public KMeansClusterFactory(ClusterDataSourceSettings settings, IClusterMergeStrategy mergeStrategy, IntSize size)
{
this.settings = settings;
this.mergeStrategy = mergeStrategy;
this.algorithm = new KMeans(this.settings.ClusterCount, settings.DepthRange, size);
this.value = new ClusterCollection();
}
public IClusterDataSource CreateClusterDataSource(ClusterDataSourceSettings clusterDataSourceSettings)
{
var size = new IntSize(this.Adapter.DepthStreamWidth, this.Adapter.DepthStreamHeight);
var clusterFactory = new KMeansClusterFactory(clusterDataSourceSettings, size);
var filter = new ImageFrameDepthPointFilter(this.Adapter, size, clusterDataSourceSettings.MinimumDepthThreshold, clusterDataSourceSettings.MaximumDepthThreshold, clusterDataSourceSettings.LowerBorder);
return new SDKClusterDataSource(this.Adapter, clusterFactory, filter);
}
public IList<ClusterPrototype> CreateClusters(int numberOfClusters, IntSize areaSize)
{
Contract.Requires(numberOfClusters >= 0);
Contract.Requires(areaSize.Width > 0 && areaSize.Height > 0);
var result = new List<ClusterPrototype>();
float sliceWidth = areaSize.Width / numberOfClusters;
float sliceHeight = areaSize.Height / numberOfClusters;
for (int index = 0; index < numberOfClusters; index++) {
int minX = (int)((index) * sliceWidth);
int maxX = (int)((index + 1) * sliceWidth);
int minY = (int)((index) * sliceHeight);
int maxY = (int)((index + 1) * sliceHeight);
result.Add(this.CreateClusterWithin(minX, maxX, minY, maxY));
}
return result;
}
public KMeansClusterFactory(ClusterDataSourceSettings settings, IntSize size)
: this(settings, new DefaultMergeStrategy(settings), size)
{
}
public KMeans(int numberOfClusters, Range zRange, IntSize size)
{
this.size = size;
this.zRange = zRange;
this.clusters = clusterFactory.CreateClusters(numberOfClusters, size);
}
