Untitled

void ObjectDetector::detect(cv::Mat& image, bool showConf) {
	cv::Mat copy = image;

	// Convert the image to grayscale
	cv::cvtColor(copy, copy, cv::COLOR_BGR2GRAY);

	// Apply a Gaussian filter for denoising
	//cv::GaussianBlur(copy, copy, cv::Size(5, 5), 0);

	// Enhance the image contrast
	cv::equalizeHist(copy, copy);

	// Resize the image to increase speed
	//cv::resize(copy, copy, cv::Size(), 0.5, 0.5, cv::INTER_LANCZOS4);

	// Convert resized image to BGR for compatibility
	cv::cvtColor(copy, copy, cv::COLOR_BGRA2BGR);

	// Create a blob from the normalized image
	cv::Mat blob = cv::dnn::blobFromImage(copy);
	
	std::vector<std::string> layers = model.getLayerNames();

	model.setInput(blob);
	try {
		/*
		In Debug mode, the forward method requires a string argument representing the layer,
		otherwise it throws a fatal exception and the whole app crashes.
		In Release mode, it automatically chooses the right layer
		*/
#ifdef NDEBUG
		blob = model.forward();
#else
		blob = model.forward("layer");
#endif
	}
	catch (const std::exception& e) {
		std::cout << e.what() << std::endl;
		std::exception ex("No valid layer was provided to model.forward(). This would happen if the application is run in Debug mode.");
		throw ex;
		return;
	}

	detectionMat = cv::Mat(blob.size[2], blob.size[3], CV_32F, blob.ptr<float>());

	for (int i = 0; i < detectionMat.rows; i++) {
		int classId = detectionMat.at<float>(i, 1);
		float confidence = detectionMat.at<float>(i, 2);

		if (confidence > minConfidence && classNames[classId - 1].second) {
			int box_x = (int)(detectionMat.at<float>(i, 3) * image.cols);
			int box_y = (int)(detectionMat.at<float>(i, 4) * image.rows);
			int box_width = (int)(detectionMat.at<float>(i, 5) * image.cols - box_x);
			int box_height = (int)(detectionMat.at<float>(i, 6) * image.rows - box_y);
			lastRect = cv::Rect(box_x, box_y, box_width, box_height);

			currentClassName = classNames[classId - 1].first.c_str();
			std::stringstream ss;
			ss << currentClassName;
			if (showConf)
				ss << ": confidence = " + std::to_string((int)(confidence * 100)) + "%";
			drawLabel(image, ss.str(), lastRect);
		}
	}
	cv::cvtColor(image, image, cv::COLOR_BGRA2BGR);
}