OpenCV4.8 Java SDK实现YOLOv5模型部署

OpenCV Java开发环境配置

Java 开发的IDE，推荐选择IDEA这个，真的比较好用，我下载的是社区版，免费可用。

安装好以后直接点击打开，选择 New Project

添加本地的OpenCV Java SDK的 Jar文件依赖包 从Project Structure到 Modules 到 Module SDK 添加Jars or Dependence

OpenCV Java 代码测试

OpenCV Java配置好以后，测试代码首先需要加载DLL，然后依赖Java SDK，可以实现图像加载与显示。测试代码如下：

package org.example;


import org.opencv.core.*;
import org.opencv.highgui.HighGui;
import org.opencv.imgcodecs.Imgcodecs;




//TIP To Run code, press  or
// click the  icon in the gutter.
public class YOLOv5DNNDetector {
    public static void main(String[] args) {
        System.load("D:/opencv-4.8.0/opencv/build/java/x64/opencv_java480.dll");
        System.out.println("start to read image...");
        Mat inputImage = Imgcodecs.imread("D:/images/lena.jpg");
        HighGui.imshow("Java OpenCV开发测试", inputImage);
        HighGui.waitKey(0);
        HighGui.destroyAllWindows();
        System.exit(0);
    }
}

运行结果如下：

YOLOv5模型部署

基于YOLOv5 7.0版本，完成了对象检测

publicstaticvoidmain(String[]args){

System.load("D:/opencv-4.8.0/opencv/build/java/x64/opencv_java480.dll");
System.out.println("starttoreadimage...");
Stringfile_path="D:/python/yolov5-7.0/classes.txt";
try{
MatinputImage=Imgcodecs.imread("D:/bird_test/city-walk.jpg");
java.util.ArrayListboxes=newArrayList<>();
FileInputStreamfis=newFileInputStream(file_path);
BufferedReaderbr=newBufferedReader(newInputStreamReader(fis));
YOLOv5DNNDetectordetector=newYOLOv5DNNDetector("D:/python/yolov5-7.0/yolov5s.onnx",0.5f,0.5f,640,640);
Stringline;
ArrayListmap_labels=newArrayList<>();
while((line=br.readLine())!=null){
map_labels.add(line);
}
detector.addAllLabels(map_labels);
detector.infer_image(inputImage,boxes);
HighGui.imshow("OpenCV4.8forJavaYOLOv5对象检测演示",inputImage);
HighGui.waitKey(0);
HighGui.destroyAllWindows();
}catch(Exceptione){
e.printStackTrace();
}
System.exit(0);
}