mirror of
https://github.com/azaion/autopilot.git
synced 2026-04-23 01:46:35 +00:00
Fixed PC build to work with ONNX Yolov10 files
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@@ -47,12 +47,11 @@ void AiEngine::inferenceResultsReceivedSlot(AiEngineInferenceResult result)
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{
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//qDebug() << "AiEngine got inference results in thread: " << QThread::currentThreadId();
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#ifdef OPI5_BUILD
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mGimbalControl->inferenceResultSlot(result);
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cv::imshow("Received Frame", result.frame);
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#endif
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//#ifndef OPI5_BUILD
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//cv::imshow("Received Frame", result.frame);
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//#endif
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cv::imshow("Received Frame", result.frame);
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}
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@@ -5,16 +5,17 @@ PKGCONFIG += opencv4
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MOC_DIR = moc
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OBJECTS_DIR = obj
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SOURCES = $$PWD/*.cpp
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SOURCES = $$PWD/*.cpp $$PWD/../../misc/camera/a8_remote/remoteControl.cpp
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HEADERS = $$PWD/*.h
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INCLUDEPATH += $$PWD/../../misc/camera/a8_remote
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opi5 {
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message("OPI5 build")
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PKGCONFIG += opencv4 librga stb libturbojpeg
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INCLUDEPATH += /usr/include/rga $$PWD/../../misc/camera/a8_remote
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INCLUDEPATH += /usr/include/rga
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QMAKE_CXXFLAGS += -DOPI5_BUILD
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LIBS += /usr/local/lib/librknnrt.so
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SOURCES += $$PWD/src-opi5/*.c $$PWD/src-opi5/*.cpp $$PWD/src-opi5/*.cc $$PWD/../../misc/camera/a8_remote/remoteControl.cpp
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SOURCES += $$PWD/src-opi5/*.c $$PWD/src-opi5/*.cpp $$PWD/src-opi5/*.cc
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HEADERS += $$PWD/src-opi5/*.h
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} else {
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message("ONNX build")
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@@ -2,17 +2,18 @@
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#include <QThread>
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#include "aiengineinferenceonnx.h"
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AiEngineInferenceOnnx::AiEngineInferenceOnnx(QString modelPath, QObject *parent)
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: AiEngineInference{modelPath, parent}
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{
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qDebug() << "TUOMAS test mModelPath=" << mModelPath;
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//qDebug() << "TUOMAS test mModelPath=" << mModelPath;
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mEngine = new InferenceEngine(modelPath.toStdString());
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}
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void AiEngineInferenceOnnx::performInferenceSlot(cv::Mat frame)
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{
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qDebug() << "performInferenceSlot() in thread: " << QThread::currentThreadId();
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//qDebug() << "performInferenceSlot() in thread: " << QThread::currentThreadId();
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mActive = true;
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@@ -20,12 +21,24 @@ void AiEngineInferenceOnnx::performInferenceSlot(cv::Mat frame)
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int orig_height = frame.rows;
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std::vector<float> input_tensor_values = mEngine->preprocessImage(frame);
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std::vector<float> results = mEngine->runInference(input_tensor_values);
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float confidence_threshold = 0.5;
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float confidence_threshold = 0.4;
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std::vector<Detection> detections = mEngine->filterDetections(results, confidence_threshold, mEngine->input_shape[2], mEngine->input_shape[3], orig_width, orig_height);
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AiEngineInferenceResult result;
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for (uint32_t i = 0; i < detections.size(); i++) {
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const Detection &detection = detections[i];
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AiEngineObject object;
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object.classId = detection.class_id;
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object.propability = detection.confidence;
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object.rectangle.top = detection.bbox.y;
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object.rectangle.left = detection.bbox.x;
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object.rectangle.bottom = detection.bbox.y + detection.bbox.height;
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object.rectangle.right = detection.bbox.x + detection.bbox.width;
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result.objects.append(object);
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}
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result.frame = mEngine->draw_labels(frame.clone(), detections);
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result.objects = 1;
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emit resultsReady(result);
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mActive = false;
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