mirror of
https://github.com/azaion/autopilot.git
synced 2026-04-22 08:26:33 +00:00
Tuomas Järvinen
e3643ea622
- removed QtSerialPort from the Qt CONFIG parameters - remove compiler warnings - reduced logging - fixed FPS to show what AI really analyzed - RTSP reader tries to connect to the stream once per second until it succeeds
124 lines
3.7 KiB
C++
124 lines
3.7 KiB
C++
#include <QDebug>
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#include <opencv2/highgui.hpp>
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#include "aiengine.h"
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#include "aiengineinference.h"
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#ifdef SAVE_IMAGES
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#include "aiengineimagesaver.h"
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#endif
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#if defined(OPI5_BUILD)
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#include "src-opi5/aiengineinferenceopi5.h"
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#elif defined(OPENCV_BUILD)
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#include "src-opencv-onnx/aiengineinferenceopencvonnx.h"
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#elif defined(NCNN_BUILD)
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#include "src-ncnn/aiengineinferencencnn.h"
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#else
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#include "src-onnx-runtime/aiengineinferenceonnxruntime.h"
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#endif
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AiEngine::AiEngine(QString modelPath, QObject *parent) :
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QObject{parent},
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mRtspFrameCounter(0),
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mInferenceFrameCounter(0)
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{
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mRtspListener = new AiEngineRtspListener(this);
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connect(mRtspListener, &AiEngineRtspListener::frameReceived, this, &AiEngine::frameReceivedSlot);
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#if defined(OPI5_BUILD)
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mInference = new AiEngineInferenceOpi5(modelPath);
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mInference->initialize(0);
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mInference2 = new AiEngineInferenceOpi5(modelPath);
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mInference2->initialize(1);
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mInference3 = new AiEngineInferenceOpi5(modelPath);
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mInference3->initialize(2);
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#elif defined(OPENCV_BUILD)
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mInference = new AiEngineInferenceOpencvOnnx(modelPath);
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#elif defined(NCNN_BUILD)
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mInference = new AiEngineInferencevNcnn(modelPath);
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#else
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mInference = new AiEngineInferencevOnnxRuntime(modelPath);
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#endif
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QThread *inferenceThread = new QThread(this);
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mInference->moveToThread(inferenceThread);
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connect(mInference, &AiEngineInference::resultsReady, this, &AiEngine::inferenceResultsReceivedSlot, Qt::QueuedConnection);
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connect(this, &AiEngine::inferenceFrame, mInference, &AiEngineInference::performInferenceSlot, Qt::QueuedConnection);
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inferenceThread->start();
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#ifdef OPI5_BUILD
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QThread *inferenceThread2 = new QThread(this);
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mInference2->moveToThread(inferenceThread2);
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connect(mInference2, &AiEngineInference::resultsReady, this, &AiEngine::inferenceResultsReceivedSlot, Qt::QueuedConnection);
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connect(this, &AiEngine::inferenceFrame2, mInference2, &AiEngineInference::performInferenceSlot, Qt::QueuedConnection);
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inferenceThread2->start();
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QThread *inferenceThread3 = new QThread(this);
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mInference3->moveToThread(inferenceThread3);
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connect(mInference3, &AiEngineInference::resultsReady, this, &AiEngine::inferenceResultsReceivedSlot, Qt::QueuedConnection);
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connect(this, &AiEngine::inferenceFrame3, mInference3, &AiEngineInference::performInferenceSlot, Qt::QueuedConnection);
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inferenceThread3->start();
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#endif
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#ifdef GIMBAL
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mGimbalClient = new AiEngineGimbalClient(this);
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#else
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mGimbalClient = nullptr;
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#endif
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}
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void AiEngine::start(void)
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{
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mRtspListener->startListening();
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mRtspElapsedTimer.start();
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}
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void AiEngine::stop(void)
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{
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mRtspListener->stopListening();
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}
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void AiEngine::inferenceResultsReceivedSlot(AiEngineInferenceResult result)
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{
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mInferenceFrameCounter++;
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float fps =mRtspElapsedTimer.elapsed() == 0 ? 0 : (mInferenceFrameCounter / (mRtspElapsedTimer.elapsed()/1000.0f));
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printf("Analyzed %d/%d frames with AI. FPS=%.1f\n", mInferenceFrameCounter, mRtspFrameCounter, fps);
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if (mGimbalClient != nullptr) {
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mGimbalClient->inferenceResultSlot(result);
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}
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cv::imshow("AI Engine", result.frame);
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#ifdef SAVE_IMAGES
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static int imageCounter = 0;
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AiEngineImageSaver *saver = new AiEngineImageSaver(result.frame, ++imageCounter);
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saver->start();
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connect(saver, &AiEngineImageSaver::finished, saver, &QObject::deleteLater);
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#endif
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}
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void AiEngine::frameReceivedSlot(cv::Mat frame)
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{
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mRtspFrameCounter++;
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if (mInference->isActive() == false) {
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emit inferenceFrame(frame);
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}
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#ifdef OPI5_BUILD
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else if (mInference2->isActive() == false) {
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emit inferenceFrame2(frame);
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}
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else if (mInference3->isActive() == false) {
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emit inferenceFrame3(frame);
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}
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#endif
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}
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