Renamed opi_player as rtsp_ai_player

2026-04-22 10:26:35 +00:00 · 2024-07-14 19:52:45 +02:00
parent 813251b170
commit 8a7d681e5b
40 changed files with 43 additions and 0 deletions
@@ -0,0 +1,97 @@
+#include <QDebug>
+#include <QThread>
+#include <vector>
+#include "aiengineinferenceonnxruntime.h"
+
+
+static const float confThreshold = 0.4f;
+static const float iouThreshold  = 0.4f;
+static const float maskThreshold = 0.5f;
+
+
+AiEngineInferencevOnnxRuntime::AiEngineInferencevOnnxRuntime(QString modelPath, QObject *parent) :
+    AiEngineInference{modelPath, parent},
+    mPredictor(modelPath.toStdString(), confThreshold, iouThreshold, maskThreshold)
+{
+    qDebug() << "TUOMAS AiEngineInferencevOnnxRuntime() mModelPath=" << mModelPath;
+
+    mClassNames = {
+        "Armoured vehicle",
+        "Truck",
+        "Vehicle",
+        "Artillery",
+        "Shadow artillery",
+        "Trenches",
+        "Military man",
+        "Tyre tracks",
+        "Additional protection tank",
+        "Smoke"
+    };
+}
+
+
+cv::Mat AiEngineInferencevOnnxRuntime::drawLabels(const cv::Mat &image, const std::vector<Yolov8Result> &detections)
+{
+    cv::Mat result = image.clone();
+
+    for (const auto &detection : detections)
+    {
+        cv::rectangle(result, detection.box, cv::Scalar(0, 255, 0), 2);
+        std::string label = mClassNames[detection.classId] + ": " + std::to_string(detection.conf);
+
+        int baseLine;
+        cv::Size labelSize = cv::getTextSize(label, cv::FONT_HERSHEY_SIMPLEX, 0.5, 1, &baseLine);
+
+        cv::rectangle(
+            result,
+            cv::Point(detection.box.x, detection.box.y - labelSize.height),
+            cv::Point(detection.box.x + labelSize.width, detection.box.y + baseLine),
+            cv::Scalar(255, 255, 255),
+            cv::FILLED);
+
+        cv::putText(
+            result,
+            label,
+            cv::Point(
+                detection.box.x,
+                detection.box.y),
+            cv::FONT_HERSHEY_SIMPLEX,
+            0.5,
+            cv::Scalar(0, 0, 0),
+            1);
+    }
+
+    return result;
+}
+
+
+void AiEngineInferencevOnnxRuntime::performInferenceSlot(cv::Mat frame)
+{
+    mActive = true;
+
+    cv::Mat scaledImage                  = resizeAndPad(frame);
+    std::vector<Yolov8Result> detections = mPredictor.predict(scaledImage);
+    AiEngineInferenceResult result;
+
+    for (uint i = 0; i < detections.size(); i++) {
+        const Yolov8Result &detection = detections[i];
+
+        // Add detected objects to the results
+        AiEngineObject object;
+        object.classId          = detection.classId;
+        object.propability      = detection.conf;
+        object.rectangle.top    = detection.box.y;
+        object.rectangle.left   = detection.box.x;
+        object.rectangle.bottom = detection.box.y + detection.box.height;
+        object.rectangle.right  = detection.box.x + detection.box.width;
+        result.objects.append(object);
+    }
+
+    if (result.objects.empty() == false) {
+        qDebug() << __PRETTY_FUNCTION__ << "detections:" << detections.size();
+        result.frame = drawLabels(scaledImage, detections);
+        emit resultsReady(result);
+    }
+
+    mActive = false;
+}