Hu Chunming / src

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Commit 450989b59d4f7fdb3c326fb15ad38956a449e21b

Authored by Hu Chunming 2022-11-02 21:02:27 +0800

1 parent 78676b64

跑通算法

Inline Side-by-side

Showing 8 changed files with 139 additions and 17 deletions

test/main.cpp

View file @450989b

 @@ -76,6 +76,7 @@ algorithm_type_t algor_index_to_algor_type(const int &amp;idx) {
    }
  }
++#ifdef POST_USE_RABBITMQ
  void init_mq_conn(void *handle) {
    for (auto key : {mq_type_t::ALARM_MQ, mq_type_t::GET_TASK_MQ, mq_type_t::HEART_BEAT_MQ}) {
      rabbitmq_conn_params_t mq_conn_params;
 @@ -111,6 +112,7 @@ void init_mq_conn(void *handle) {
        fprintf(stderr, "ip is %s port is %d\n", mq_conn_params.ip, mq_conn_params.port);
    }
  }
++#endif
  const char* ipc_url = "/home/cmhu/tongtu/tsl_aiplatform_project_with_screenshot/data/duan1.avi";

tsl_aiplatform/ai_platform/GpuRgbMemory.hpp

View file @450989b

	@@ -18,7 +18,7 @@ public:		@@ -18,7 +18,7 @@ public:
18	gpuid = _gpuid;	18	gpuid = _gpuid;
19	timestamp = helpers::timer::get_timestamp<std::chrono::milliseconds>();	19	timestamp = helpers::timer::get_timestamp<std::chrono::milliseconds>();
20		20
21	- // cudaSetDevice(atoi(gpuid.c_str()));	21	+ cudaSetDevice(atoi(gpuid.c_str()));
22	CHECK(cudaMalloc((void *)&pHwRgb, size sizeof(unsigned char)));	22	CHECK(cudaMalloc((void *)&pHwRgb, size sizeof(unsigned char)));
23	}	23	}
24		24

