java+opencv+onnx(yolo8)

最新推荐文章于 2024-08-24 16:08:55 发布

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最新推荐文章于 2024-08-24 16:08:55 发布

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文章标签： java opencv 开发语言

本文链接：https://blog.youkuaiyun.com/taoli188/article/details/134720614

版权

本文描述了作者将Python中的YOLOv8模型转换到Java中进行对象检测的过程，涉及ONNX模型读取、图像预处理、网络前向传播、非极大值抑制(NMS)以及结果可视化，展示了在不同语言间迁移的困难和最终实现的成就感。

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	static void dnn(){
		Net net= Dnn.readNetFromONNX("yolov8n.onnx");
		String tempPath = "36.jpg";
		Mat mat = Imgcodecs.imread(tempPath);
		Mat blob = Dnn.blobFromImage(mat, 1/255.0, new Size(640,640));
		net.setInput(blob);
		Mat predict = net.forward();
		Mat mask = predict.reshape(0,1).reshape(0, predict.size(1));
		
		double width = mat.cols() /640.0;
		double height = mat.rows() /640.0;
		Rect2d[] rect2d = new Rect2d[mask.cols()];
		float[] scoref = new float[mask.cols()];
		int[] classid = new int[mask.cols()];
		for (int i = 0; i < mask.cols(); i++) {
			double[] x = mask.col(i).get(0, 0);
			double[] y = mask.col(i).get(1, 0);
			double[] w = mask.col(i).get(2, 0);
			double[] h = mask.col(i).get(3, 0);
			rect2d[i] = new Rect2d((x[0]-w[0]/2)*width, (y[0]-h[0]/2)*height, w[0]*width, h[0]*height);
			Mat score = mask.col(i).submat(4, predict.size(1)-1, 0, 1);
			MinMaxLocResult mmr = Core.minMaxLoc(score);
			scoref[i] = (float)mmr.maxVal;
			classid[i] = (int) mmr.maxLoc.y;
		}
		MatOfRect2d bboxes = new MatOfRect2d(rect2d);
		MatOfFloat scores = new MatOfFloat(scoref);
		MatOfInt indices = new MatOfInt();
		Dnn.NMSBoxes(bboxes, scores, 0.3f, 0.5f, indices);
		List<Integer> result = indices.toList();
		for (Integer integer : result) {
			Imgproc.rectangle(mat, new Rect(rect2d[integer].tl(), rect2d[integer].size()),
		              new Scalar(255, 0, 0), 1);
				Imgproc.putText(mat, classid[integer]+":"+scoref[integer], rect2d[integer].tl(),
                  Imgproc.FONT_HERSHEY_SIMPLEX, 0.5, new Scalar(0, 255, 0));
		}
		OpencvUtil.imshow("展示图片", mat);
	}