Java call ONNX models using ONNXRUNTIME and opencv

Type6test.java

// opencv

import org.opencv.core.Core;
import org.opencv.core.CvType;
import org.opencv.core.Mat;
import org.opencv.core.Size;
import org.opencv.imgproc.Imgproc;
import org.opencv.imgcodecs.Imgcodecs;


// onnxruntime

import ai.onnxruntime.NodeInfo;
import ai.onnxruntime.OnnxTensor;
import ai.onnxruntime.OrtEnvironment;
import ai.onnxruntime.OrtException;
import ai.onnxruntime.OrtSession;
import ai.onnxruntime.OrtSession.Result;
import ai.onnxruntime.OrtSession.SessionOptions;
import ai.onnxruntime.OrtSession.SessionOptions.OptLevel;
import java.io.BufferedReader;
import java.io.FileReader;
import java.io.IOException;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Collections;
import java.util.List;
import java.util.logging.Level;
import java.util.logging.Logger;
import java.util.regex.Pattern;


public class Type6test {
    private static final Logger logger = Logger.getLogger(Type6test.class.getName());
    public static void main(String[] args) throws OrtException, IOException{
        System.out.println("Hello");
        System.loadLibrary(Core.NATIVE_LIBRARY_NAME);

        String file ="face.jpg"; 

        // Imgcodecs imageCodecs = new Imgcodecs();
        // Mat img_bgr = imageCodecs.imread(file);
        Mat img_bgr = Imgcodecs.imread(file);
        Mat img_rgb = new Mat();

        Imgproc.cvtColor(img_bgr, img_rgb, Imgproc.COLOR_BGR2RGB);

        Mat img = new Mat();

        Mat resizeimage = new Mat();
        Size sz = new Size(320, 240); // size is (x, y)
        Imgproc.resize( img_rgb, img, sz );
        

        float[][][][] batch_arr = new float[1][3][240][320];
        
        for(int i=0; i<240; i++){
            for(int j=0; j<320; j++){
                var c = img.get(i, j);
                for(int k=0; k<3;k++){
                    // logger.info(""+ i + ", " + j);
                    batch_arr[0][k][i][j] = (float)(c[k] - 127) / 128;
                }
            }
        }

        logger.info("Data setup finished start to setup ONNXRUNTIME");

        try(OrtEnvironment env = OrtEnvironment.getEnvironment();
            OrtSession.SessionOptions opts = new SessionOptions()){

            opts.setOptimizationLevel(OptLevel.BASIC_OPT);

            try(OrtSession session = env.createSession("updated2_ultra_light_320.onnx", opts)){

                logger.info("Inputs:");
                for (NodeInfo i : session.getInputInfo().values()) {
                    logger.info(i.toString());
                }

                logger.info("Outputs:");
                for (NodeInfo i : session.getOutputInfo().values()) {
                    logger.info(i.toString());
                }

                String inputName = session.getInputNames().iterator().next();

                try(OnnxTensor batch = OnnxTensor.createTensor(env, batch_arr);
                    Result output = session.run(Collections.singletonMap(inputName, batch))){
                    System.out.println("output: " + output);
                }
                logger.info("Done!");
            }
        }
    }

}