This guide covers building a complete face detection desktop application using Java with OpenCV, JavaFX, and computer vision capabilities.

Project Setup and Dependencies

Step 1: Maven Configuration

<?xml version="1.0" encoding="UTF-8"?> <project> <properties> <maven.compiler.source>17</maven.compiler.source> <maven.compiler.target>17</maven.compiler.target> <javafx.version>21</javafx.version> <opencv.version>4.8.0</opencv.version> </properties> <dependencies> <!-- JavaFX --> <dependency> <groupId>org.openjfx</groupId> <artifactId>javafx-controls</artifactId> <version>${javafx.version}</version> </dependency> <dependency> <groupId>org.openjfx</groupId> <artifactId>javafx-fxml</artifactId> <version>${javafx.version}</version> </dependency> <dependency> <groupId>org.openjfx</groupId> <artifactId>javafx-swing</artifactId> <version>${javafx.version}</version> </dependency> <!-- OpenCV --> <dependency> <groupId>org.openpnp</groupId> <artifactId>opencv</artifactId> <version>${opencv.version}</version> </dependency> <!-- Image Processing --> <dependency> <groupId>com.twelvemonkeys.imageio</groupId> <artifactId>imageio-core</artifactId> <version>3.9.4</version> </dependency> <dependency> <groupId>com.twelvemonkeys.imageio</groupId> <artifactId>imageio-jpeg</artifactId> <version>3.9.4</version> </dependency> <!-- Utilities --> <dependency> <groupId>com.fasterxml.jackson.core</groupId> <artifactId>jackson-databind</artifactId> <version>2.15.2</version> </dependency> <!-- Logging --> <dependency> <groupId>org.slf4j</groupId> <artifactId>slf4j-api</artifactId> <version>2.0.7</version> </dependency> <dependency> <groupId>ch.qos.logback</groupId> <artifactId>logback-classic</artifactId> <version>1.4.8</version> </dependency> </dependencies> <build> <plugins> <plugin> <groupId>org.openjfx</groupId> <artifactId>javafx-maven-plugin</artifactId> <version>0.0.8</version> <configuration> <mainClass>com.example.facedetection.MainApp</mainClass> </configuration> </plugin> <plugin> <groupId>org.apache.maven.plugins</groupId> <artifactId>maven-resources-plugin</artifactId> <version>3.3.1</version> <configuration> <encoding>UTF-8</encoding> </configuration> </plugin> </plugins> </build> </project>

