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 *
 * Since product implements StAX API, it has dependencies to StAX API
 * classes.
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 * For additional credits (generally to people who reported problems)
 * see CREDITS file.
 */
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package com.aparapi.examples.convolution;

import java.io.File;

import com.aparapi.Kernel;

public class PureJava{

   final static class ImageConvolution extends Kernel{
      private float convMatrix3x3[];

      private int width, height;

      private byte imageIn[], imageOut[];

      public void processPixel(int x, int y, int w, int h) {
         float accum = 0f;
         int count = 0;
         for (int dx = -3; dx < 6; dx += 3) {
            for (int dy = -1; dy < 2; dy += 1) {
               int rgb = 0xff & imageIn[((y + dy) * w) + (x + dx)];

               accum += rgb * convMatrix3x3[count++];
            }
         }
         byte value = (byte) (max(0, min((int) accum, 255)));
         imageOut[y * w + x] = value;

      }

      @Override public void run() {
         int x = getGlobalId(0) % (width * 3);
         int y = getGlobalId(0) / (width * 3);

         if (x > 3 && x < (width * 3 - 3) && y > 1 && y < (height - 1)) {
            processPixel(x, y, width * 3, height);
         }

      }

      public void applyConvolution(float[] _convMatrix3x3, byte[] _imageIn, byte[] _imageOut, int _width, int _height) {
         imageIn = _imageIn;
         imageOut = _imageOut;
         width = _width;
         height = _height;
         convMatrix3x3 = _convMatrix3x3;

         execute(3 * width * height);
      }

   }

   public static void main(final String[] _args) {
      File file = new File(_args.length == 1 ? _args[0] : "./src/main/resources/testcard.jpg");

      final ImageConvolution convolution = new ImageConvolution();

      float convMatrix3x3[] = new float[] {
            0f,
            -10f,
            0f,
            -10f,
            40f,
            -10f,
            0f,
            -10f,
            0f,
      };

      new ConvolutionViewer(file, convMatrix3x3){
         @Override protected void applyConvolution(float[] _convMatrix3x3, byte[] _inBytes, byte[] _outBytes, int _width,
               int _height) {
            convolution.applyConvolution(_convMatrix3x3, _inBytes, _outBytes, _width, _height);
         }
      };

   }

}