Esempio n. 1
0
  @Override
  protected void onDraw(Canvas canvas) {
    Paint paint = new Paint();
    paint.setColor(Color.RED);
    paint.setTextSize(20);

    String s = "FacePreview - This side up.";
    float textWidth = paint.measureText(s);
    canvas.drawText(s, (getWidth() - textWidth) / 2, 20, paint);

    if (faces != null) {
      paint.setStrokeWidth(2);
      paint.setStyle(Paint.Style.STROKE);
      float scaleX = (float) getWidth() / grayImage.width();
      float scaleY = (float) getHeight() / grayImage.height();
      int total = faces.total();
      for (int i = 0; i < total; i++) {
        CvRect r = new CvRect(cvGetSeqElem(faces, i));
        int x = r.x(), y = r.y(), w = r.width(), h = r.height();
        canvas.drawRect(x * scaleX, y * scaleY, (x + w) * scaleX, (y + h) * scaleY, paint);
      }
    }
  }
Esempio n. 2
0
 public static List<Result> findMatchesByGrayscaleAtOriginalResolution(
     BufferedImage input, BufferedImage target, int limit, double minScore) {
   IplImage input1 = ImagePreprocessor.createGrayscale(input);
   IplImage target1 = ImagePreprocessor.createGrayscale(target);
   IplImage resultMatrix =
       TemplateMatchingUtilities.computeTemplateMatchResultMatrix(input1, target1);
   List<Result> result = fetchMatches(resultMatrix, target1, limit, minScore);
   input1.release();
   target1.release();
   resultMatrix.release();
   return result;
 }
Esempio n. 3
0
  protected void processImage(byte[] data, int width, int height) {
    // First, downsample our image and convert it into a grayscale IplImage
    int f = SUBSAMPLING_FACTOR;
    if (grayImage == null || grayImage.width() != width / f || grayImage.height() != height / f) {
      grayImage = IplImage.create(width / f, height / f, IPL_DEPTH_8U, 1);
    }
    int imageWidth = grayImage.width();
    int imageHeight = grayImage.height();
    int dataStride = f * width;
    int imageStride = grayImage.widthStep();
    ByteBuffer imageBuffer = grayImage.getByteBuffer();
    for (int y = 0; y < imageHeight; y++) {
      int dataLine = y * dataStride;
      int imageLine = y * imageStride;
      for (int x = 0; x < imageWidth; x++) {
        imageBuffer.put(imageLine + x, data[dataLine + f * x]);
      }
    }

    cvClearMemStorage(storage);
    faces = cvHaarDetectObjects(grayImage, classifier, storage, 1.1, 3, CV_HAAR_DO_CANNY_PRUNING);
    postInvalidate();
  }