Core Face Detection Engine

Step 2: OpenCV Face Detection Service

package com.example.facedetection.core; import org.opencv.core.*; import org.opencv.imgproc.Imgproc; import org.opencv.objdetect.CascadeClassifier; import org.opencv.videoio.VideoCapture; import org.opencv.videoio.Videoio; import javax.imageio.ImageIO; import java.awt.image.BufferedImage; import java.io.ByteArrayInputStream; import java.io.File; import java.io.IOException; import java.io.InputStream; import java.util.ArrayList; import java.util.List; public class FaceDetectionService { private CascadeClassifier faceClassifier; private CascadeClassifier eyeClassifier; private CascadeClassifier smileClassifier; private static FaceDetectionService instance; public static synchronized FaceDetectionService getInstance() { if (instance == null) { instance = new FaceDetectionService(); } return instance; } private FaceDetectionService() { initializeOpenCV(); loadClassifiers(); } private void initializeOpenCV() { try { // Load OpenCV native library nu.pattern.OpenCV.loadLocally(); System.out.println("OpenCV loaded successfully: " + Core.VERSION); } catch (Exception e) { System.err.println("Failed to load OpenCV: " + e.getMessage()); throw new RuntimeException("OpenCV initialization failed", e); } } private void loadClassifiers() { try { // Load Haar cascade classifiers String basePath = "src/main/resources/haarcascades/"; // Face detector faceClassifier = new CascadeClassifier(); if (!faceClassifier.load(basePath + "haarcascade_frontalface_default.xml")) { // Try loading from classpath as fallback faceClassifier.load(getClass().getResource("/haarcascades/haarcascade_frontalface_default.xml").getPath()); } // Eye detector eyeClassifier = new CascadeClassifier(); if (!eyeClassifier.load(basePath + "haarcascade_eye.xml")) { eyeClassifier.load(getClass().getResource("/haarcascades/haarcascade_eye.xml").getPath()); } // Smile detector smileClassifier = new CascadeClassifier(); if (!smileClassifier.load(basePath + "haarcascade_smile.xml")) { smileClassifier.load(getClass().getResource("/haarcascades/haarcascade_smile.xml").getPath()); } System.out.println("All classifiers loaded successfully"); } catch (Exception e) { System.err.println("Failed to load classifiers: " + e.getMessage()); throw new RuntimeException("Classifier loading failed", e); } } public DetectionResult detectFaces(Mat image) { return detectFaces(image, true, true, true); } public DetectionResult detectFaces(Mat image, boolean detectEyes, boolean detectSmiles, boolean drawAnnotations) { List<Rect> faces = new ArrayList<>(); List<Rect> eyes = new ArrayList<>(); List<Rect> smiles = new ArrayList<>(); Mat processedImage = image.clone(); Mat grayImage = new Mat(); try { // Convert to grayscale for better detection if (processedImage.channels() > 1) { Imgproc.cvtColor(processedImage, grayImage, Imgproc.COLOR_BGR2GRAY); } else { grayImage = processedImage; } // Equalize histogram to improve contrast Imgproc.equalizeHist(grayImage, grayImage); // Detect faces MatOfRect faceDetections = new MatOfRect(); faceClassifier.detectMultiScale( grayImage, faceDetections, 1.1, // scale factor 3, // min neighbors 0, // flags new Size(30, 30), // min size new Size(500, 500) // max size ); faces = faceDetections.toList(); // Detect eyes and smiles within each face for (Rect face : faces) { Mat