/// <summary>
/// Classifies points from <paramref name="labeledImage"/> (using the mask if present) and adds the distributions at each pixel to <paramref name="dist"/>.
/// </summary>
/// <param name="tree">The tree used for the computation</param>
/// <param name="labeledImage">The image to classify</param>
/// <param name="dist">Image which is used to store the distributions</param>
public static void ClassifySoft <T>(this DecisionTree <ImageDataPoint <T>, T[]> tree, LabeledImage <T> labeledImage, DistributionImage dist)
{
List <ImageDataPoint <T> > points = labeledImage.CreateAllDataPoints(BackgroundSampleMode.Full);
List <int> indices = new List <int>();
for (int i = 0; i < points.Count; i++)
{
indices.Add(i);
}
INodeInfo <ImageDataPoint <T>, T[]>[] info = new INodeInfo <ImageDataPoint <T>, T[]> [points.Count];
DecisionTree <ImageDataPoint <T>, T[]> .assignLabels(tree._root, points, info, indices);
for (int i = 0; i < info.Length; i++)
{
dist.Add(points[i].Row, points[i].Column, info[i].Distribution);
}
}
/// <summary>
/// Classifies each point from <paramref name="image"/> and trackes which nodes it visits.
/// </summary>
/// <param name="tree">The tree used for the computation</param>
/// <param name="image">Image to add to the tree</param>
/// <param name="mode">Mode to use when sampling the image</param>
public static void Fill <T>(this DecisionTree <ImageDataPoint <T>, T[]> tree, LabeledImage <T> image, BackgroundSampleMode mode)
{
List <ImageDataPoint <T> > points = image.CreateAllDataPoints(mode);
tree.Fill(points);
}
/// <summary>
/// Computes a histogram for all trees from the provided image.
/// </summary>
/// <param name="forest">The forest used for the computation</param>
/// <param name="image">Image to classify</param>
/// <returns>The histogram</returns>
public static TreeHistogram ComputeHistogram <T>(this DecisionForest <ImageDataPoint <T>, T[]> forest, LabeledImage <T> image)
{
return(forest.ComputeHistogram(image.CreateAllDataPoints(BackgroundSampleMode.Full)));
}
