motocycle_hs_process.cpp
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#include <algorithm>
#include "./motocycle_hs_process.h"
#include <cmath>
#include "../decoder/interface/DeviceMemory.hpp"
#include "../common/logger.hpp"
#include "../ai_platform/mvpt_process_assist.h"
namespace ai_engine_module
{
namespace motocycle_hs_process
{
static std::set<algorithm_type_t> algor_type_list_ = {
algorithm_type_t::NONMOTOR_VEHICLE_NOHELMET,
algorithm_type_t::NONMOTOR_VEHICLE_OVERMAN,
};
inline bool is_valid_label(const label_t &label) {
return ((label == label_t::helmet_major) ||
(label == label_t::nohelmet_major));
}
std::set<algorithm_type_t> task_id_to_algorithm_type_seq(const task_id_t &task_id,
task_param_manager *const task_param) {
std::set<algorithm_type_t> seq;
auto &&algor_map = task_param->get_task_other_param(task_id);
if (algor_map) {
// LOG_TRACE("task id is {} size algor type {}", task_id, algor_map->size());
for (auto iter = algor_map->begin(); iter != algor_map->end(); ++iter) {
if (algor_type_list_.count(iter->first) > 0)
seq.emplace(iter->first);
}
}
return seq; // N(RVO)
}
bool is_valid_box(const int top, const int left, const int right, const int bottom, const float score,
const algorithm_type_t &algor_type,
const task_param_manager::algo_param_type_t_ *params_ptr = nullptr) {
if (!params_ptr)
return false;
if (!snapshot_legal_inarea(params_ptr->basic_param->algor_valid_rect, left, top, right, bottom))
return false;
if (params_ptr->algor_param == nullptr)
return false;
const unsigned width = right - left;
const unsigned height = bottom - top;
if (width == 0 || height == 0)
return false;
//! TODO: use switch to replace.
using data_t = algor_config_param_manned_incident;
data_t *algor_params_ptr = (data_t *) (params_ptr->algor_param);
if ((width < algor_params_ptr->obj_min_width || height < algor_params_ptr->obj_min_height || score < algor_params_ptr->obj_confidence_threshold))
return false;
return true;
}
MotorHsProcess::MotorHsProcess()
: task_param_manager_(nullptr)
{
}
MotorHsProcess::~MotorHsProcess()
{
if (tools_) {
hs_motor_release(&tools_);
tools_ = nullptr;
}
if (m_algorthim_ctx) {
aclrtDestroyContext(m_algorthim_ctx);
}
}
bool MotorHsProcess::init(int gpu_id, string models_dir)
{
init_ = false;
string model_path = models_dir + "/models/hs/hs_motor_310p.om" ;
LOG_INFO("hs_motor 版本：{} 模型路径：{}", hs_motor_getversion(), model_path);
hs_motor_param param;
char modelNames[100];
strcpy(modelNames, model_path.c_str());
param.modelNames = modelNames;
param.thresld = 0.25;
param.devId = gpu_id;
m_devId = param.devId;
ACL_CALL(aclrtSetDevice(m_devId), ACL_SUCCESS, -1);
ACL_CALL(aclrtCreateContext(&m_algorthim_ctx, m_devId), ACL_SUCCESS, -1);
int status;
if (!(init_ = (0 == (status = hs_motor_init(&tools_, param)))))
LOG_ERROR("Init MotorHsProcessSdk failed error code is {}", status);
else
if (!task_param_manager_)
task_param_manager_ = task_param_manager::getInstance();
return init_;
}
bool MotorHsProcess::check_initied()
{
if (!init_)
LOG_ERROR("[%s:%d] call init function please.", __FILE__, __LINE__);
return init_;
}
void MotorHsProcess::force_release_result(const task_id_t& task_id) {
for (auto iter = id_to_result_.begin(); iter != id_to_result_.end();) {
const auto& key = iter->first;
if (key.task_id == task_id) {
auto& value = iter->second;
if (value.origin_img_desc != nullptr) {
VPCUtil::vpc_pic_desc_release(value.origin_img_desc);
}
if (value.roi_img_desc != nullptr) {
VPCUtil::vpc_pic_desc_release(value.roi_img_desc);
}
iter = id_to_result_.erase(iter);
}
else {
++iter;
}
}
}
std::shared_ptr<results_data_t> MotorHsProcess::get_result_by_objectid(const id_t& id, bool do_erase)
{
auto it = id_to_result_.find(id);
if (it == id_to_result_.end())
return std::shared_ptr<results_data_t>(nullptr);
std::shared_ptr<results_data_t> res = std::make_shared<results_data_t>(it->second);
if (do_erase)
id_to_result_.erase(id);
return res;
}
bool MotorHsProcess::update_mstreams(const std::vector<task_id_t>& taskIds, vector<DeviceMemory*> vec_det_input_images, const std::vector<onelevel_det_result> &det_results)
{
if (!check_initied())
return false;
if (det_results.empty())
{
LOG_DEBUG("detection result is empty.");
return false;
}
struct stream_idx_and_algor_seq_t {
unsigned stream_idx;
std::set<algorithm_type_t> algors;
};
int n_images = det_results.size(); // or n_stream
unsigned flattened_idx = 0;
std::map<int, int> flattened_idx_to_batch_idx;
//! 记录每个box对应的算法以及流id.