faceROI = grayImage.submat(face); if (detectEyes) { MatOfRect eyeDetections = new MatOfRect(); eyeClassifier.detectMultiScale( faceROI, eyeDetections, 1.1, 2, 0, new Size(20, 20), new Size(80, 80) ); for (Rect eye : eyeDetections.toList()) { Rect absoluteEye = new Rect( face.x + eye.x, face.y + eye.y, eye.width, eye.height ); eyes.add(absoluteEye); } } if (detectSmiles) { MatOfRect smileDetections = new MatOfRect(); smileClassifier.detectMultiScale( faceROI, smileDetections, 1.8, 20, 0, new Size(25, 15), new Size(100, 50) ); for (Rect smile : smileDetections.toList()) { Rect absoluteSmile = new Rect( face.x + smile.x, face.y + smile.y, smile.width, smile.height ); smiles.add(absoluteSmile); } } } // Draw annotations if requested if (drawAnnotations) { drawDetectionAnnotations(processedImage, faces, eyes, smiles); } return new DetectionResult(processedImage, faces, eyes, smiles); } finally { grayImage.release(); } } private void drawDetectionAnnotations(Mat image, List<Rect> faces, List<Rect> eyes, List<Rect> smiles) { // Draw face rectangles (blue) for (Rect face : faces) { Imgproc.rectangle( image, new Point(face.x, face.y), new Point(face.x + face.width, face.y + face.height), new Scalar(255, 0, 0), // Blue 3 ); // Add face label Imgproc.putText( image, "Face", new Point(face.x, face.y - 10), Imgproc.FONT_HERSHEY_SIMPLEX, 0.8, new Scalar(255, 0, 0), 2 ); } // Draw eye circles (green) for (Rect eye : eyes) { Point center = new Point(eye.x + eye.width / 2, eye.y + eye.height / 2); int radius = (int) Math.round((eye.width + eye.height) * 0.25); Imgproc.circle( image, center, radius, new Scalar(0, 255, 0), // Green 2 ); } // Draw smile rectangles (red) for (Rect smile : smiles) { Imgproc.rectangle( image, new Point(smile.x, smile.y), new Point(smile.x + smile.width, smile.y + smile.height), new Scalar(0, 0, 255), // Red 2 ); } } public BufferedImage matToBufferedImage(Mat mat) { try { MatOfByte mob = new MatOfByte(); Imgproc.cvtColor(mat, mat, Imgproc.COLOR_BGR2RGB); Imgcodecs.imencode(".jpg", mat, mob); byte[] byteArray = mob.toArray(); InputStream in = new ByteArrayInputStream(byteArray); return ImageIO.read(in); } catch (IOException e) { throw new RuntimeException("Failed to convert Mat to BufferedImage", e); } } public Mat bufferedImageToMat(BufferedImage image) { try { Mat mat = new Mat(image.getHeight(), image.getWidth(), CvType.CV_8UC3); byte[] data = ((java.awt.image.DataBufferByte) image.getRaster().getDataBuffer()).getData(); mat.put(0, 0, data); return mat; } catch (Exception e) { throw new RuntimeException("Failed to convert BufferedImage to Mat", e); } } public static class DetectionResult { private final Mat processedImage; private final List<Rect> faces; private final List<Rect> eyes; private final List<Rect> smiles; public DetectionResult(Mat processedImage, List<Rect> faces, List<Rect> eyes, List<Rect> smiles) { this.processedImage = processedImage; this.faces = faces; this.eyes = eyes; this.smiles = smiles; } // Getters public Mat getProcessedImage() { return processedImage; } public List<Rect> getFaces() { return faces; } public List<Rect> getEyes() { return eyes; } public List<Rect> getSmiles() { return smiles; } public int getFaceCount() { return faces.size(); } public int getEyeCount() { return eyes.size(); } public int getSmileCount() { return smiles.size(); } } }

