#pragma once
#include "raw_image_class.h"
//#include <mymist_ver2.h>
//#include <myOpenCV.h>
#include "myOpenCV3.h"
#include "mymist.h"

//出血検出に関する関数をまとめたクラス
//主に骨抽出手法と出血候補領域抽出手法
static class Extravasation_detect
{
public:
	//座標
	struct LabelData {
		int x = 0;
		int y = 0;
		int z = 0;
		int minz = 0;
		int maxz = 0;
		int minx = 0;
		int maxx = 0;
		int miny = 0;
		int maxy = 0;
		int xCount = 0;
		int yCount = 0;
		int zCount = 0;
		int Area = 0;
		int CTValue = 0;
		bool Delete = true;
		bool Detectcheck = true;
	};
	//どの位置を示しているかを表す列挙型
	enum BODYTYPE{HEAD,UPPER,LOWER};
	//骨抽出関連
	//人工物除去
	static array3<uchar> Artificial_Segmentation(Raw_image<short>& ct);
	//適応的閾値決定
	static int Adaptive_Threshold(Raw_image<short>& ct);
	//watershed
	static array3<uchar> Watershed(short* ct, array3<uchar> prebone, int thre);

	//従来の骨抽出手法
	static array3<uchar> Old_BoneExtractMethod(Raw_image<short>& ct, BODYTYPE type);
	//thresholdを変えることで適応的閾値処理になる
	static array3<uchar> Bone_Extract(Raw_image<short>& ct, BODYTYPE type,int threshold = 350);

	//出血候補領域抽出手法
	/*候補領域抽出パラメータ*/
	struct Parameter {

		//骨抽出
		int HighCut;

		//平均CT値
		int MaxCTValue;
		int MinCTValue;

		//候補領域抽出
		int MINV;
		int CutVeno;
		int ExtractKarnel;
		float sigma;
		int MaxVolume;
	};
	//二段階閾値処理
	static array3<uchar> double_thresholding(Raw_image<short>& ct, array3<uchar>& bone, BODYTYPE type);

	//ピーク点ベース(dencity_vertexをやる前に骨領域除去が必要)
	template <typename Type>
	static array3<float> unshape(array3<Type>& input);
	static std::vector<mist::vector3<int>> reduction_point(array3<short> ct, std::vector<mist::vector3<int>>& point, float rate);
	static array3<uchar> dencity_vertex(Raw_image<short>& ct,array3<uchar>& bon);

	//評価
	//結果の構造体
	struct Result {
		array3<uchar> Evalu_Array;
		int region = 0;
		int TP = 0;
		int FP = 0;
		int MissCount = 0;
		int OriginalP = 0;
		int HEADP = 0;
		int LOWERP = 0;
		int UPPERP = 0;
		int MissH = 0;
		int MissL = 0;
		int MissU = 0;
		int HFP = 0;
		int UFP = 0;
		int LFP = 0;

	public:
		void ToString(int casenum = 0);
	};
	static Result Evaluation(array3<unsigned int>& InputLabel, size_t& VenoCount, 
		array3<uchar>& Mask, int SIZE1, int SIZE2);

	//その他
	static array3<uchar> ArrayLink(array3<uchar>& FirstArray, array3<uchar>& SecondArray);
};