std::map<unsigned, stream_idx_and_algor_seq_t> flattened_idx_to_algor_seq;
/* 1. Crop & keep some interest class. */
auto taskId_iter = taskIds.begin();
std::vector<sy_img> flattened_imgs(0);
std::vector<vpc_img_info> flattened_vpc_imgs(0);
std::vector<input_data_wrap_t> flattened_interest_data(0); //
VPCUtil* pVpcUtil = VPCUtil::getInstance();
for (int n = 0; n < n_images; ++n)
{
int n_interest_obj = 0;
auto& src_img = vec_det_input_images[n];
int src_img_w = src_img->getWidth();
int src_img_h = src_img->getHeight();
auto& boxes_of_one_image = det_results[n].obj;
for (int i = 0; i < det_results[n].obj_count; ++i)
{
auto& box = boxes_of_one_image[i];
if (static_cast<det_class_label_t>(box.index) == det_class_label_t::MOTOCYCLE)
{
auto& taskId = *taskId_iter;
input_data_wrap_t data;
int top = std::max(int(box.top - (IMAGE_CROP_EXPAND_RATIO * box.top)), 0);
int left = std::max(int(box.left - (IMAGE_CROP_EXPAND_RATIO * box.left)), 0);
int right = std::min(int(box.right + (IMAGE_CROP_EXPAND_RATIO * box.right)), src_img_w);
int bottom = std::min(int(box.bottom + (IMAGE_CROP_EXPAND_RATIO * box.bottom)), src_img_h);
//! loop per algor from set.
stream_idx_and_algor_seq_t stream_idx_and_algor_seq{n, {}};
std::set<algorithm_type_t> algorithm_type_seq = task_id_to_algorithm_type_seq(taskId,
task_param_manager_); // N(RVO).
for (auto algor_iter = algorithm_type_seq.begin();algor_iter != algorithm_type_seq.end(); ++algor_iter) {
const algorithm_type_t algor_type = *algor_iter;
auto &&algor_param_wrap = task_param_manager_->get_task_other_param(taskId, algor_type);
if (!algor_param_wrap) {
LOG_ERROR("{} is nullptr when get algor param from task_param", taskId.c_str());
continue;
}
if (!is_valid_box(top, left, right, bottom, box.confidence, algor_type, algor_param_wrap))
continue;
stream_idx_and_algor_seq.algors.emplace(algor_type);
}
if (stream_idx_and_algor_seq.algors.empty())
continue;
int width = right - left;
int height = bottom - top;
data.box.top = top;
data.box.left = left;
data.box.right = right;
data.box.bottom = bottom;
data.box.score = box.confidence;
data.taskId = taskId;
data.objId = box.id;
// data.id = obj_key_t{ box.id, taskId, algorithm_type_t::TRUCK_MANNED };
// 抠图
video_object_info obj;
strcpy(obj.task_id, taskId.c_str());
obj.object_id = box.id;
obj.left = left; obj.top = top;
obj.right = right; obj.bottom = bottom;
vpc_img_info img_info = pVpcUtil->crop(src_img, obj);
sy_img img;
img.w_ = width;
img.h_ = height;
img.c_ = src_img->getChannel();
if (img_info.pic_desc != nullptr) {
void *outputDataDev = acldvppGetPicDescData(img_info.pic_desc);
img.data_ = reinterpret_cast<unsigned char*>(outputDataDev);
}
else {
LOG_ERROR("Crop image NPU failed wh is [{}, {}] ltrb is [{} {} {} {}]",
src_img_w, src_img_h, data.box.left, data.box.top, data.box.right, data.box.bottom);
continue;
}
flattened_imgs.emplace_back(std::move(img));
flattened_vpc_imgs.emplace_back(std::move(img_info));
flattened_interest_data.emplace_back(std::move(data));
flattened_idx_to_algor_seq[flattened_idx] = std::move(stream_idx_and_algor_seq);
flattened_idx_to_batch_idx[flattened_idx++] = n;
}
}
++taskId_iter;
}
int ret = aclrtSetCurrentContext(m_algorthim_ctx);
if (ACL_SUCCESS != ret) {
return false;
}
/* 2. collection result. */
int n_input_image = flattened_imgs.size();
hs_motor_result model_results[n_input_image];
{
int steps = (n_input_image + MAX_BATCH - 1) / MAX_BATCH;
for (int step = 0; step < steps; ++step)
{
int offset = step * MAX_BATCH;
int batch_size = (step == steps - 1) ? n_input_image - offset : MAX_BATCH;
hs_motor_process_batch(tools_, flattened_imgs.data() + offset, batch_size, model_results + offset);
}
}
/* 3. postprocess. */
