Java tutorial
/* * To change this license header, choose License Headers in Project Properties. * To change this template file, choose Tools | Templates * and open the template in the editor. */ package Domain; import java.awt.Canvas; import java.awt.Graphics; import java.awt.image.BufferedImage; import java.io.ByteArrayInputStream; import java.io.File; import java.io.FilenameFilter; import java.io.IOException; import java.io.InputStream; import java.nio.IntBuffer; import javax.imageio.ImageIO; import org.opencv.core.Core; import org.opencv.core.Mat; import org.opencv.core.MatOfByte; import org.opencv.core.MatOfRect; import org.opencv.core.Point; import org.opencv.core.Rect; import org.opencv.core.Scalar; import org.opencv.core.Size; import org.opencv.highgui.Highgui; import org.opencv.highgui.VideoCapture; import org.opencv.imgproc.Imgproc; import org.opencv.objdetect.CascadeClassifier; import static org.bytedeco.javacpp.opencv_contrib.*; import static org.bytedeco.javacpp.opencv_core.*; import static org.bytedeco.javacpp.opencv_highgui.*; import DataAcces.SettingsDAO; import java.util.logging.Level; import java.util.logging.Logger; /** * * @author Gertrude */ public class ImgProcess { public Mat retornaFrame() { System.loadLibrary("opencv_java2410"); /*opencv_java2410*/ VideoCapture camera = new VideoCapture(0);//inicializa com o dispositivo de video #0 camera.open(0); try { Thread.sleep(100);//necessario para a cmera poder ser inicializada } catch (InterruptedException ex) { System.out.printf(ex.getMessage()); } if (camera.isOpened()) { System.out.println("Ta aberto"); } Mat frame = new Mat(); camera.read(frame);//captura o frame atual da cmera System.out.println("Frame adquirido."); camera.release(); return frame; } public Mat DetectarFace(Canvas c, Mat image) throws IOException { System.out.println("Rodando DetectFace"); CascadeClassifier faceDetector = new CascadeClassifier( "C:\\Users\\Gertrude\\Documents\\NetBeansProjects\\OWL_Sight\\src\\Resources\\lbpcascade_frontalface.xml"); // seleciona o classificador para identificao da face MatOfRect faceDetections = new MatOfRect(); //matriz de rectangulos representando os rosto encontrados faceDetector.detectMultiScale(image, faceDetections);//detecta multiplas faces na imagem fornecida System.out.printf("Detected %s faces", faceDetections.toArray().length); Mat corte = null; for (Rect rect : faceDetections.toArray()) { Core.rectangle(image, new Point(rect.x, rect.y), new Point(rect.x + rect.width, rect.y + rect.height), new Scalar(0, 0, 0));// desenha os rectangulos // Highgui.imwrite("C:/TCC-FacialRecognize/src/resources/TESTECORTE.jpg", utl.corte(image, rect)); corte = new Mat(image, rect); } Size sz = new Size(120, 120); MatOfByte bytemat = new MatOfByte(); //transformando a matriz image em uma matriz de bytes para carga no canvas do form principal Highgui.imencode(".jpg", corte, bytemat); byte[] bytes = bytemat.toArray(); InputStream in = new ByteArrayInputStream(bytes); BufferedImage render = ImageIO.read(in); Graphics g = c.getGraphics(); g.drawImage(render, 1, 1, c.getHeight(), c.getWidth(), c); return corte; } public void Treino_Reconhecimento(String root) { String trainingDir = root;// diretorio com as imagens devidamente tratadas e dimensionadas no mesmo tamanho System.out.print("criando diretorio de treino"); File trainDir = new File(trainingDir); //Mahomeno um parse de string pra file FilenameFilter imgFilter; imgFilter = new FilenameFilter() { @Override public boolean accept(File dir, String name) { name = name.toLowerCase(); return name.endsWith(".jpg") || name.endsWith(".pgm") || name.endsWith(".png");// faz tratamento pra retornar soh imagens. } }; File[] imageFiles = trainDir.listFiles(imgFilter);// retorna lista s das imagens MatVector images = new MatVector(imageFiles.length);// cria matriz de imagens com tamanho especfico System.out.print("criando vetor label"); org.bytedeco.javacpp.opencv_core.Mat labels = new org.bytedeco.javacpp.opencv_core.Mat(imageFiles.length, 1, CV_32SC1);// matriz com as etiquetas das imagens, note que o valor de retorno na identificao a etiqueta da imagem correspondente IntBuffer labelsBuf = labels.getIntBuffer(); int counter = 0; for (File image : imageFiles) { org.bytedeco.javacpp.opencv_core.Mat img = imread(image.getAbsolutePath(), CV_LOAD_IMAGE_GRAYSCALE);// l imagem por imagem em escala de cinza System.out.print("Pegando label"); int label = Integer.parseInt(image.getName().split("\\.")[0]);//etiqueta com equivalente numerico do nome da imagem, sim, genial. images.put(counter, img);//seta a imagem com o numero labelsBuf.put(counter, label);//seta a etiqueta com o numero counter++; } FaceRecognizer faceRecognizer = createLBPHFaceRecognizer(); faceRecognizer.train(images, labels);//D xp ao bichinho faceRecognizer.set("threshold", 100); SettingsDAO settings = new SettingsDAO(); faceRecognizer.save(settings.getSettings().getRecogXMLPath() + "\\faceID.xml"); } public FaceRecognizer load() { SettingsDAO settings = new SettingsDAO(); FaceRecognizer fr = createLBPHFaceRecognizer(); fr.load(settings.getSettings().getRecogXMLPath() + "\\faceID.xml"); return fr; } public int Predict(Mat rosto) { SettingsDAO s = new SettingsDAO(); String caminho = s.getSettings().getRecogImageSetPath() + "\\comp\\testcomp.jpg"; Highgui.imwrite(caminho, rosto); try { Thread.sleep(300); } catch (InterruptedException ex) { Logger.getLogger(ImgProcess.class.getName()).log(Level.SEVERE, null, ex); } FaceRecognizer fr; fr = load(); org.bytedeco.javacpp.opencv_core.Mat testImage = imread(caminho, CV_LOAD_IMAGE_GRAYSCALE); int predict = fr.predict(testImage); System.out.println("Predicted label: " + predict); return predict; } }