tsl_aiplatform/ai_platform/MultiSourceProcess.cpp

View file @450989b

 @@ -9,6 +9,8 @@
  #include "authority.h"
++#include "NvJpegEncoder.hpp"
++
  #ifdef AUTHORIZATION
  #include <boost/thread.hpp>
  #ifdef _MSC_VER
 @@ -261,6 +263,9 @@ int CMultiSourceProcess::InitAlgorthim(tsl_aiplatform_param vptParam) {
  #endif // #ifdef __linux__
  #endif // #ifdef AUTHORIZATION
++  // 启动算法处理线程
++  startProcessByGpuid();
++
    return ret;
  }
 @@ -329,8 +334,6 @@ bool CMultiSourceProcess::AddTask(task_param _cur_task_param){
      // 所有参数都准备好之后再启动解码
      pDecManager->startDecodeByName(config.name);
      cout << "started task: " << config.name << endl;
--    // 启动算法处理线程
--    startProcessByGpuid();
  }
  // 启动算法处理线程
 @@ -352,8 +355,14 @@ void CMultiSourceProcess::post_decode_thread(decode_cbk_userdata* userPtr, AVFra
    FFNvDecoder* dec = (FFNvDecoder*)ptr->opaque1;
    if (gpuFrame->format == AV_PIX_FMT_CUDA && dec != nullptr){
--    cout << "decode task: " << dec->getName() << " gpuid: " << gpu_id_ << endl;
++    // cout << "decode task: " << dec->getName() << " gpuid: " << gpu_id_ << endl;
      GpuRgbMemory* gpuMem = new GpuRgbMemory(3, gpuFrame->width, gpuFrame->height, dec->getName(), gpu_id_ , true);
++
++    if (gpuMem->getMem() == nullptr){
++      cout << "new GpuRgbMemory failed !!!" << endl;
++      return;
++    }
++
      // cudaSetDevice(atoi(gpu_id_.c_str()));
      // cuda_common::setColorSpace( ITU_709, 0 );
 @@ -431,7 +440,11 @@ void CMultiSourceProcess::cuda_free_wrap(sy_img &amp;img) {
  // 算法处理函数，由算法线程调用
  void CMultiSourceProcess::algorthim_process_thread(){
++  cudaSetDevice(atoi(gpu_id_.c_str()));
++
    map<string, int> task_id_to_n_frame;
++
++  int sum = 0;
    while(true){
      /* step1. 授权check */
      if (licence_status_ <= -3) {
 @@ -470,6 +483,10 @@ void CMultiSourceProcess::algorthim_process_thread(){
        batch_img[i].set_data(gpuMem->getWidth(), gpuMem->getHeight(), gpuMem->getChannel(), gpuMem->getMem());
        task_list.push_back(gpuMem->getId());
        ++task_id_to_n_frame[gpuMem->getId()];
++
++      // string path = "/home/cmhu/data2/test/" + gpuMem->getId() + "_" + to_string(sum) + ".jpg";
++      // saveJpeg(path.c_str(), gpuMem->getMem(), gpuMem->getWidth(), gpuMem->getHeight(), nullptr);  // 验证 CUDAToRGB
++      // sum ++;
      }
      m_QueueMtx.unlock();
 @@ -511,6 +528,8 @@ void CMultiSourceProcess::algorthim_process_thread(){
      LOG_DEBUG("{}", msg);
    }
  #endif
++
++  cout << "algorthim_process_thread end. " << endl;
  }
  // VPT 检测
 @@ -669,7 +688,6 @@ void CMultiSourceProcess::algorithm_snapshot(vector&lt;string&gt;&amp; vpt_interest_task_i
  /* 轨迹结束帧需要做的算法模块 */
  int CMultiSourceProcess::endframe_obj_process(const OBJ_KEY &obj_key, algorithm_type_t algor_type) {
    auto task_param_ptr = m_task_param_manager->get_task_algor_param(obj_key.video_id);
--  auto task_other_param_ptr = m_task_param_manager->get_task_other_param(obj_key.video_id);
    // 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
    if ((task_param_ptr->human_algors.find(algorithm_type_t::HUMAN_SNAPSHOT) != task_param_ptr->human_algors.end() ||
 @@ -884,6 +902,7 @@ int CMultiSourceProcess::endframe_obj_process(const OBJ_KEY &amp;obj_key, algorithm_
    }
    #endif
++  auto task_other_param_ptr = m_task_param_manager->get_task_other_param(obj_key.video_id);
    /* 开启人脸抓拍分析算法模块，获取该目标的算法分析结果 返回结果+快照 最后释放资源 */
    if (task_other_param_ptr->find(algorithm_type_t::FACE_SNAPSHOT) != task_other_param_ptr->end() &&
        algor_type == algorithm_type_t::FACE_SNAPSHOT) {
 @@ -1095,8 +1114,10 @@ void CMultiSourceProcess::algorthim_face_detect(vector&lt;string&gt;&amp; task_list, sy_im
      std::vector<onelevel_det_result> facedet_result(image_size);
      std::vector<std::vector<int>> face_deleteObjectID(image_size);
++#ifdef WITH_FACE_DET_SS
      m_face_det_ai_engine.ai_engine_process_batch2(face_det_interest_task_id,
          face_det_interest_imgs.data(), face_det_interest_imgs.size(), facedet_result, face_deleteObjectID);
++#endif
  #if 0
      // accum
 @@ -1129,6 +1150,7 @@ void CMultiSourceProcess::algorthim_face_detect(vector&lt;string&gt;&amp; task_list, sy_im
  #endif
  }
++#ifdef POST_USE_RABBITMQ
  /* MQ队列的初始化 */
  int CMultiSourceProcess::AddMqConn(mq_type_t mq_type, rabbitmq_conn_params_t mq_conn_param) {
    /* 初始化MQ队列 */
 @@ -1170,6 +1192,7 @@ int CMultiSourceProcess::GetTaskStatus(const string taskID) {
    return SUCCESS;
  }
++#endif
  bool CMultiSourceProcess::PauseTask(const string taskID) {
    FFNvDecoderManager* pDecManager = FFNvDecoderManager::getInstance();
 @@ -1182,15 +1205,12 @@ bool CMultiSourceProcess::RestartTask(const string taskID){
  }
  bool CMultiSourceProcess::finish_task(const string taskID, const bool delete_snapshot){
--  FFNvDecoderManager* pDecManager = FFNvDecoderManager::getInstance();
--  bool ret = pDecManager->closeDecoderByName(taskID);
--
  #ifdef POST_USE_RABBITMQ
    auto json_str = helpers::gen_json::gen_office_task_heart_beat_json({taskID});
    mq_manager_->publish(mq_type_t::HEART_BEAT_MQ, json_str.c_str(), true);
  #endif
--  #ifdef WITH_FACE_DET_SS
++#ifdef WITH_FACE_DET_SS
    // 人脸任务结束
    auto task_param_ptr = m_task_param_manager->get_task_algor_param(taskID);
    if (task_param_ptr->human_face_algors.find(algorithm_type_t::FACE_SNAPSHOT) !=
 @@ -1201,7 +1221,14 @@ bool CMultiSourceProcess::finish_task(const string taskID, const bool delete_sna
    m_task_param_manager->delete_task_param(taskID);
--  if (delete_snapshot) {
++  return true;
++}
++
++bool CMultiSourceProcess::FinishTask(const string taskID){
++  FFNvDecoderManager* pDecManager = FFNvDecoderManager::getInstance();
++  bool ret = pDecManager->closeDecoderByName(taskID);
++
++  if (ret){
      m_snapshot_reprocessing->delete_finishtask_snapshot(taskID);
      ((save_snapshot_reprocessing *)m_save_snapshot_reprocessing)->delete_finishtask(taskID);
    }
 @@ -1209,10 +1236,6 @@ bool CMultiSourceProcess::finish_task(const string taskID, const bool delete_sna
    return ret;
  }
--bool CMultiSourceProcess::FinishTask(const string taskID){
--  return finish_task(taskID,true);
--}
--
  void CMultiSourceProcess::CloseAllTask(){
    m_bfinish = true;

