Java Imgcodecs.imread方法代码示例

import org.opencv.imgcodecs.Imgcodecs; //导入方法依赖的package包/类
public static void loadImage(String saveRoute, List<Mat> matLists, List<Integer> labels) {
	File saveRoot = new File(saveRoute);
	if(!saveRoot.exists()) {
		LOG.info("图片保存路径--" + saveRoute + "--不存在");
		return;
	}
	if(!saveRoot.isDirectory()) {
		LOG.info("图片路径--" + saveRoute+ "--不是一个文件夹");
		return;
	}
	
	File[] procImages = saveRoot.listFiles(new ImageFileFilter());
	for(int i = 0; i < procImages.length; i ++) {
		LOG.info("加载图片：" + procImages[i].getAbsolutePath());
		Mat m = Imgcodecs.imread(procImages[i].getAbsolutePath(), Imgcodecs.CV_LOAD_IMAGE_GRAYSCALE);
		matLists.add(m);
		labels.add(Integer.parseInt(procImages[i].getName().split("_")[0]));
	}
}
 

import org.opencv.imgcodecs.Imgcodecs; //导入方法依赖的package包/类
public void enhanceImageContrast() {
    Mat source = Imgcodecs.imread("GrayScaleParrot.png",
            Imgcodecs.CV_LOAD_IMAGE_GRAYSCALE);
    Mat destination = new Mat(source.rows(), source.cols(), source.type());
    Imgproc.equalizeHist(source, destination);
    Imgcodecs.imwrite("enhancedParrot.jpg", destination);
}
 

import org.opencv.imgcodecs.Imgcodecs; //导入方法依赖的package包/类
private void processStillImage() {
    Mat mat = Imgcodecs.imread("fly.bmp");
    for (int c = 0; c < mat.width() / 2; c++) {
        for (int r = 0; r < mat.height() / 2; r++) {
            double color[] = mat.get(r, c);
            color[0] = 255;
            mat.put(r, c, color);
            //System.out.printf("(%d, %d) = %s\n", r, c, Arrays.toString(color));
        }
    }
    Imgcodecs.imwrite("fly_new.bmp", mat);

    Mat gray = new Mat();
    Imgproc.cvtColor(mat, gray, Imgproc.COLOR_RGB2GRAY);
    Imgcodecs.imwrite("fly_gray.bmp", gray);
}
 

import org.opencv.imgcodecs.Imgcodecs; //导入方法依赖的package包/类
public static void denoise() {
        String imgInPath = "captchaExample.jpg";
        imgInPath = "MyCaptcha.PNG";
        imgInPath = "blurredtext.jpg";
        String imgOutPath = "captchaNoiseRemovedExample.png";
        imgOutPath = "MyNoiseRemovedCaptcha.PNG";

        Mat image = Imgcodecs.imread(imgInPath);
        Mat out = new Mat();
        Mat tmp = new Mat();
        Mat kernel = new Mat(new Size(3, 3), CvType.CV_8UC1, new Scalar(255));
//        Mat kernel = new Mat(image.size(), CvType.CV_8UC1, new Scalar(255));
        Imgproc.morphologyEx(image, tmp, Imgproc.MORPH_OPEN, kernel);
        Imgproc.morphologyEx(tmp, out, Imgproc.MORPH_CLOSE, kernel);
        Imgcodecs.imwrite(imgOutPath, out);
    }
 

import org.opencv.imgcodecs.Imgcodecs; //导入方法依赖的package包/类
public void run() {
  System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
  String base = "C:/Books in Progress/Java for Data Science/Chapter 10/OpenCVExamples/src/resources";
  CascadeClassifier faceDetector = 
          new CascadeClassifier(base + "/lbpcascade_frontalface.xml");
  
  Mat image = Imgcodecs.imread(base + "/images.jpg");

