同步模式推理流程

OpenVINO2023版本的SDK支持同步與異步推理模式相比之前OpenVINO2021版本更加的簡(jiǎn)潔，易用。同時(shí)支持創(chuàng)建多個(gè)Requst然后基于多個(gè)Requst實(shí)現(xiàn)流水線方式的推理從而提升CPU推理的吞吐率。同步模式下OpenVINO2023 SDK的推理方式如下：

推理的流程如下：

while(true) {
  // capture frame
  // populate CURRENT InferRequest
  // Infer CURRENT InferRequest
  //this call is synchronous
  // display CURRENT result
}

// 創(chuàng)建IE插件, 查詢支持硬件設(shè)備
ov::Core core;
std::string model_onnx = "D:/python/yolov5-7.0/yolov5s.onnx";
auto model = core.read_model(model_onnx);
ov::CompiledModel cmodel = core.compile_model(model, "CPU");




// create infer request
auto request = cmodel.create_infer_request();
cv::Mat frame;
while (true) {
  bool ret = cap.read(frame);
  if (frame.empty()) {
    break;
  }
  image_detect(frame, request);
  char c = cv::waitKey(1);
  if (c == 27) { // ESC
    break;
  }
}

// 前處理
// 開啟同步
request.infer();
// 后處理

異步模式推理流程

當(dāng)使用OpenVINO2023提供的Request對(duì)象的回調(diào)功能以后，我們可以把模型的后處理直接放到回調(diào)中去，這樣異步推理方式就變成只有圖像前處理+模型推兩個(gè)步驟了，然后通過創(chuàng)建兩個(gè)Request基于流水線方式，實(shí)現(xiàn)異步流水線模式推理方式，這個(gè)時(shí)候推理流程如下：

推理的流程如下：

while(true) {
  // capture frame
  // populate NEXT InferRequest
  // start NEXT InferRequest
  // this call is async and returns immediately
  // wait for the CURRENT InferRequest
  // display CURRENT result
  // swap CURRENT and NEXT InferRequests
}

 1//創(chuàng)建IE插件,查詢支持硬件設(shè)備
 2ov::Corecore;
 3std::stringmodel_onnx="D:/python/yolov5-7.0/yolov5s.onnx";
 4automodel=core.read_model(model_onnx);
 5ov::CompiledModelcmodel=core.compile_model(model,"AUTO");
 6
 7//createinferrequest
 8autorequest=cmodel.create_infer_request();
 9autonext_request=cmodel.create_infer_request();
10std::exception_ptrexception_var;
11request.set_callback([&](std::exception_ptrex){
12if(ex){
13exception_var=ex;
14return;
15}
16det_boxes.clear();
17det_ids.clear();
18ov::Tensoroutput=request.get_output_tensor();
19constfloat*prob=(float*)output.data();
20constov::ShapeoutputDims=output.get_shape();
21size_tnumRows=outputDims[1];
22size_tnumCols=outputDims[2];
23
24//后處理,1x25200x85
25std::vectorboxes;
26std::vectorclassIds;
27std::vectorconfidences;
28cv::Matdet_output(numRows,numCols,CV_32F,(float*)prob);
29for(inti=0;i(i,4);
31if(confidence0.25)
41{
42floatcx=det_output.at(i,0);
43floatcy=det_output.at(i,1);
44floatow=det_output.at(i,2);
45floatoh=det_output.at(i,3);
46intx=static_cast((cx-0.5*ow)*x_factor);
47inty=static_cast((cy-0.5*oh)*y_factor);
48intwidth=static_cast(ow*x_factor);
49intheight=static_cast(oh*y_factor);
50cv::Rectbox;
51box.x=x;
52box.y=y;
53box.width=width;
54box.height=height;
55
56boxes.push_back(box);
57classIds.push_back(classIdPoint.x);
58confidences.push_back(score);
59}
60}
61
62//NMS
63std::vectorindexes;
64cv::NMSBoxes(boxes,confidences,0.25,0.45,indexes);
65for(size_ti=0;i
 依據(jù)上述的推理流程，最終調(diào)用執(zhí)行的代碼如下：
 1cv::Matframe,next_frame;
 2//dofirstframe
 3cap.read(frame);
 4async_image_detect(frame,request);
 5std::millisecondstout{50};
 6intcnt=0;
 7while(true){
 8boolret=cap.read(next_frame);
 9if(next_frame.empty()){
10break;
11}
12
13int64start=cv::getTickCount();
14//繼續(xù)異步
15if(cnt%2==0){
16async_image_detect(next_frame,next_request);
17request.wait_for(tout);
18}
19if(cnt%2==1){
20async_image_detect(next_frame,request);
21next_request.wait_for(tout);
22}
23for(size_tt=0;t(cv::getTickFrequency());
31putText(frame,cv::format("FPS:%.2f",1.0/t),cv::Point(20,40),cv::FONT_HERSHEY_PLAIN,2.0,cv::Scalar(255,0,0),2,8);
32cv::imshow("OpenVINO2023-YOLOv57.0異步推理",frame);
33charc=cv::waitKey(1);
34if(c==27){//ESC
35break;
36}
37next_frame.copyTo(frame);
38cnt++;
39}
40cv::waitKey(0);
41cv::destroyAllWindows();
42return0;
 其中async_image_detect方法中實(shí)現(xiàn)了YOLOv5模型推理的圖像前處理與啟動(dòng)異步推理模式
preprocess(frame)
// 開啟異步
request.start_async();


	審核編輯：湯梓紅