{
for (int n = 0; n < n_input_image; ++n)
{
auto& det_result = flattened_interest_data[n];
auto& objId = det_result.objId;
auto& task_id = det_result.taskId;
auto &stream_idx_and_algor_seq = flattened_idx_to_algor_seq[n];
auto &algors = stream_idx_and_algor_seq.algors;
// auto &steram_idx = stream_idx_and_algor_seq.stream_idx;
const auto& src_img = vec_det_input_images[flattened_idx_to_batch_idx[n]];
auto &model_result = model_results[n];
int person_cnt = 0, helmet_cnt = 0; //统计主要车驾乘人员数量及戴盔数量
for (unsigned i = 0; i < model_result.objcount; ++i) {
auto &box = model_result.objinfo[i];
const label_t label = static_cast<label_t>(box.index);
// LOG_TRACE("task id is {} obj_id {} label {} score {}", task_id, obj_id, label, box.obj_score);
if (!is_valid_label(label))
continue;
person_cnt ++;
if (box.index == 0)
helmet_cnt ++;
}
// if (person_cnt == 0) {
// VPCUtil::vpc_img_release(flattened_vpc_imgs[n]); //flattened_imgs[n].data_
// flattened_imgs[n].data_ = nullptr;
// continue;
// }
for (auto algor_type_iter = algors.begin();algor_type_iter != algors.end(); ++algor_type_iter) {
const algorithm_type_t algor_type = *algor_type_iter;
auto &&algor_param_wrap = task_param_manager_->get_task_other_param(task_id, algor_type);
if (!algor_param_wrap) {
LOG_ERROR("{} is nullptr when get algor param from task_param", task_id);
continue;
}
auto algor_param = ((algor_param_type)algor_param_wrap->algor_param);
id_t obj_key = obj_key_t{ objId, task_id, algor_type};
if (id_to_result_.find(obj_key) != id_to_result_.end())
continue;
// LOG_TRACE("task id is {} algor type is {} obj_id {}", task_id, int(algor_type), objId);
auto& e = id_to_mn_[obj_key];
++e.m_frame;
// 超载：数量小于设定阈值不报警
if (algor_type == algorithm_type_t::NONMOTOR_VEHICLE_OVERMAN && person_cnt < algor_param->hs_count_threshold)
continue;
// 未戴盔：戴盔数量不小于驾乘数量则不报警
if (algor_type == algorithm_type_t::NONMOTOR_VEHICLE_NOHELMET && person_cnt <= helmet_cnt)
continue;
{
if (++e.n_frame == algor_param->n)
{
results_data_t result;
{
result.box = det_result.box;
result.taskId = det_result.taskId;
result.objId = det_result.objId;
result.algor_type = algor_type;
// 原图
vpc_img_info src_img_info = VPCUtil::vpc_devMem2vpcImg(src_img);
result.origin_img_desc = src_img_info.pic_desc;
// 抠图--拷贝后赋值
void *outputDataDev = acldvppGetPicDescData(flattened_vpc_imgs[n].pic_desc);
int nBufferSize = acldvppGetPicDescSize(flattened_vpc_imgs[n].pic_desc);
void *devBuffer = nullptr;
auto ret = acldvppMalloc(&devBuffer, nBufferSize);
if (ret != ACL_SUCCESS) {
LOG_ERROR("acldvppMalloc failed, size = %u, errorCode = %d.", nBufferSize, static_cast<int32_t>(ret));
return false;
}
aclrtMemcpy(devBuffer, nBufferSize, outputDataDev, nBufferSize, ACL_MEMCPY_DEVICE_TO_DEVICE);
acldvppPicDesc *vpcInputDesc_= acldvppCreatePicDesc();
acldvppSetPicDescData(vpcInputDesc_, devBuffer);
acldvppSetPicDescFormat(vpcInputDesc_, PIXEL_FORMAT_YUV_SEMIPLANAR_420);
acldvppSetPicDescWidth(vpcInputDesc_, acldvppGetPicDescWidth(flattened_vpc_imgs[n].pic_desc));
acldvppSetPicDescHeight(vpcInputDesc_, acldvppGetPicDescHeight(flattened_vpc_imgs[n].pic_desc));
acldvppSetPicDescWidthStride(vpcInputDesc_, acldvppGetPicDescWidthStride(flattened_vpc_imgs[n].pic_desc));
acldvppSetPicDescHeightStride(vpcInputDesc_, acldvppGetPicDescHeightStride(flattened_vpc_imgs[n].pic_desc));
acldvppSetPicDescSize(vpcInputDesc_, nBufferSize);
result.roi_img_desc = vpcInputDesc_; //需复制
}
id_to_result_.emplace(obj_key, std::move(result));
}
}
if (e.m_frame == algor_param->m)
e.reset();
}
VPCUtil::vpc_img_release(flattened_vpc_imgs[n]); //flattened_imgs[n].data_
}
}
return true;
}
} // namespace motocycle_hs_process
} // namespace ai_engine_module