tsl_aiplatform/ai_platform/NvJpegEncoder.hpp 0 → 100644

View file @450989b

		1	+/*
		2	+*主要用于测试显卡上的数据是否正常
		3	+*/
		4	+
		5	+#include <nvjpeg.h>
		6	+
		7	+#include <fstream>
		8	+#include <vector>
		9	+#include <iostream>
		10	+
		11	+
		12	+#define CHECK_NVJPEG(S) do {nvjpegStatus_t status; \
		13	+ status = S; \
		14	+ if (status != NVJPEG_STATUS_SUCCESS ) std::cout << __LINE__ <<" CHECK_NVJPEG - status = " << status << std::endl; \
		15	+ } while (false)
		16	+
		17	+
		18	+int saveJpeg(const char * filepath, unsigned char* d_srcBGR, int width, int height, cudaStream_t stream)
		19	+{
		20	+ nvjpegHandle_t nvjpeg_handle;
		21	+ nvjpegEncoderState_t encoder_state;
		22	+ nvjpegEncoderParams_t encoder_params;
		23	+
		24	+ cudaEvent_t ev_start, ev_end;
		25	+ cudaEventCreate(&ev_start);
		26	+ cudaEventCreate(&ev_end);
		27	+
		28	+ nvjpegImage_t input;
		29	+ nvjpegInputFormat_t input_format = NVJPEG_INPUT_BGRI;
		30	+ int image_width = width;
		31	+ int image_height = height;
		32	+
		33	+ // int channel_size = image_width * image_height;
		34	+ // for (int i = 0; i < 3; i++)
		35	+ // {
		36	+ // input.pitch[i] = image_width;
		37	+ // (cudaMalloc((void**)&(input.channel[i]), channel_size));
		38	+ // (cudaMemset(input.channel[i], 50 * 40 * i, channel_size));
		39	+ // }
		40	+
		41	+ input.channel[0] = d_srcBGR;
		42	+ input.pitch[0] = image_width * 3;
		43	+
		44	+ nvjpegBackend_t backend = NVJPEG_BACKEND_DEFAULT;
		45	+
		46	+ CHECK_NVJPEG(nvjpegCreate(backend, nullptr, &nvjpeg_handle));
		47	+
		48	+ CHECK_NVJPEG(nvjpegEncoderParamsCreate(nvjpeg_handle, &encoder_params, stream));
		49	+ CHECK_NVJPEG(nvjpegEncoderStateCreate(nvjpeg_handle, &encoder_state, stream));
		50	+
		51	+ // set params
		52	+ CHECK_NVJPEG(nvjpegEncoderParamsSetEncoding(encoder_params, nvjpegJpegEncoding_t::NVJPEG_ENCODING_PROGRESSIVE_DCT_HUFFMAN, stream));
		53	+ CHECK_NVJPEG(nvjpegEncoderParamsSetOptimizedHuffman(encoder_params, 1, stream));
		54	+ CHECK_NVJPEG(nvjpegEncoderParamsSetQuality(encoder_params, 70, stream));
		55	+ CHECK_NVJPEG(nvjpegEncoderParamsSetSamplingFactors(encoder_params, nvjpegChromaSubsampling_t::NVJPEG_CSS_420, stream));
		56	+
		57	+ cudaEventRecord(ev_start);
		58	+ CHECK_NVJPEG(nvjpegEncodeImage(nvjpeg_handle, encoder_state, encoder_params, &input, input_format, image_width, image_height, stream));
		59	+ cudaEventRecord(ev_end);
		60	+
		61	+ std::vector<unsigned char> obuffer;
		62	+ size_t length;
		63	+ CHECK_NVJPEG(nvjpegEncodeRetrieveBitstream(
		64	+ nvjpeg_handle,
		65	+ encoder_state,
		66	+ NULL,
		67	+ &length,
		68	+ stream));
		69	+
		70	+ obuffer.resize(length);
		71	+ CHECK_NVJPEG(nvjpegEncodeRetrieveBitstream(
		72	+ nvjpeg_handle,
		73	+ encoder_state,
		74	+ obuffer.data(),
		75	+ &length,
		76	+ stream));
		77	+
		78	+ cudaEventSynchronize(ev_end);
		79	+
		80	+ // 用完销毁，避免显存泄露
		81	+ nvjpegEncoderParamsDestroy(encoder_params);
		82	+ nvjpegEncoderStateDestroy(encoder_state);
		83	+ nvjpegDestroy(nvjpeg_handle);
		84	+
		85	+ float ms;
		86	+ cudaEventElapsedTime(&ms, ev_start, ev_end);
		87	+ // std::cout << "time spend " << ms << " ms" << std::endl;
		88	+
		89	+ std::ofstream outputFile(filepath, std::ios::out \| std::ios::binary);
		90	+ outputFile.write(reinterpret_cast<const char *>(obuffer.data()), static_cast<int>(length));
		91	+ outputFile.close();
		92	+
		93	+ return 0;
		94	+}
0	\ No newline at end of file	95	\ No newline at end of file