  MatOfRect faceVectors = new MatOfRect();
  faceDetector.detectMultiScale(image, faceVectors);

  out.println(faceVectors.toArray().length + " faces found");

  for (Rect rect : faceVectors.toArray()) {
      Imgproc.rectangle(image, new Point(rect.x, rect.y), 
              new Point(rect.x + rect.width, rect.y + rect.height), 
              new Scalar(0, 255, 0));
  }
  Imgcodecs.imwrite("faceDetection.png", image);
}
 

import org.opencv.imgcodecs.Imgcodecs; //导入方法依赖的package包/类
/**
 * 
* @Title: processRawImage 
* @Description: 处理原始图片， 对用户上传的人脸图片进行预处理
* @param rawFacePathDir 原始图像的保存根路径(根文件有所有单人的图像，单人图像以注册的手机号为文件夹存储)
* @param processedSavePathDir 处理后要保存的根路径
* @return
* boolean 
 */
public static boolean processRawImage(String rawFacePathDir, String processedSavePathDir, int faceLabel) {
	File rawRoot = new File(rawFacePathDir);
	
	// rawRoot不存在或者不是一个文件夹，返回false
	if(!rawRoot.exists() || !rawRoot.isDirectory()) 
		return false;
	
	//如果输出路径不存在，则创建文件夹
	File outRoot = new File(processedSavePathDir);
	if(!outRoot.exists()) {
		outRoot.mkdirs();
	}
	
	File[] rawImages = rawRoot.listFiles(new ImageFileFilter());
	// 用预处理根路径的文件夹名字作为用户预处理图片的标签
	for(int i = 0; i < rawImages.length; i ++) {
		Mat m = Imgcodecs.imread(rawImages[i].getAbsolutePath(), Imgcodecs.CV_LOAD_IMAGE_GRAYSCALE);
		LOG.info("正在处理:" + rawImages[i]);
		Mat preproc = rawProcessedFace(m);
		if(preproc != null) {
			String filename = processedSavePathDir + File.separator + faceLabel +"_" + (i+1) +".jpg";
			Imgcodecs.imwrite(filename, preproc);
		}
	}
	return true;
}
 

import org.opencv.imgcodecs.Imgcodecs; //导入方法依赖的package包/类
public void processarAlgoritmo(String diretorioImagem, String nomeDaImagem) {
    Mat imagemOriginal = Imgcodecs.imread(diretorioImagem, Imgcodecs.CV_LOAD_IMAGE_GRAYSCALE);
    Mat imagemTratada = new Mat(imagemOriginal.rows(), imagemOriginal.cols(), imagemOriginal.type());
    imagemTratada = imagemOriginal;
    Imgproc.adaptiveThreshold(imagemOriginal, imagemTratada, 500, Imgproc.ADAPTIVE_THRESH_MEAN_C, Imgproc.THRESH_BINARY, 11, 1);
    Imgcodecs.imwrite(System.getProperty("user.home") + "/Desktop/" + nomeDaImagem + ".png", imagemTratada);
}
 

import org.opencv.imgcodecs.Imgcodecs; //导入方法依赖的package包/类
public static void main(String[] args) {
	String opencvDLL = "G:/java/JavaProjectRelease/classchecks/src/main/webapp/WEB-INF/dll/x64/opencv_java320.dll";
	System.load(opencvDLL);
	
	Mat src = Imgcodecs.imread("e:/classchecks/paper/zoudongjun.jpg");//e:/classchecks/Test/13.jpg G:/C++/images/flower3.jpg
	int scaledWidth = 320;
	float scale = src.cols() / (float) scaledWidth;
	Mat resizeMat = resize(src, scale, scaledWidth);
	Imgcodecs.imwrite("e:/classchecks/paper/resize.jpg", resizeMat);
	/*grayEqualizeHist(src);*/
	//unevenLightCompensate(src, 32);
	ImageGui.imshow(resizeMat, "src");
}
 

import org.opencv.imgcodecs.Imgcodecs; //导入方法依赖的package包/类
public void enhanceImageBrightness() {
    double alpha = 1;   // Change to 2 for more brightness
    double beta = 50;
    String fileName = "cat.jpg";

    Mat source = Imgcodecs.imread("cat.jpg");
    Mat destination = new Mat(source.rows(), source.cols(),
            source.type());
    source.convertTo(destination, -1, 1, 50);
    Imgcodecs.imwrite("brighterCat.jpg", destination);
}
 

import org.opencv.imgcodecs.Imgcodecs; //导入方法依赖的package包/类
public static void main(String[] args) throws Exception {
	// 根据系统架构载入dll
	final Properties props = System.getProperties();
	final String bits = String.valueOf(props.get("sun.arch.data.model"));
	System.out.println("System Architecture: " + bits + " bits System");
	if (Integer.parseInt(bits) == 64) {
		System.loadLibrary("opencv_java330_64");
	} else {
		System.loadLibrary("opencv_java330_86");
	}

