#pragma once
#include <opencv2/opencv.hpp>
#include <opencv2/xfeatures2d.hpp>
#include "identify_struct.h"
#include "schema_struct.h"
#include <vector>
#include <boost/smart_ptr.hpp>
using namespace std;
using namespace cv;
using namespace cv::ml;
using namespace cv::xfeatures2d;
using namespace identify::schema;
using namespace identify::result;
using namespace identify::analysis;
namespace identify{
	class CResultReader
	{
	public:
		CResultReader(void);
		~CResultReader(void);
		bool m_nBxuanxiang;
	public:
		int ReadResult(const IplImage* img, int schemaIndex, cv::Mat transform, double scale, int dir, OMR_RESULT* out_result);
		int ReadResult(int shemaIndex);
		void SetSchemaPages(boost::shared_ptr<const ISCH_Schema>schema);
	private:
		//模板
		boost::shared_ptr<const ISCH_Schema>schemaPages;
		//源图像
		const IplImage *src;
		int m_pageDirection;
		double m_Scaler0;
		Mat m_AffineTransform;//防射变换(由模板变换到图像)
		AnalyseResult anlyseResult;
		int dianshu_meihaomi;
		OMR_RESULT* omr_result;

		std::vector<cv::Point2f> point_muban;
		std::vector<cv::Point2f> point_shijuan;
		cv::Ptr<cv::ml::KNearest> knn;
	private:


		template<typename T1, typename T2 >
		double GetDistance(T1 point1, T2 point2)
		{
			double dx = point1.x - point2.x;
			double dy = point1.y - point2.y;
			return sqrt(dx*dx + dy*dy);
		}
		//截取图像
		int ClipImg(const ISCH_SCHEMA_PAGE& schemaPage);
		/************************************************************************/
		/* 设置识别结果默认值                                                   */
		/************************************************************************/
		void SetDefaultOMR_Result(OMR_RESULT& omr_result);

		template<typename T1, typename T2> T2 warpAffinePoint(T1& src, Mat * map_matrix);
		template<typename T1> CvRect GetResultRect(T1& item);
		template<typename T1> CvRect GetJiaoZhengResultRect(T1& item);
		template<typename T1, typename T2> T2 GetJiaoZhengResultPoint(T1& point);

		template<class T> void SaveRect(CvRect& rect, T& result);


		//读取二维码
		int ReadBarCode(const ISCH_SCHEMA_PAGE& schemaPage);

		unsigned char(*_GetGray)(const IplImage * dst, int x, int y);
		unsigned char GetGray(const IplImage * dst, int x, int y);

		//获取全局背景灰度，通过统计所有涂点周围像素(灰度不小于160)的灰度平均值获得
		int caculate_global_background(const ISCH_SCHEMA_PAGE& schemaPage);


		//计算涂点属性
		int caculate_cell_property(ISCH_SCHEMA_PAGE& schemaPage, ISCH_SCHEMA_ITEM &item, const IplImage * dst, int &cellSize, double &refArea, double &avg_gray, int &grayNum, double &mo_hu_du, double &gao_heidu, int &char_area_size, int& char_area_black_count, double& char_area_avg_gray, int & diheidushu);
		int caculate_item_property(const ISCH_SCHEMA_PAGE& schemaPage, const ISCH_SCHEMA_ITEM &item, const IplImage * dst, AnalyseResult::itemResult& item_result);

		void GetCorrectedRect(CvRect &rr, const IplImage * src, int tembackcolor);

		//分析全局属性
		int analyseOmrPanoramic(ISCH_SCHEMA_PAGE& schemaPage);
		/************************************************************************/
		/* 生成OMR涂点字符串（客观题填涂判断）     2014年11月28日10:54:19                                                                 */
		/************************************************************************/
		int GenerateOmrStr(const ISCH_SCHEMA_PAGE& schemaPage);

		//读取客观题分数
		int ReadKeGuanTi(const ISCH_SCHEMA_PAGE &schemaPage);
		int ReadDingWeiDian(const ISCH_SCHEMA_PAGE& schemaPage);
		void caculate_item_global_property(const ISCH_SCHEMA_PAGE & schemaPage);
		int findAssitLocate(const ISCH_SCHEMA_PAGE& schemaPage);
		//读取填空题，和主观题分数
		int ReadQuestionScore(const ISCH_SCHEMA_PAGE &schemaPage);


		//获取图像指定区域红色点数(主观题)  去除长直线和周边像素 减少直线边缘偏色影响
		int GetZhuGuanTiRedCount(IplImage * dst, const CvRect& rect, const CvRect& normal_rect, int * red_counts, int * red_in_counts, int count);
		//获取图像指定区域红色点数(填空题)
		int GetTianKongTiRedCount(IplImage * dst, const CvRect& rect_normal, const CvRect& rect_detect);


		BOOL GetRedBinary(IplImage * dst, const CvRect& rect_detect, IplImage ** red_binary);

	};
}