Add functionality to save inference images for the debugging purposes.

Save bmp images of inference results to /tmp as bmp files. BMP was
chosen to reduce encoding time. Saving is fully threaded. It can be
enable with qmake CONFIG+=save_images option

Also:
  - use antialised fonts in RKNN inference
  - moved class strings to inference base class
  - fixed silly segfault in ONNX inference
  - prevent writing results if class if exceeds valid values

Issue: https://denyspopov.atlassian.net/browse/AZ-38
Type: Improvement

misc/rtsp_ai_player/src-onnx-runtime/aiengineinferenceonnxruntime.cpp

@@ -14,104 +14,7 @@ AiEngineInferencevOnnxRuntime::AiEngineInferencevOnnxRuntime(QString modelPath,
     mPredictor(modelPath.toStdString(), confThreshold, iouThreshold, maskThreshold)
 {
     qDebug() << "TUOMAS AiEngineInferencevOnnxRuntime() mModelPath=" << mModelPath;
-
-#ifdef YOLO_ONNX
-    mClassNames = {
-        "person",
-        "bicycle",
-        "car",
-        "motorcycle",
-        "airplane",
-        "bus",
-        "train",
-        "truck",
-        "boat",
-        "traffic light",
-        "fire hydrant",
-        "stop sign",
-        "parking meter",
-        "bench",
-        "bird",
-        "cat",
-        "dog",
-        "horse",
-        "sheep",
-        "cow",
-        "elephant",
-        "bear",
-        "zebra",
-        "giraffe",
-        "backpack",
-        "umbrella",
-        "handbag",
-        "tie",
-        "suitcase",
-        "frisbee",
-        "skis",
-        "snowboard",
-        "sports ball",
-        "kite",
-        "baseball bat",
-        "baseball glove",
-        "skateboard",
-        "surfboard",
-        "tennis racket",
-        "bottle",
-        "wine glass",
-        "cup",
-        "fork",
-        "knife",
-        "spoon",
-        "bowl",
-        "banana",
-        "apple",
-        "sandwich",
-        "orange",
-        "broccoli",
-        "carrot",
-        "hot dog",
-        "pizza",
-        "donut",
-        "cake",
-        "chair",
-        "couch",
-        "potted plant",
-        "bed",
-        "dining table",
-        "toilet",
-        "tv",
-        "laptop",
-        "mouse",
-        "remote",
-        "keyboard",
-        "cell phone",
-        "microwave",
-        "oven",
-        "toaster",
-        "sink",
-        "refrigerator",
-        "book",
-        "clock",
-        "vase",
-        "scissors",
-        "teddy bear",
-        "hair drier",
-        "toothbrush"
-    };
-#else
-    mClassNames = {
-        "Armoured vehicle",
-        "Truck",
-        "Vehicle",
-        "Artillery",
-        "Shadow artillery",
-        "Trenches",
-        "Military man",
-        "Tyre tracks",
-        "Additional protection tank",
-        "Smoke"
-    };
-#endif
+    qDebug() << "AiEngineInferencevOnnxRuntime() mClassNames.size() =" << mClassNames.size();
 }
 
 
@@ -183,6 +86,11 @@ void AiEngineInferencevOnnxRuntime::performInferenceSlot(cv::Mat frame)
         for (uint i = 0; i < detections.size(); i++) {
             const Yolov8Result &detection = detections[i];
 
+            if (detection.classId >= mClassNames.size()) {
+                qDebug() << "performInferenceSlot() invalid classId =" << detection.classId;
+                continue;
+            }
+
             // Add detected objects to the results
             AiEngineObject object;
             object.classId          = detection.classId;

misc/rtsp_ai_player/src-onnx-runtime/aiengineinferenceonnxruntime.h

@@ -17,5 +17,4 @@ public slots:
 private:
     cv::Mat drawLabels(const cv::Mat &image, const std::vector<Yolov8Result> &detections);
     YOLOPredictor mPredictor;
-    QVector<QString> mClassNames;
 };