smart-bow-infrared/Assets/InfraredProject/WebCamera/Script/ZIM/InfraredLocate/LineIdentify/LineGuess.cs

using o0.Geometry2D.Float;
using o0.Num;
using System;
using System.Collections.Generic;
using System.Linq;
using UnityEngine;

namespace o0.Project
{
    // 大于阈值则猜测是Line，但是这个类不考虑梯度，外部仍需结合梯度评估
    public class LineGuess
    {
        public static float isLineThreshold = 1.0f;
        // 记录分段的线段数据
        class SubLineData
        {
            public List<float> DataList;    
            public List<float> DiffList;    // 数据与平均值的差

            // 幅度
            float diffExtent = -1;
            float dataExtent = -1;

            public SubLineData(float data, float diff)
            {
                DataList = new List<float> { data };
                DiffList = new List<float> { diff };
            }

            public void Add(float data, float diff)
            {
                DataList.Add(data);
                DiffList.Add(diff);
            }

            // 得到差异的幅度
            //public float GetDiffExtent()
            //{
            //    if (diffExtent == -1)
            //    {
            //        var sum = 0.0f;
            //        foreach (var i in DiffList)
            //            sum += i * i;
            //        return diffExtent = sum / DiffList.Count;
            //    }
            //    else
            //        return diffExtent;
            //}

            // 得到数据的幅度（和0比）
            public float GetDataExtent()
            {
                if (dataExtent == -1)
                {
                    var sum = 0.0f;
                    foreach (var i in DataList)
                        sum += i * i;
                    return dataExtent = sum / DataList.Count;
                }
                else
                    return dataExtent;
            }
        }

        public List<Matrix> ScreenLocateMatList;
        public float GradientLength;
        public float MinLineLength;

        public LineGuess(List<Matrix> screenLocateMatList, float gradientLength, float minLineLength)
        {
            ScreenLocateMatList = screenLocateMatList;
            GradientLength = gradientLength;
            MinLineLength = minLineLength;
        }

        // 猜测是直线返回true
        public bool GuessIsLine(LineIdentified line) => Guess(line) > isLineThreshold;

        // 越大越可能是直线
        public float Guess(LineIdentified line)
        {
            var dir = (line.Line.B - line.Line.A).Normalized;
            var vertical = new Vector(-dir.y, dir.x) * (GradientLength / 2);
            var verticalNormal = vertical.Normalized;
            float lineABStep = MinLineLength / 15;

            float lineGuessStart;
            float lineGuessEnd;
            if (line.Line.Length > 2 * MinLineLength)
            {
                lineGuessStart = 7.5f * lineABStep;
                lineGuessEnd = line.Line.Length - 7.5f * lineABStep;        // 线的两端不计算
            }
            else
            {
                lineGuessStart = lineABStep;
                lineGuessEnd = line.Line.Length - lineABStep;
            }

            var gradData = new List<float>();      // 直线两侧梯度的平均值，垂直于直线变化

            var a0 = line.Line.A - vertical;
            var gradStep = 1.5f;
            for (float n = 0; n < GradientLength; n += gradStep)
            {
                var aN = a0 + verticalNormal * n;
                var gradThisLine = new List<float>();
                for (float i = lineGuessStart; i <= lineGuessEnd; i += lineABStep)
                {
                    var point = aN + dir * i;
                    gradThisLine.Add(ScreenLocateMatList[line.Batch][(int)point.x, (int)point.y]);
                }
                gradData.Add(gradThisLine.Mean());
            }
            //Debug.Log(line.Gradient + ", " + line.GradientDegree + ", " + gradData.ToJson());
            if (gradData.Count <= 3)
                return 400;

            var gradChangeData = new List<float>();
            for (int j = 1; j < gradData.Count; j++)
                gradChangeData.Add(Math.Abs(gradData[j] - gradData[j - 1]));
            var meanChange = gradChangeData.Mean();
            var diff = gradChangeData[0] - meanChange;

            var subList = new List<SubLineData>() { new SubLineData(gradChangeData[0], diff) };

            for (int i = 1; i < gradChangeData.Count; i++)
            {
                var newDiff = gradChangeData[i] - meanChange;
                if ((newDiff <= 0 && diff <= 0) || (newDiff > 0 && diff > 0))   // 同号，是一个分段
                    subList.Last().Add(gradChangeData[i], newDiff);
                else
                    subList.Add(new SubLineData(gradChangeData[i], newDiff));
                diff = newDiff;
            }
            int maxSubDataIndex = subList.MaxIndex((a, b) => a.GetDataExtent().CompareTo(b.GetDataExtent()));  // 找到分段里和平均数差异最大的分段

            //TODO 这里要不要考虑加个阈值，过滤掉梯度太小的线条？ -----------------------------------

            if (subList.Count < 3)
                maxSubDataIndex = -1;  // ≥3的时候把SubDataExtent最高的这段剔除掉再计算

            var lineGuessExtent = 0.0f;
            for (int i = 0; i < subList.Count; i++)
            {
                if (i != maxSubDataIndex)
                    lineGuessExtent += subList[i].GetDataExtent();
            }
            if (maxSubDataIndex == -1)
                lineGuessExtent /= subList.Count;
            else
                lineGuessExtent /= subList.Count - 1;

            lineGuessExtent = (float)Math.Sqrt(lineGuessExtent);
            var countFactor = -0.002f * Math.Abs(subList.Count - 3) + 0.015f;  // 3时最大
            if (ScreenLocate.Main.DebugOnZIMDemo)
                Debug.Log("line.Index" + line.ScreenLineIndex + ", maxDiffIndex: " + maxSubDataIndex + ", sub count: " + subList.Count + ", lineGuess: " + (1 - lineGuessExtent + countFactor));
            return 1 - lineGuessExtent + countFactor;
        }
    }


}