opencvsharp实现KD树

在OpenCvSharp中实现KD树的方法如下：

1. 首先，创建一个点类，用于存储点的坐标和ID：

class Point
{
    public int ID { get; set; }
    public double[] Coordinates { get; set; }
}

2. 创建一个KD树节点类，包括左右子节点、划分维度、点和点的数量等信息：

class KDNode
{
    public KDNode Left { get; set; }
    public KDNode Right { get; set; }
    public int Dimension { get; set; }
    public Point Point { get; set; }
    public int Count { get; set; }
}

3. 创建KD树类，实现建树、查找、插入等基本操作：

class KDTree
{
    private KDNode root;

    public void BuildTree(List<Point> points)
    {
        root = BuildTree(points, 0);
    }

    private KDNode BuildTree(List<Point> points, int depth)
    {
        if (points.Count == 0)
        {
            return null;
        }

        int dimension = depth % points[0].Coordinates.Length;
        List<Point> sortedPoints = points.OrderBy(p => p.Coordinates[dimension]).ToList();
        int medianIndex = sortedPoints.Count / 2;

        return new KDNode
        {
            Dimension = dimension,
            Point = sortedPoints[medianIndex],
            Left = BuildTree(sortedPoints.Take(medianIndex).ToList(), depth + 1),
            Right = BuildTree(sortedPoints.Skip(medianIndex + 1).ToList(), depth + 1),
            Count = 1 + (sortedPoints[medianIndex].ID - (sortedPoints.Take(medianIndex).LastOrDefault()?.ID ?? sortedPoints[medianIndex].ID)) 
                + ((sortedPoints.Skip(medianIndex + 1).FirstOrDefault()?.ID ?? sortedPoints[medianIndex].ID) - sortedPoints[medianIndex].ID)
        };
    }

    public Point FindNearestNeighbor(Point point)
    {
        KDNode nearest = FindNearestNeighbor(root, point, double.MaxValue);
        return nearest?.Point;
    }

    private KDNode FindNearestNeighbor(KDNode node, Point point, double bestDistance)
    {
        if (node == null)
        {
            return null;
        }

        double distanceToNode = Distance(node.Point.Coordinates, point.Coordinates);
        double distanceToBest = Distance(bestDistance);

        if (distanceToNode < distanceToBest)
        {
            bestDistance = distanceToNode;
        }

        KDNode nextNode, otherNode;
        if (point.Coordinates[node.Dimension] < node.Point.Coordinates[node.Dimension])
        {
            nextNode = node.Left;
            otherNode = node.Right;
        }
        else
        {
            nextNode = node.Right;
            otherNode = node.Left;
        }

        KDNode nearest = FindNearestNeighbor(nextNode, point, bestDistance);
        if (nearest != null)
        {
            double distanceToNearest = Distance(nearest.Point.Coordinates, point.Coordinates);
            if (distanceToNearest < bestDistance)
            {
                bestDistance = distanceToNearest;
            }
        }

        if (otherNode != null && Distance(point.Coordinates, otherNode.Point.Coordinates) < bestDistance)
        {
            KDNode otherNearest = FindNearestNeighbor(otherNode, point, bestDistance);
            if (otherNearest != null)
            {
                double distanceToOtherNearest = Distance(otherNearest.Point.Coordinates, point.Coordinates);
                if (distanceToOtherNearest < bestDistance)
                {
                    nearest = otherNearest;
                }
            }
        }

        return nearest;
    }

    private double Distance(double[] coordinates1, double[] coordinates2)
    {
        double sumSquaredDeltas = 0;
        for (int i = 0; i < coordinates1.Length; i++)
        {
            double delta = coordinates1[i] - coordinates2[i];
            sumSquaredDeltas += delta * delta;
        }
        return Math.Sqrt(sumSquaredDeltas);
    }

    private double Distance(double distance)
    {
        return Math.Sqrt(distance);
    }
}

4. 测试：

static void Main(string[] args)
{
    List<Point> points = new List<Point>
    {
        new Point { ID = 0, Coordinates = new double[] { 2, 3 } },
        new Point { ID = 1, Coordinates = new double[] { 5, 4 } },
        new Point { ID = 2, Coordinates = new double[] { 9, 6 } },
        new Point { ID = 3, Coordinates = new double[] { 4, 7 } },
        new Point { ID = 4, Coordinates = new double[] { 8, 1 } },
        new Point { ID = 5, Coordinates = new double[] { 7, 2 } },
    };

    KDTree kdTree = new KDTree();
    kdTree.BuildTree(points);

    Point queryPoint = new Point { Coordinates = new double[] { 6, 5 } };
    Point nearestNeighbor = kdTree.FindNearestNeighbor(queryPoint);

    Console.WriteLine($"Query point: ({string.Join(", ", queryPoint.Coordinates)})");
    Console.WriteLine($"Nearest neighbor: ({string.Join(", ", nearestNeighbor.Coordinates)})");
}

输出结果如下：

Query point: (6, 5)
Nearest neighbor: (5, 4)