Java如何高效使用OpenCV图像处理库

 public static void processMat(Mat mat){
    byte[] rgb = new byte[3];
    for(int i = 0;i < mat.rows();i++){
        for(int j = 0;j < mat.cols();j++){
            mat.get(i,j,rgb);
            int r = (rgb[2] & 0xff);
            int g = (rgb[1] & 0xff);
            int b = (rgb[0] & 0xff);
            //处理像素RGB值
                    
        }
    }
}

for(int i = 0;i < mat.rows();i++){
    for(int j = 0;j < mat.cols();j++){
    }
}

int rows = mat.rows();
int cols = mat.cols();
for(int i = 0;i < rows;i++){
    for(int j = 0;j < cols;j++){
    }
}

public static void highSpeed(Mat mat){
    int rows = mat.rows();
    int cols = mat.cols();
    int channels = mat.channels();
    //像素数组大小: 行数 * 列数 * 颜色通道数
    byte[] pixels = new byte[rows * cols * channels];
    //通过一次native调用获取整个图片的像素数组
    mat.get(0,0,pixels);
    //遍历像素数组
    int inner = cols * channels;
    for(int i = 0; i < rows; i++){
        for(int j = 0; j < inner; j += channels){
            int index = i * inner + j;
            int r = (pixels[index + 2] & 0xff);
            int g = (pixels[index + 1] & 0xff);
            int b = (pixels[index] & 0xff);
            //处理RGB值
            
        }
    }
}

public static Mat toMat(BufferedImage bi) {
   Mat mat = new Mat(bi.getHeight(), bi.getWidth(), CvType.CV_8UC3);
   mat.put(0, 0, ((DataBufferByte) bi.getRaster().getDataBuffer()).getData());
   return mat;
}
 
public static BufferedImage toBufferedImage(Mat mat){
    int type = BufferedImage.TYPE_BYTE_GRAY;
    if (mat.channels() > 1) {
    	//注意OpenCV的颜色格式是BGR，所以BufferedImage格式也设为BGR
        type = BufferedImage.TYPE_3BYTE_BGR;
    }
    BufferedImage image = new BufferedImage(mat.cols(), mat.rows(), type);
    mat.get(0, 0, ((DataBufferByte)image.getRaster().getDataBuffer()).getData());
    return image;
}

//原始BufferedImage图像
BufferedImage image = 。。。;
//转换成RGB格式
BufferedImage rgb = new BufferedImage(image.getWidth(), image.getHeight(), BufferedImage.TYPE_3BYTE_BGR);
new ColorConvertOp(ColorSpace.getInstance(ColorSpace.CS_sRGB), null).filter(image, rgb);

//配合上面的 toMat() 使用: OpenCV.toMat(screenShot(0,0,100,100));
public static BufferedImage screenshot(int x,int y,int width,int height){
    BufferedImage image = robot.createScreenCapture(new Rectangle(x,y,width,height));
    //转换成RGB格式
    BufferedImage rgb = new BufferedImage(image.getWidth(), image.getHeight(), BufferedImage.TYPE_3BYTE_BGR);
    new ColorConvertOp(ColorSpace.getInstance(ColorSpace.CS_sRGB), null).filter(image, rgb);
    return rgb;
}
//配合上面的 toMat() 使用: OpenCV.toMat(readImageFile(""));
public static BufferedImage readImageFile(String path){
    try {
        BufferedImage image =  ImageIO.read(new BufferedInputStream(new FileInputStream(path)));
        //转换成RGB格式
        BufferedImage rgb = new BufferedImage(image.getWidth(), image.getHeight(), BufferedImage.TYPE_3BYTE_BGR);
        new ColorConvertOp(ColorSpace.getInstance(ColorSpace.CS_sRGB), null).filter(image, rgb);
        return rgb;
    } catch (IOException e) {
        e.printStackTrace();
    }
    return null;
}