172 + if (vpcInputBatchDesc_ == nullptr) {
  173 + LOG_ERROR("acldvppCreatePicDesc outBatchPicDesc failed");
  174 + return vec_img_info;
  175 + }
156 176 acldvppPicDesc *vpcInputDesc_ = acldvppGetPicDesc(vpcInputBatchDesc_, 0);
157 177 acldvppSetPicDescData(vpcInputDesc_, devMem->getMem());
158 178 acldvppSetPicDescFormat(vpcInputDesc_, PIXEL_FORMAT_YUV_SEMIPLANAR_420);
... ... @@ -166,6 +186,7 @@ vector&lt;vpc_img_info&gt; VPCUtil::crop_batch(DeviceMemory *devMem, vector&lt;video_obje
166 186 acldvppBatchPicDesc *outputBatchPicDesc_ = acldvppCreateBatchPicDesc(outputBatchSize_);
167 187 if (outputBatchPicDesc_ == nullptr) {
168 188 LOG_ERROR("acldvppCreatePicDesc outBatchPicDesc failed");
  189 + (void)acldvppDestroyBatchPicDesc(vpcInputBatchDesc_);
169 190 return vec_img_info;
170 191 }
171 192 vector<void *> vecOutPtr_;
... ... @@ -216,10 +237,17 @@ vector&lt;vpc_img_info&gt; VPCUtil::crop_batch(DeviceMemory *devMem, vector&lt;video_obje
216 237 (void)acldvppSetPicDescSize(vpcOutputDesc, vpcOutBufferSize_);
217 238 }
218 239  
  240 + aclrtStream stream_;
  241 + aclrtCreateStream(&stream_);
  242 +
219 243 uint32_t roiNums[] = { outputBatchSize_ };
220 244 ret = acldvppVpcBatchCropAsync(dvppChannelDesc_, vpcInputBatchDesc_, roiNums, 1, outputBatchPicDesc_, cropAreas, stream_);
221 245 ret = aclrtSynchronizeStream(stream_);
222 246  
  247 + if (stream_ != nullptr) {
  248 + aclrtDestroyStream(stream_);
  249 + }
  250 +
223 251 for (uint32_t i = 0; i < outputBatchSize_; i++) {
224 252 video_object_info obj = objs[i];
225 253  
... ... @@ -281,7 +309,6 @@ vector&lt;vpc_img_info&gt; VPCUtil::crop_batch(DeviceMemory *devMem, vector&lt;video_obje
281 309 // acldvppDestroyPicDesc(vec_img_info[i].pic_desc);
282 310 // }
283 311 // }
284   -
285 312  
286 313 for (uint32_t i = 0; i < outputBatchSize_; i++) {
287 314 if (cropAreas[i] != nullptr) {
... ... @@ -326,6 +353,12 @@ vpc_img_info VPCUtil::vpc_devMem2vpcImg(DeviceMemory *devMem){
326 353 return img_info;
327 354 }
328 355  
  356 +void VPCUtil::vpc_pic_desc_release(acldvppPicDesc* pic_desc){
  357 + void *outputDataDev = acldvppGetPicDescData(pic_desc);
  358 + acldvppFree(outputDataDev);
  359 + acldvppDestroyPicDesc(pic_desc);
  360 +}
  361 +
329 362 void VPCUtil::vpc_img_release(vpc_img_info img_info){
330 363 if(img_info.pic_desc != nullptr){
331 364 void *outputDataDev = acldvppGetPicDescData(img_info.pic_desc);
... ...
src/util/vpc_util.h
  View file @29b64a8
... ... @@ -25,24 +25,39 @@ class DeviceMemory;
25 25 class VPCUtil {
26 26  
27 27 public:
28   - int vpc_crop(acldvppPicDesc *input_pic_desc, video_object_info obj);
  28 + static VPCUtil* getInstance(){
  29 + static VPCUtil* singleton = nullptr;
  30 + if (singleton == nullptr){
  31 + singleton = new VPCUtil();
  32 + }
  33 + return singleton;
  34 + }
29 35  
30   - int init(int32_t devId);
  36 + ~VPCUtil()
  37 + {
  38 + release();
  39 + }
31 40  
32   - vector<vpc_img_info> crop_batch(DeviceMemory *devMem, vector<video_object_info> objs);
  41 + static void vpc_pic_desc_release(acldvppPicDesc* );
33 42  
34   - void vpc_img_release(vpc_img_info );
  43 + static void vpc_img_release(vpc_img_info );
35 44  
36   - void vpc_imgList_release(vector<vpc_img_info>& );
  45 + static void vpc_imgList_release(vector<vpc_img_info>& );
37 46  
38   - void release();
  47 + static vpc_img_info vpc_devMem2vpcImg(DeviceMemory *devMem);
  48 +
  49 +public:
  50 + vpc_img_info crop(DeviceMemory *devMem, video_object_info obj);
39 51  
40   - vpc_img_info vpc_devMem2vpcImg(DeviceMemory *devMem);
  52 + int init(int32_t devId);
  53 +
  54 + vector<vpc_img_info> crop_batch(DeviceMemory *devMem, vector<video_object_info> objs);
  55 +
  56 + void release();
41 57  
42 58 private:
43 59 int32_t deviceId_;
44 60 aclrtContext context_;
45   - aclrtStream stream_;
46 61  
47 62 acldvppChannelDesc *dvppChannelDesc_;
48 63 };
... ...