autopilot/tmp/opi_rtsp/src-onnx/aiengineinferenceonnx.cpp

#include <QDebug>
#include <QThread>
#include "aiengineinferenceonnx.h"


AiEngineInferenceOnnx::AiEngineInferenceOnnx(QString modelPath, QObject *parent)
    : AiEngineInference{modelPath, parent}
{
    //qDebug() << "TUOMAS test mModelPath=" << mModelPath;
    mEngine = new InferenceEngine(modelPath.toStdString());
}


void AiEngineInferenceOnnx::performInferenceSlot(cv::Mat frame)
{
    //qDebug() << "performInferenceSlot() in thread: " << QThread::currentThreadId();

    mActive = true;

    int orig_width                         = frame.cols;
    int orig_height                        = frame.rows;
    std::vector<float> input_tensor_values = mEngine->preprocessImage(frame);
    std::vector<float> results             = mEngine->runInference(input_tensor_values);
    float confidence_threshold             = 0.4;
    std::vector<Detection> detections      = mEngine->filterDetections(results, confidence_threshold, mEngine->input_shape[2], mEngine->input_shape[3], orig_width, orig_height);

    AiEngineInferenceResult result;
    for (uint32_t i = 0; i < detections.size(); i++) {
        const Detection &detection = detections[i];

        AiEngineObject object;
        object.classId          = detection.class_id;
        object.propability      = detection.confidence;
        object.rectangle.top    = detection.bbox.y;
        object.rectangle.left   = detection.bbox.x;
        object.rectangle.bottom = detection.bbox.y + detection.bbox.height;
        object.rectangle.right  = detection.bbox.x + detection.bbox.width;
        result.objects.append(object);
    }

    result.frame = mEngine->draw_labels(frame.clone(), detections);
    emit resultsReady(result);

    mActive = false;
}