private float d(Image i1, Image i2) {
double d = 0;
for (int i = 0; i < i1.getDataShort().length; i++) {
d +=
(i1.getDataShort()[i] - i2.getDataShort()[i])
* (i1.getDataShort()[i] - i2.getDataShort()[i]);
}
return (float) Math.sqrt(d);
}
public void constructNormalizedImageClusters() {
clusterImages.clear();
for (int i = 0; i < noClusters; i++) {
Image image = new ImageFloat(dimFilterX, dimFilterY);
System.arraycopy(
memClusters.getSrc(),
i * dimFilterX * dimFilterY,
image.getDataFloat(),
0,
dimFilterX * dimFilterY);
clusterImages.add(image);
}
}
private void constructImageClusters() {
for (int i = 0; i < noClusters; i++) {
Image image = new ImageFloat(dimFilterX, dimFilterY);
double max = -1 * Double.MAX_VALUE;
double min = Double.MAX_VALUE;
int clusterOffset = dimFilterX * dimFilterY * i;
for (int j = 0; j < dimFilterX * dimFilterY; j++) {
if (clustersCenters[clusterOffset + j] > max) max = clustersCenters[clusterOffset + j];
if (clustersCenters[clusterOffset + j] < min) min = clustersCenters[clusterOffset + j];
}
max = 255 / (max - min);
for (int j = 0; j < dimFilterX * dimFilterY; j++) {
image.getDataFloat()[j] = (float) ((clustersCenters[clusterOffset + j] - min) * max);
}
clusterImages.add(image);
}
}
private void randomizeClustersFromData() {
List<Image> filters = new ArrayList<>();
int dimImage = (int) Math.sqrt(imageSize);
while (filters.size() < noClusters) {
Image initCluster = images.get((int) (Math.random() * images.size()));
int x = strideX * ((int) (getInitOffset() * ((dimImage - dimFilterX) / strideX)));
int y = strideY * ((int) (getInitOffset() * ((dimImage - dimFilterY) / strideY)));
Image filter = initCluster.extractImage(x, y, dimFilterX, dimFilterY);
if (okToAdd(filters, filter)) {
// System.out.println(filters.size());
filters.add(filter);
}
}
for (int i = 0; i < noClusters; i++) {
for (int j = 0; j < dimFilterX * dimFilterY; j++) {
clustersCenters[i * dimFilterX * dimFilterY + j] = filters.get(i).getDataShort()[j];
}
}
}