Webcam Capture Service

Step 3: Real-time Camera Integration

package com.example.facedetection.core; import org.opencv.core.Mat; import org.opencv.videoio.VideoCapture; import org.opencv.videoio.Videoio; import javafx.animation.AnimationTimer; import javafx.scene.image.Image; import javafx.scene.image.ImageView; import java.awt.image.BufferedImage; import java.util.concurrent.atomic.AtomicBoolean; public class WebcamService { private VideoCapture capture; private AtomicBoolean isRunning; private FaceDetectionService faceDetector; private int cameraIndex; public WebcamService() { this(0); // Default camera } public WebcamService(int cameraIndex) { this.cameraIndex = cameraIndex; this.isRunning = new AtomicBoolean(false); this.faceDetector = FaceDetectionService.getInstance(); initializeCamera(); } private void initializeCamera() { try { capture = new VideoCapture(cameraIndex); if (!capture.isOpened()) { throw new RuntimeException("Cannot open camera: " + cameraIndex); } // Set camera properties capture.set(Videoio.CAP_PROP_FRAME_WIDTH, 640); capture.set(Videoio.CAP_PROP_FRAME_HEIGHT, 480); capture.set(Videoio.CAP_PROP_FPS, 30); System.out.println("Camera initialized: " + cameraIndex); System.out.println("Resolution: " + capture.get(Videoio.CAP_PROP_FRAME_WIDTH) + "x" + capture.get(Videoio.CAP_PROP_FRAME_HEIGHT)); System.out.println("FPS: " + capture.get(Videoio.CAP_PROP_FPS)); } catch (Exception e) { throw new RuntimeException("Failed to initialize camera: " + e.getMessage(), e); } } public void startCapture(ImageView imageView, boolean detectFaces) { if (isRunning.get()) { return; } isRunning.set(true); AnimationTimer timer = new AnimationTimer() { @Override public void handle(long now) { if (!isRunning.get()) { this.stop(); return; } Mat frame = new Mat(); if (capture.read(frame)) { if (!frame.empty()) { try { Mat processedFrame; if (detectFaces) { FaceDetectionService.DetectionResult result = faceDetector.detectFaces(frame, true, true, true); processedFrame = result.getProcessedImage(); } else { processedFrame = frame; } // Convert to JavaFX Image BufferedImage bufferedImage = faceDetector.matToBufferedImage(processedFrame); Image fxImage = convertToFxImage(bufferedImage); // Update ImageView on JavaFX thread javafx.application.Platform.runLater(() -> { imageView.setImage(fxImage); }); processedFrame.release(); } catch (Exception e) { System.err.println("Error processing frame: " + e.getMessage()); } } frame.release(); } else { System.err.println("Failed to capture frame"); this.stop(); } } }; timer.start(); } public void stopCapture() { isRunning.set(false); } public Mat captureSingleFrame() { Mat frame = new Mat(); if (capture.read(frame) && !frame.empty()) { return frame; } frame.release(); return null; } public Mat captureSingleFrameWithDetection() { Mat frame = captureSingleFrame(); if (frame != null) { FaceDetectionService.DetectionResult result = faceDetector.detectFaces(frame); Mat processed = result.getProcessedImage(); frame.release(); return processed; } return null; } private Image convertToFxImage(BufferedImage image) { java.io.ByteArrayOutputStream out = new java.io.ByteArrayOutputStream(); try { javax.imageio.ImageIO.write(image, "png", out); return new Image(new java.io.ByteArrayInputStream(out.toByteArray())); } catch (Exception e) { throw new RuntimeException("Failed to convert image", e); } } public void setCameraResolution(int width, int height) { capture.set(Videoio.CAP_PROP_FRAME_WIDTH, width); capture.set(Videoio.CAP_PROP_FRAME_HEIGHT, height); } public void setFrameRate(double fps) { capture.set(Videoio.CAP_PROP_FPS, fps); } public void release() { stopCapture(); if (capture != null) { capture.release(); } } public boolean isRunning() { return isRunning.get(); } public static List<Integer> getAvailableCameras() { List<Integer> cameras = new ArrayList<>(); for (int i = 0; i < 10; i++) { VideoCapture testCapture = new VideoCapture(i); if (testCapture.isOpened()) { cameras.add(i); testCapture.release(); } } return cameras; } }

