Beispiel #1
0
  private double match_eye(Rect area, Mat mTemplate, int type) {
    Point matchLoc;
    Mat mROI = mGray.submat(area);
    int result_cols = mGray.cols() - mTemplate.cols() + 1;
    int result_rows = mGray.rows() - mTemplate.rows() + 1;
    if (mTemplate.cols() == 0 || mTemplate.rows() == 0) {
      return 0.0;
    }
    mResult = new Mat(result_cols, result_rows, CvType.CV_32FC1);

    switch (type) {
      case TM_SQDIFF:
        Imgproc.matchTemplate(mROI, mTemplate, mResult, Imgproc.TM_SQDIFF);
        break;
      case TM_SQDIFF_NORMED:
        Imgproc.matchTemplate(mROI, mTemplate, mResult, Imgproc.TM_SQDIFF_NORMED);
        break;
      case TM_CCOEFF:
        Imgproc.matchTemplate(mROI, mTemplate, mResult, Imgproc.TM_CCOEFF);
        break;
      case TM_CCOEFF_NORMED:
        Imgproc.matchTemplate(mROI, mTemplate, mResult, Imgproc.TM_CCOEFF_NORMED);
        break;
      case TM_CCORR:
        Imgproc.matchTemplate(mROI, mTemplate, mResult, Imgproc.TM_CCORR);
        break;
      case TM_CCORR_NORMED:
        Imgproc.matchTemplate(mROI, mTemplate, mResult, Imgproc.TM_CCORR_NORMED);
        break;
    }

    Core.MinMaxLocResult mmres = Core.minMaxLoc(mResult);

    if (type == TM_SQDIFF || type == TM_SQDIFF_NORMED) {
      matchLoc = mmres.minLoc;
    } else {
      matchLoc = mmres.maxLoc;
    }

    Point matchLoc_tx = new Point(matchLoc.x + area.x, matchLoc.y + area.y);
    Point matchLoc_ty =
        new Point(matchLoc.x + mTemplate.cols() + area.x, matchLoc.y + mTemplate.rows() + area.y);

    Core.rectangle(mRgba, matchLoc_tx, matchLoc_ty, new Scalar(255, 255, 0, 255));

    if (type == TM_SQDIFF || type == TM_SQDIFF_NORMED) {
      return mmres.maxVal;
    } else {
      return mmres.minVal;
    }
  }
  public void templateMatching() {
    System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
    int match_method = 5;
    int max_Trackbar = 5;
    Mat data = Highgui.imread("images/training_data/1" + "/data (" + 1 + ").jpg");
    Mat temp = Highgui.imread("images/template.jpg");
    Mat img = data.clone();

    int result_cols = img.cols() - temp.cols() + 1;
    int result_rows = img.rows() - temp.rows() + 1;
    Mat result = new Mat(result_rows, result_cols, CvType.CV_32FC1);

    Imgproc.matchTemplate(img, temp, result, match_method);
    Core.normalize(result, result, 0, 1, Core.NORM_MINMAX, -1, new Mat());

    double minVal;
    double maxVal;
    Point minLoc;
    Point maxLoc;
    Point matchLoc;
    // minMaxLoc( result, &minVal, &maxVal, &minLoc, &maxLoc, Mat() );
    Core.MinMaxLocResult res = Core.minMaxLoc(result);

    if (match_method == Imgproc.TM_SQDIFF || match_method == Imgproc.TM_SQDIFF_NORMED) {
      matchLoc = res.minLoc;
    } else {
      matchLoc = res.maxLoc;
    }

    // / Show me what you got
    Core.rectangle(
        img,
        matchLoc,
        new Point(matchLoc.x + temp.cols(), matchLoc.y + temp.rows()),
        new Scalar(0, 255, 0));

    // Save the visualized detection.
    Highgui.imwrite("images/samp.jpg", img);
  }
Beispiel #3
0
  private void match_eye(Rect area, Mat mTemplate, int type) {
    Point matchLoc;
    Mat mROI = mGray.submat(area);
    int result_cols = mROI.cols() - mTemplate.cols() + 1;
    int result_rows = mROI.rows() - mTemplate.rows() + 1;
    // Check for bad template size
    if (mTemplate.cols() == 0 || mTemplate.rows() == 0) {
      return;
    }
    Mat mResult = new Mat(result_cols, result_rows, CvType.CV_8U);
    long nbPixels = (mResult.rows() * mResult.cols()) - getBlackPixels(mResult);
    if (Math.abs(nbPixels) < 2000) {
      final MediaPlayer mp = new MediaPlayer();
      try {
        mp.reset();
        AssetFileDescriptor afd;
        afd = getAssets().openFd("wakeUp.mp3");
        mp.setDataSource(afd.getFileDescriptor(), afd.getStartOffset(), afd.getLength());
        mp.prepare();
        mp.start();
        Thread.sleep(60000);
      } catch (IllegalStateException e) {
        e.printStackTrace();
      } catch (IOException e) {
        e.printStackTrace();
      } catch (InterruptedException e) {
        e.printStackTrace();
      }

      Log.i("You are sleeping", "YOU SLEPT");
    } else Log.i("M_match_eye: else ", "nbPixels = " + nbPixels);

    switch (type) {
      case TM_SQDIFF:
        Imgproc.matchTemplate(mROI, mTemplate, mResult, Imgproc.TM_SQDIFF);
        break;
      case TM_SQDIFF_NORMED:
        Imgproc.matchTemplate(mROI, mTemplate, mResult, Imgproc.TM_SQDIFF_NORMED);
        break;
      case TM_CCOEFF:
        Imgproc.matchTemplate(mROI, mTemplate, mResult, Imgproc.TM_CCOEFF);
        break;
      case TM_CCOEFF_NORMED:
        Imgproc.matchTemplate(mROI, mTemplate, mResult, Imgproc.TM_CCOEFF_NORMED);
        break;
      case TM_CCORR:
        Imgproc.matchTemplate(mROI, mTemplate, mResult, Imgproc.TM_CCORR);
        break;
      case TM_CCORR_NORMED:
        Imgproc.matchTemplate(mROI, mTemplate, mResult, Imgproc.TM_CCORR_NORMED);
        break;
    }

    Core.MinMaxLocResult mmres = Core.minMaxLoc(mResult);
    // there is difference in matching methods - best match is max/min value
    if (type == TM_SQDIFF || type == TM_SQDIFF_NORMED) {
      matchLoc = mmres.minLoc;
    } else {
      matchLoc = mmres.maxLoc;
    }

    Point matchLoc_tx = new Point(matchLoc.x + area.x, matchLoc.y + area.y);
    Point matchLoc_ty =
        new Point(matchLoc.x + mTemplate.cols() + area.x, matchLoc.y + mTemplate.rows() + area.y);

    Imgproc.rectangle(mRgba, matchLoc_tx, matchLoc_ty, new Scalar(255, 255, 0, 255));
    Rect rec = new Rect(matchLoc_tx, matchLoc_ty);
  }