/** * Default constructor * * @param capture * @param width * @param height */ public ShapeRenderingTutorial(Video<MBFImage> capture, int width, int height) { super("Drawing", capture, width, height); this.detector = new HaarCascadeDetector(20); }
/** * Used to detect faces when there is no current state. * * @return The list of detected faces */ private List<DetectedFace> detectFaces(final FImage img) { return this.faceDetector.detectFaces(img); }
/** * Default constructor that takes the minimum size (in pixels) of detections * that should be considered faces. * * @param minSize * The minimum size of face boxes */ public KLTHaarFaceTracker(final int minSize) { this.faceDetector.setMinSize(minSize); }
HaarCascadeDetector det1 = new HaarCascadeDetector(); DetectedFace face1 = det1.detectFaces(img).get(0);
HaarCascadeDetector hcd = new HaarCascadeDetector("haarcascade_frontalface_alt.xml"); hcd.setMinSize( minSize ); List<DetectedFace> faces = hcd.detectFaces( img ); if( displayResults )
fd.setMinSize( this.options.faceSize ); faces = fd.detectFaces( faceFrame.flatten() );
public static void main(String[] args) throws IOException, InterruptedException { final File fddbGroundTruth = new File("/Users/jsh2/Downloads/FDDB-folds/FDDB-fold-01-ellipseList.txt"); final File imageBase = new File("/Users/jsh2/Downloads/originalPics/"); final FDDBDataset dataset = new FDDBDataset(fddbGroundTruth, imageBase, true); final HaarCascadeDetector det = HaarCascadeDetector.BuiltInCascade.frontalface_alt2.load(); det.setGroupingFilter(new OpenCVGrouping(0)); det.setMinSize(80); final EvaluationDetector evDet = new EvaluationDetector() { @Override public synchronized List<? extends DetectedFace> getDetections(FDDBRecord record) { final List<DetectedFace> faces = det.detectFaces(record.getFImage()); // for (final DetectedFace f : faces) // f.setConfidence(1); return faces; } }; final FDDBEvaluation eval = new FDDBEvaluation(); final List<Results> result = eval.performEvaluation(dataset, evDet); System.out.println(Results.getROCData(result)); } }
/** * Construct with the given cascade resource. See * {@link #setCascade(String)} to understand how the cascade is loaded. * * @param cas * The cascade resource. * @see #setCascade(String) */ public HaarCascadeDetector(String cas) { try { setCascade(cas); } catch (final Exception e) { throw new RuntimeException(e); } groupingFilter = new OpenCVGrouping(); }
HaarCascadeDetector det1 = new HaarCascadeDetector(); DetectedFace face1 = det1.detectFaces(img).get(0);
HaarCascadeDetector hcd = new HaarCascadeDetector("haarcascade_frontalface_alt.xml"); hcd.setMinSize( minSize ); List<DetectedFace> faces = hcd.detectFaces( img ); if( displayResults )
fd.setMinSize( this.options.faceSize ); faces = fd.detectFaces( faceFrame.flatten() );
/** * Default constructor. Uses the standard {@link HaarCascadeDetector} with a * minimum search size of 80 pixels. */ public FKEFaceDetector() { this(new HaarCascadeDetector(80)); }
HaarCascadeDetector faceDetector = new HaarCascadeDetector( 40 ); List<DetectedFace> faces = faceDetector.detectFaces( image.flatten() );
@Override public synchronized List<? extends DetectedFace> getDetections(FDDBRecord record) { final List<DetectedFace> faces = det.detectFaces(record.getFImage()); // for (final DetectedFace f : faces) // f.setConfidence(1); return faces; } };
@Override public FaceDetector<DetectedFace, FImage> getDetector() { final HaarCascadeDetector fd = cascade.load(); fd.setMinSize(minSize); return fd; } }
/** * Default constructor. Uses the standard {@link HaarCascadeDetector} with a * minimum search size of 80 pixels, and the given scale-factor for * extracting the face patch. * * @param patchScale * the scale of the patch compared to the patch extracted by the * internal detector. */ public FKEFaceDetector(float patchScale) { this(new HaarCascadeDetector(80), patchScale); }
HaarCascadeDetector faceDetector = new HaarCascadeDetector( 40 ); List<DetectedFace> faces = faceDetector.detectFaces( image.flatten() );
@Override public FeatureVector extract(MBFImage image, FImage mask) { if (mask != null) System.err.println("Warning: HAAR_FACES doesn't support masking"); HaarCascadeDetector fd = cascade.load(); return mode.getFeatureVector(fd.detectFaces(Transforms.calculateIntensityNTSC(image)), image); } }
@Override public FaceDetector<DetectedFace, FImage> getDetector() { final HaarCascadeDetector fd = cascade.load(); fd.setMinSize(minSize); return fd; } }
/** * */ public OpenIMAJ() { faceDetector = new HaarCascadeDetector(80); }