JavaFX Main Application

Step 4: Main Application UI

package com.example.facedetection; import com.example.facedetection.core.FaceDetectionService; import com.example.facedetection.core.WebcamService; import javafx.application.Application; import javafx.application.Platform; import javafx.geometry.Insets; import javafx.geometry.Pos; import javafx.scene.Scene; import javafx.scene.control.*; import javafx.scene.image.Image; import javafx.scene.image.ImageView; import javafx.scene.layout.*; import javafx.stage.FileChooser; import javafx.stage.Stage; import org.opencv.core.Mat; import javax.imageio.ImageIO; import java.awt.image.BufferedImage; import java.io.File; import java.util.List; public class MainApp extends Application { private Stage primaryStage; private BorderPane rootLayout; // Services private FaceDetectionService faceDetector; private WebcamService webcamService; // UI Components private ImageView imageView; private Label statusLabel; private ProgressIndicator progressIndicator; private Button startWebcamButton; private Button stopWebcamButton; private Button loadImageButton; private Button detectFacesButton; private Button saveImageButton; private ComboBox<Integer> cameraComboBox; private CheckBox detectEyesCheckBox; private CheckBox detectSmilesCheckBox; // Current state private boolean webcamActive = false; private Mat currentImage; @Override public void init() throws Exception { super.init(); // Initialize services faceDetector = FaceDetectionService.getInstance(); // Get available cameras List<Integer> availableCameras = WebcamService.getAvailableCameras(); if (!availableCameras.isEmpty()) { webcamService = new WebcamService(availableCameras.get(0)); } } @Override public void start(Stage primaryStage) { this.primaryStage = primaryStage; this.primaryStage.setTitle("Face Detection Application"); initializeRootLayout(); showMainInterface(); primaryStage.setOnCloseRequest(event -> { shutdown(); }); primaryStage.show(); } private void initializeRootLayout() { rootLayout = new BorderPane(); Scene scene = new Scene(rootLayout, 1200, 800); scene.getStylesheets().add(getClass().getResource("/styles/main.css").toExternalForm()); primaryStage.setScene(scene); } private void showMainInterface() { // Create main layout VBox mainContainer = new VBox(20); mainContainer.setPadding(new Insets(20)); mainContainer.setAlignment(Pos.TOP_CENTER); // Create title Label titleLabel = new Label("Face Detection Application"); titleLabel.getStyleClass().add("title-label"); // Create image display area imageView = new ImageView(); imageView.setPreserveRatio(true); imageView.setFitWidth(800); imageView.setFitHeight(600); imageView.setStyle("-fx-border-color: #cccccc; -fx-border-width: 2px; -fx-background-color: #f8f8f8;"); // Create control panel HBox controlPanel = createControlPanel(); // Create status bar HBox statusBar = createStatusBar(); mainContainer.getChildren().addAll( titleLabel, imageView, controlPanel, statusBar ); rootLayout.setCenter(mainContainer); // Set initial status updateStatus("Ready to detect faces"); } private HBox createControlPanel() { HBox controlPanel = new HBox(15); controlPanel.setAlignment(Pos.CENTER); controlPanel.setPadding(new Insets(15)); controlPanel.setStyle("-fx-background-color: #f0f0f0; -fx-border-color: #dddddd; -fx-border-radius: 5px;"); // Webcam controls Label webcamLabel = new Label("Webcam:"); cameraComboBox = new ComboBox<>(); cameraComboBox.setPrefWidth(80); List<Integer> cameras = WebcamService.getAvailableCameras(); cameraComboBox.getItems().addAll(cameras); if (!cameras.isEmpty()) { cameraComboBox.setValue(cameras.get(0)); } startWebcamButton = new Button("Start Webcam"); startWebcamButton.setOnAction(e -> startWebcam()); stopWebcamButton = new Button("Stop Webcam"); stopWebcamButton.setOnAction(e -> stopWebcam()); stopWebcamButton.setDisable(true); // Image controls loadImageButton = new Button("Load Image"); loadImageButton.setOnAction(e -> loadImage()); detectFacesButton = new Button("Detect Faces"); detectFacesButton.setOnAction(e -> detectFacesInImage()); detectFacesButton.setDisable(true); saveImageButton = new Button("Save Result"); saveImageButton.setOnAction(e -> saveImage()); saveImageButton.setDisable(true); // Detection options detectEyesCheckBox = new CheckBox("Detect Eyes"); detectEyesCheckBox.setSelected(true); detectSmilesCheckBox = new CheckBox("Detect Smiles"); detectSmilesCheckBox.setSelected(true); // Layout VBox webcamBox = new VBox(5, webcamLabel, cameraComboBox, startWebcamButton, stopWebcamButton); VBox imageBox = new VBox(5, loadImageButton, detectFacesButton, saveImageButton); VBox optionsBox = new VBox(5, detectEyesCheckBox, detectSmilesCheckBox); controlPanel.getChildren().addAll(webcamBox, new Separator(), imageBox, new Separator(), optionsBox); return controlPanel; } private HBox createStatusBar() { HBox statusBar = new HBox(10); statusBar.setAlignment(Pos.CENTER_LEFT); statusBar.setPadding(new Insets(10)); statusBar.setStyle("-fx-background-color: #e8e8e8; -fx-border-color: #cccccc; -fx-border-width: 