	// Scanner inputKey = new Scanner(System.in);

	// 欢迎
	System.out.println("Welcome running Classified Project Argus");

	// 载入主封面和初始化主控窗口
	final Mat cover = Imgcodecs.imread(System.getProperty("user.dir") + "/cover.jpg");

	CentralControl.imshow(cover, "SpotSpotter");

	final List<String> oldlist = new ArrayList<String>();

	pilot(oldlist);

	// while (true) {
	// Time.waitFor(100);
	// if (CentralControl.hasWorkDir) {
	// if (CentralControl.ok2Proceed) {
	// FileListener.autoDeepScan(CentralControl.algoIndex);
	// }
	// }
	// }
	// System.exit(0);
}
 

import org.opencv.imgcodecs.Imgcodecs; //导入方法依赖的package包/类
public void processarAlgoritmo(String diretorioImagem, String nomeDaImagem) {
    Mat imagemOpenCV = Imgcodecs.imread(diretorioImagem, Imgcodecs.CV_LOAD_IMAGE_COLOR);
    Mat imagemOpenCVProcessada = this.processarImagem(imagemOpenCV);
    Imgcodecs.imwrite(System.getProperty("user.home") + "/Desktop/" + nomeDaImagem + ".png", imagemOpenCVProcessada);
}
 

import org.opencv.imgcodecs.Imgcodecs; //导入方法依赖的package包/类
public static Mat Pythagoras_G(String input) {
	// public static void main(String[] args) {
	// TODO �Զ����ɵķ������
	// String input =
	// "D:/workspace/SpotSpotter/src/pers/zylo117/spotspotter/image/1.jpg";
	// String output =
	// "D:/workspace/SpotSpotter/src/pers/zylo117/spotspotter/image/output1.jpg";

	final int roiWidth = 20;
	final int roiHeight = 20;
	final int ulx = 206;
	final int uly = 182;
	final int urx = 302;
	final int ury = 182;
	final int llx = 206;
	final int lly = 326;

	System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
	Mat src = Imgcodecs.imread(input);

	// Upper-Left corner
	src = CornerDetector.corners(src, ulx, uly, roiWidth, roiHeight, 10, false);
	// �����Ž�
	upperLeft_optimus();
	// Imgproc.circle(CornerDetector.srcROI, rel_ulPoint, 4, new Scalar(255, 255,
	// 0), 2);
	abs_ulPoint = new org.opencv.core.Point(ulx + rel_ulPoint.x, uly + rel_ulPoint.y);

	// Upper-Right corner
	src = CornerDetector.corners(src, urx, ury, roiWidth, roiHeight, 15, false);
	// �����Ž�
	upperRight_optimus();
	// Imgproc.circle(CornerDetector.srcROI, rel_urPoint, 4, new Scalar(255, 255,
	// 0), 2);
	abs_urPoint = new org.opencv.core.Point(urx + rel_urPoint.x, ury + rel_urPoint.y);

	// Lower-Left corner
	src = CornerDetector.corners(src, llx, lly, roiWidth, roiHeight, 15, false);
	// �����Ž�
	lowerLeft_optimus();
	// Imgproc.circle(CornerDetector.srcROI, rel_llPoint, 4, new Scalar(255, 255,
	// 0), 2);
	abs_llPoint = new org.opencv.core.Point(llx + rel_llPoint.x, lly + rel_llPoint.y);

	// Lower-Right corner
	// abs_lrPoint =FourthCorner.fourthPoint(abs_ulPoint, abs_urPoint, abs_llPoint);
	ROIOutput.abs_lrPoint = FourthCorner.fourthPoint(ROIOutput.abs_ulPoint, ROIOutput.abs_urPoint,
			ROIOutput.abs_llPoint);

	// Imgcodecs.imwrite(output, src);
	return src;

}
 

import org.opencv.imgcodecs.Imgcodecs; //导入方法依赖的package包/类
public static Mat abrirImagem(String path) {
	System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
	return Imgcodecs.imread(path, IMREAD_COLOR);
}
 

import org.opencv.imgcodecs.Imgcodecs; //导入方法依赖的package包/类
public Mat abrirImagem(String path) {
	System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
	return Imgcodecs.imread(path, IMREAD_COLOR);
}