Chaneges to opi_rtsp test application

- refactoring - can use normal YOLOv8 files converted to ONNX format - does not work with azaion ONNX files!
2026-04-23 00:26:33 +00:00 · 2024-07-10 19:53:19 +02:00
parent 3d39d8fd99
commit 683f2d538b
6 changed files with 13 additions and 24 deletions
@@ -0,0 +1,93 @@
+#include <QDebug>
+#include <QThread>
+#include "aiengineinferenceopencvonnx.h"
+
+
+const int INFERENCE_SQUARE_WIDTH  = 640;
+const int INFERENCE_SQUARE_HEIGHT = 640;
+
+
+AiEngineInferenceOpencvOnnx::AiEngineInferenceOpencvOnnx(QString modelPath, QObject *parent)
+    : AiEngineInference{modelPath, parent},
+      mInference(modelPath.toStdString(), cv::Size(640, 640), "classes.txt")
+{
+    //qDebug() << "TUOMAS test mModelPath=" << mModelPath;
+    //mEngine = new InferenceEngine(modelPath.toStdString());
+    //mInference = new Inference(modelPath.toStdString(), cv::Size(INFERENCE_SQUARE_WIDTH, INFERENCE_SQUARE_HEIGHT), "classes.txt");
+}
+
+
+cv::Mat resizeAndPad(const cv::Mat& src)
+{
+    // Calculate the aspect ratio
+    float aspectRatio = static_cast<float>(src.cols) / src.rows;
+
+    // Determine new size while maintaining aspect ratio
+    int newWidth = src.cols;
+    int newHeight = src.rows;
+    if (src.cols > INFERENCE_SQUARE_WIDTH || src.rows > INFERENCE_SQUARE_HEIGHT) {
+        if (aspectRatio > 1)
+        {
+            // Width is greater than height
+            newWidth = INFERENCE_SQUARE_WIDTH;
+            newHeight = static_cast<int>(INFERENCE_SQUARE_WIDTH / aspectRatio);
+        }
+        else {
+            // Height is greater than or equal to width
+            newHeight = INFERENCE_SQUARE_HEIGHT;
+            newWidth = static_cast<int>(INFERENCE_SQUARE_HEIGHT * aspectRatio);
+        }
+    }
+
+    // Resize the original image if needed
+    cv::Mat resized;
+    cv::resize(src, resized, cv::Size(newWidth, newHeight));
+
+    // Create a new 640x640 image with a black background
+    cv::Mat output(INFERENCE_SQUARE_HEIGHT, INFERENCE_SQUARE_WIDTH, src.type(), cv::Scalar(0, 0, 0));
+
+    // Copy the resized image to the top-left corner of the new image
+    resized.copyTo(output(cv::Rect(0, 0, resized.cols, resized.rows)));
+
+    return output;
+}
+
+
+void AiEngineInferenceOpencvOnnx::performInferenceSlot(cv::Mat frame)
+{
+    try {
+        //qDebug() << "performInferenceSlot() in thread: " << QThread::currentThreadId();
+
+        mActive = true;
+
+        cv::Mat scaledImage               = resizeAndPad(frame);
+        std::vector<Detection> detections = mInference.runInference(scaledImage);
+        AiEngineInferenceResult result;
+
+        //qDebug() << "performInferenceSlot() found " << detections.size() << " objects";
+
+        for (uint i = 0; i < detections.size(); ++i) {
+            const Detection &detection = detections[i];
+
+            // Add detected objects to the results
+            AiEngineObject object;
+            object.classId          = detection.class_id;
+            object.propability      = detection.confidence;
+            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) {
+            result.frame = mInference.drawLabels(scaledImage, detections);
+            emit resultsReady(result);
+        }
+
+        mActive = false;
+    }
+    catch (const cv::Exception& e) {
+        std::cerr << "performInferenceSlot() Error: " << e.what() << std::endl;
+    }
+}