1px 0 0 0;"); statusLabel = new Label("Ready"); statusLabel.setStyle("-fx-font-weight: bold;"); progressIndicator = new ProgressIndicator(); progressIndicator.setVisible(false); progressIndicator.setPrefSize(20, 20); statusBar.getChildren().addAll(progressIndicator, statusLabel); HBox.setHgrow(statusLabel, Priority.ALWAYS); return statusBar; } private void startWebcam() { if (webcamService == null) { showError("No webcam available"); return; } try { Integer selectedCamera = cameraComboBox.getValue(); if (selectedCamera != null && selectedCamera != webcamService.getCameraIndex()) { webcamService.release(); webcamService = new WebcamService(selectedCamera); } webcamService.startCapture(imageView, true); webcamActive = true; startWebcamButton.setDisable(true); stopWebcamButton.setDisable(false); loadImageButton.setDisable(true); detectFacesButton.setDisable(true); updateStatus("Webcam active - detecting faces in real-time"); } catch (Exception e) { showError("Failed to start webcam: " + e.getMessage()); } } private void stopWebcam() { if (webcamService != null) { webcamService.stopCapture(); webcamActive = false; startWebcamButton.setDisable(false); stopWebcamButton.setDisable(true); loadImageButton.setDisable(false); // Clear image view imageView.setImage(null); updateStatus("Webcam stopped"); } } private void loadImage() { FileChooser fileChooser = new FileChooser(); fileChooser.setTitle("Open Image File"); fileChooser.getExtensionFilters().addAll( new FileChooser.ExtensionFilter("Image Files", "*.png", "*.jpg", "*.jpeg", "*.bmp", "*.gif"), new FileChooser.ExtensionFilter("All Files", "*.*") ); File selectedFile = fileChooser.showOpenDialog(primaryStage); if (selectedFile != null) { try { showProgress(true); updateStatus("Loading image..."); // Load image in background thread new Thread(() -> { try { BufferedImage bufferedImage = ImageIO.read(selectedFile); Image fxImage = convertToFxImage(bufferedImage); // Convert to OpenCV Mat currentImage = faceDetector.bufferedImageToMat(bufferedImage); Platform.runLater(() -> { imageView.setImage(fxImage); detectFacesButton.setDisable(false); saveImageButton.setDisable(true); updateStatus("Image loaded: " + selectedFile.getName()); showProgress(false); }); } catch (Exception e) { Platform.runLater(() -> { showError("Failed to load image: " + e.getMessage()); showProgress(false); }); } }).start(); } catch (Exception e) { showError("Failed to load image: " + e.getMessage()); showProgress(false); } } } private void detectFacesInImage() { if (currentImage == null) { showError("No image loaded"); return; } showProgress(true); updateStatus("Detecting faces..."); new Thread(() -> { try { boolean detectEyes = detectEyesCheckBox.isSelected(); boolean detectSmiles = detectSmilesCheckBox.isSelected(); FaceDetectionService.DetectionResult result = faceDetector.detectFaces(currentImage, detectEyes, detectSmiles, true); BufferedImage processedImage = faceDetector.matToBufferedImage(result.getProcessedImage()); Image fxImage = convertToFxImage(processedImage); Platform.runLater(() -> { imageView.setImage(fxImage); saveImageButton.setDisable(false); String status = String.format("Detection complete: %d faces, %d eyes, %d smiles found", result.getFaceCount(), result.getEyeCount(), result.getSmileCount()); updateStatus(status); showProgress(false); }); } catch (Exception e) { Platform.runLater(() -> { showError("Face detection failed: " + e.getMessage()); showProgress(false); }); } }).start(); } private void saveImage() { if (imageView.getImage() == null) { showError("No image to save"); return; } FileChooser fileChooser = new FileChooser(); fileChooser.setTitle("Save Processed Image"); fileChooser.getExtensionFilters().addAll( new FileChooser.ExtensionFilter("PNG Image", "*.png"), new FileChooser.ExtensionFilter("JPEG Image", "*.jpg"), new FileChooser.ExtensionFilter("All Files", "*.*") ); File file = fileChooser.showSaveDialog(primaryStage); if (file != null) { try { // Implementation for saving image would go here // This would involve converting the ImageView content back to a file updateStatus("Image saved: " + file.getName()); } catch (Exception e) { showError("Failed to save image: " + e.getMessage()); } } } private Image convertToFxImage(BufferedImage image) { java.io.ByteArrayOutputStream out = new java.io.ByteArrayOutputStream(); try { ImageIO.write(image, "png", out); return new Image(new java.io.ByteArrayInputStream(out.toByteArray())); } catch (Exception e) { throw new RuntimeException("Failed to convert image", e); } } private void updateStatus(String message) { statusLabel.setText(message); } private void showProgress(boolean show) { progressIndicator.setVisible(show); } private void showError(String message) { Alert alert = new Alert(Alert.AlertType.ERROR); alert.setTitle("Error"); alert.setHeaderText("An error occurred"); alert.setContentText(message); alert.showAndWait(); } private void shutdown() { if (webcamService != null) { webcamService.release(); } } public static void main(String[] args) { launch(args); } }