tsl_aiplatform/ai_platform/header.h

View file @450989b

	@@ -445,7 +445,7 @@ enum ai_log_level {		@@ -445,7 +445,7 @@ enum ai_log_level {
445	#endif	445	#endif
446		446
447		447
448	-#define POST_USE_RABBITMQ	448	+// #define POST_USE_RABBITMQ
449		449
450	#ifdef POST_USE_RABBITMQ	450	#ifdef POST_USE_RABBITMQ
451	/**	451	/**

tsl_aiplatform/ai_platform/stl_aiplatform.cpp

View file @450989b

 @@ -24,7 +24,6 @@ int add_mq_conn(void *handle, mq_type_t tstatus, rabbitmq_conn_params_t mq_conn_
  	int res = tools->AddMqConn(tstatus, mq_conn_param);
  	return res;
  }
--#endif
  int get_task_status(void *handle, char *task_id)
 @@ -33,6 +32,7 @@ int get_task_status(void *handle, char *task_id)
  	int res = tools->GetTaskStatus(task_id);
  	return res;
  }
++#endif
  int add_task(void *handle, task_param param)

tsl_aiplatform/ai_platform/stl_aiplatform.h

View file @450989b

 @@ -42,11 +42,13 @@ extern &quot;C&quot;
  	 * @return TSL_AIPLATFORM_API
  	 */
  	TSL_AIPLATFORM_API int add_mq_conn(void *handle, mq_type_t tstatus, rabbitmq_conn_params_t mq_conn_param);
--#endif
++
  	TSL_AIPLATFORM_API int get_task_status(void *handle, char *task_id);
++#endif
++
  	/*************************************************************************
  	* FUNCTION: add_task
  	* PURPOSE: 添加任务

tsl_aiplatform/helpers/helpers.h

View file @450989b

	@@ -16,5 +16,6 @@		@@ -16,5 +16,6 @@
16	#include "logger.hpp"	16	#include "logger.hpp"
17	#include "str_helper.hpp"	17	#include "str_helper.hpp"
18	#include "os_helper.hpp"	18	#include "os_helper.hpp"
		19	+#include "timer.hpp"
19		20
20		21