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geekprogramming/Predict

Last active June 2, 2016 06:46
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  1. geekprogramming revised this gist Jun 2, 2016. 1 changed file with 11 additions and 0 deletions.
    11 changes: 11 additions & 0 deletions Predict
    View file
    Original file line number Diff line number Diff line change
    @@ -23,6 +23,17 @@ public static int[][] toIntArrayArray(BufferedImage image) {
    return ret;
    }


    //Steps which appy data before train and then apply for predict
    public static BufferedImage preprocess(BufferedImage img) {
    opencv_core.Mat original = ImageOpenCvUtils.toMat(img);
    opencv_core.Mat grayScale = ImageOpenCvUtils.toGray(original);
    opencv_core.Mat maximizeContrast = ImageOpenCvUtils.maximizeContrastMat(grayScale, 1);
    opencv_core.Mat output = new opencv_core.Mat(maximizeContrast.size(),maximizeContrast.type());
    opencv_imgproc.resize(maximizeContrast,output,new opencv_core.Size(23,43));
    return ImageOpenCvUtils.toBufferedImage(output);
    }

    public static double predict(BufferedImage img,MultiLayerNetwork model) {
    img = preprocess(img);
    int[][] ret = toIntArrayArray(img);
  2. geekprogramming created this gist Jun 2, 2016.
    35 changes: 35 additions & 0 deletions Predict
    View file
    Original file line number Diff line number Diff line change
    @@ -0,0 +1,35 @@
    // Predict function
    public static int[][] toIntArrayArray(BufferedImage image) {
    int w = image.getWidth();
    int h = image.getHeight();
    int[][] ret = new int[h][w];
    int j;
    if(image.getRaster().getNumDataElements() == 1) {
    WritableRaster i = image.getRaster();

    for(j = 0; j < h; ++j) {
    for(int j1 = 0; j1 < w; ++j1) {
    ret[j][j1] = i.getSample(j1, j, 0);
    }
    }
    } else {
    for(int var8 = 0; var8 < h; ++var8) {
    for(j = 0; j < w; ++j) {
    ret[var8][j] = image.getRGB(j, var8);
    }
    }
    }

    return ret;
    }

    public static double predict(BufferedImage img,MultiLayerNetwork model) {
    img = preprocess(img);
    int[][] ret = toIntArrayArray(img);
    ImageLoader loader = new ImageLoader();

    INDArray input = ArrayUtil.toNDArray(ArrayUtil.flatten(ret));
    INDArray output = model.output(input);
    output = Nd4j.argMax(output, 1);
    return output.getDouble(0);
    }