Advanced Features

Step 5: Face Recognition and Analytics

package com.example.facedetection.advanced; import org.opencv.core.*; import org.opencv.face.FaceRecognizer; import org.opencv.face.LBPHFaceRecognizer; import org.opencv.imgproc.Imgproc; import java.io.File; import java.util.*; public class FaceRecognitionService { private FaceRecognizer faceRecognizer; private Map<Integer, String> labelMap; private int nextLabelId; private boolean isTrained; public FaceRecognitionService() { this.faceRecognizer = LBPHFaceRecognizer.create(); this.labelMap = new HashMap<>(); this.nextLabelId = 0; this.isTrained = false; } public void trainFromDirectory(String directoryPath) { List<Mat> images = new ArrayList<>(); List<Integer> labels = new ArrayList<>(); File rootDir = new File(directoryPath); if (!rootDir.exists() || !rootDir.isDirectory()) { throw new IllegalArgumentException("Directory does not exist: " + directoryPath); } // Process each subdirectory (each represents a person) for (File personDir : rootDir.listFiles(File::isDirectory)) { String personName = personDir.getName(); int labelId = getOrCreateLabel(personName); // Process each image in the person's directory for (File imageFile : personDir.listFiles((dir, name) -> name.toLowerCase().endsWith(".jpg") || name.toLowerCase().endsWith(".png") || name.toLowerCase().endsWith(".jpeg"))) { try { Mat image = loadAndPreprocessImage(imageFile.getAbsolutePath()); images.add(image); labels.add(labelId); } catch (Exception e) { System.err.println("Failed to process image: " + imageFile.getName() + " - " + e.getMessage()); } } } if (images.isEmpty()) { throw new IllegalStateException("No training images found"); } // Train the recognizer MatOfInt labelsMat = new MatOfInt(); labelsMat.fromList(labels); faceRecognizer.train(images, labelsMat); isTrained = true; // Clean up images.forEach(Mat::release); labelsMat.release(); System.out.println("Training completed. " + labelMap.size() + " persons, " + images.size() + " images"); } public RecognitionResult recognizeFace(Mat faceImage) { if (!isTrained) { throw new IllegalStateException("Recognizer is not trained"); } Mat processedFace = preprocessFace(faceImage); int[] label = new int[1]; double[] confidence = new double[1]; faceRecognizer.predict(processedFace, label, confidence); String personName = labelMap.getOrDefault(label[0], "Unknown"); processedFace.release(); return new RecognitionResult(personName, confidence[0], label[0]); } private Mat loadAndPreprocessImage(String imagePath) { Mat image = Imgcodecs.imread(imagePath, Imgcodecs.IMREAD_GRAYSCALE); if (image.empty()) { throw new RuntimeException("Failed to load image: " + imagePath); } return preprocessFace(image); } private Mat preprocessFace(Mat faceImage) { Mat processed = new Mat(); // Resize to standard size Imgproc.resize(faceImage, processed, new Size(100, 100)); // Equalize histogram Imgproc.equalizeHist(processed, processed); return processed; } private int getOrCreateLabel(String personName) { for (Map.Entry<Integer, String> entry : labelMap.entrySet()) { if (entry.getValue().equals(personName)) { return entry.getKey(); } } int newLabel = nextLabelId++; labelMap.put(newLabel, personName); return newLabel; } public void saveModel(String modelPath) { if (!isTrained) { throw new IllegalStateException("No model to save - recognizer is not trained"); } faceRecognizer.save(modelPath); // Save label mapping try (java.io.ObjectOutputStream out = new java.io.ObjectOutputStream( new java.io.FileOutputStream(modelPath + ".labels"))) { out.writeObject(labelMap); } catch (Exception e) { throw new RuntimeException("Failed to save label mapping", e); } } @SuppressWarnings("unchecked") public void loadModel(String modelPath) { faceRecognizer.read(modelPath); // Load label mapping try (java.io.ObjectInputStream in = new java.io.ObjectInputStream( new java.io.FileInputStream(modelPath + ".labels"))) { labelMap = (Map<Integer, String>) in.readObject(); nextLabelId = labelMap.keySet().stream().max(Integer::compareTo).orElse(0) + 1; isTrained = true; } catch (Exception e) { throw new RuntimeException("Failed to load label mapping", e); } } public boolean isTrained() { return isTrained; } public Map<Integer, String> getLabelMap() { return Collections.unmodifiableMap(labelMap); } public static class RecognitionResult { private final String personName; private final double confidence; private final int label; public RecognitionResult(String personName, double confidence, int label) { this.personName = personName; this.confidence = confidence; this.label = label; } // Getters public String getPersonName() { return personName; } public double getConfidence() { return confidence; } public int getLabel() { return label; } public boolean isConfident(double threshold) { return confidence < threshold; } @Override public String toString() { return String.format("%s (%.2f confidence)", personName, confidence); } } }

CSS Styling

Step 6: Application Styling

```css
/* resources/styles/main.css */

.root {
-fx-font-family: "Segoe UI", Arial, sans-serif;
-fx-font-size: 14