#include "AlgorithmFluorescence.h"
#include "ImageProcess.h"

#include <QVariant>
#include <QImage>
#include <QDebug>
#include <QPixmap>
#include "CVUtils.h"
#include "qtcvutils.h"

#include "Result2Ui.h"
#include "ICompareModel.h"
#include "IWheelModel.h"

#pragma execution_character_set("utf-8")

#define MAX_CIRCLE_RADII 110
#define MIN_INSIDE_RATIO 0.038
#define MAX_INSIDE_RATIO 0.072
#define INSIDE_NUM_DIS_THRE 1.5

using namespace cv;
using namespace lp;

class CLocalWheel{
public:
	CLocalWheel() {
		useHeight = true;
		useDiameter = true;
	}
	cv::Mat img;
	int height;
	int diameter;
	bool useHeight;
	bool useDiameter;
	QStringList defectList;
	double dRatioVal{0};
	int ratioType{ 0 };
};

CAlgorithmFluorescence::CAlgorithmFluorescence(void)
{

}

CAlgorithmFluorescence::~CAlgorithmFluorescence(void)
{

}

//检测算法入口函数 由corctl框架回调
int CAlgorithmFluorescence::IImageAnalysis(class IImageObject* pImgObj, TP_ALGORITHM_OPTION* pOpt, class IDetectorEngine* pDE)
{
	try {
		qDebug() << "start alg";
		QMutexLocker locker(&mutex);
		CircleParam cParam;
		double dStart = cv::getTickCount();
		Mat matSrc = getImage(pImgObj).clone();//获取相机原始图像
		QVariantMap vMap = pImgObj->IVarFromUI().toMap();//获取由UI传递过来的算法参数
	
		//解析出模板库指针 这里获取的是整个模块库
		long long modelMapPtr = vMap.value("modelMap").toLongLong();
		QMap<QString, IWheelModel*> *ptr = (QMap<QString, IWheelModel*>*)modelMapPtr;

		//获取需要检测的列表 型号名
		long long defectListPtr = vMap.value("defectList").toLongLong();
		QStringList* strModelListptr = (QStringList*)defectListPtr;
		QStringList strModelList;
		if(strModelListptr)
			strModelList = *(strModelListptr);
		int IsCutedImg = vMap.value("IsCutImg", 0).toInt();//裁剪后的轮毂图 检测模式 小图

		int th = vMap.value("thickness", -1).toInt();//轮毂厚度 轮毂高度数据
		bool useThickness = vMap.value("useThickness", 0).toBool();//是否使用厚度检测判断  匹配时过滤不符合范围的模板
		bool useDiameter = vMap.value("useDiameter", 0).toBool();//是否使用直径参数检测判断
		double dD2H = vMap.value("d2h", -1).toDouble();

		int nthreshold = vMap.value("Threshold", 15).toInt();//图像阈值参数 使用背景图抠图算法时使用
		bool bUseBackground = vMap.value("useBackground",false).toBool();//true 使用背景图抠图 false 不使用背景
	
		int ratioType = vMap.value("RatioType").toInt();//偏距检测模式 启用方式
		double ratioVal = vMap.value("Ratio").toDouble();//偏距系数
		bool bEqual = vMap.value("bEqual").toBool();//使用使用图像增强
		int filterSize = vMap.value("filterSize").toInt();//过滤圆大小
		cParam.CirclePolarity = vMap.value("Circle_Polarity",0).toInt();
		cParam.CircleACThres = vMap.value("Circle_ACThres",3).toInt();
		cParam.CircleEdgeWidth = vMap.value("Circle_EdgeWidth",3).toInt();
		cParam.filterSize = filterSize;

		if (nthreshold <= 0)
			nthreshold = 15; 

		QVariantMap rltMap;//算法检测结果值 输出到UI用
		rltMap.insert("ratioVal", ratioVal);
		luffy_base::luffyCircle lCircle;
		static bool bReload = false;//背景图加载判断
		Mat matBack = getBackGroundImage(pImgObj, bReload);//获取背景图
	
		Mat matMatch;//抠图后的图像 目标图像
		if (IsCutedImg == 0) //使用的是原始图像 需要执行圆查找算法找出 轮毂
		{
			//原始图像的size和背景图size不匹配， 直接返回错误提示
			if (bUseBackground == true && (matSrc.size().height != matBack.size().height || matSrc.size().width != matBack.size().width))
			{
				rltMap.insert("error", 0);
				pImgObj->IVariantMapToUI(rltMap);
				bReload = true;
				return 0;
			}
			else{
				bReload = false;
			}

			if (bUseBackground == true)//使用背景图 做减法找圆
			{
				Point2f centerPoint;
				double radius = 0;
				matMatch = ImageProcess::findCircleByBackground(matSrc, matBack, centerPoint, radius, bEqual, filterSize, cParam);
				lCircle.ptCenter = centerPoint;
				lCircle.fRadius = radius;
			}
			else {
				//不需要 背景图找圆算法 
				Point2f centerPoint;
				double radius = 0;
				matMatch = ImageProcess::findCircle(matSrc, centerPoint, radius, bEqual,filterSize,cParam);
				lCircle.ptCenter = centerPoint;
				lCircle.fRadius = radius;
			}
			if (matMatch.cols >= 900 || matMatch.rows >= 900)//控制检测图像大小不能超过这个范围
			{
				cv::resize(matMatch, matMatch, cv::Size(matMatch.cols / 2, matMatch.rows / 2));
				lCircle.fRadius = lCircle.fRadius / 2;
			}
		}
		else{
			matMatch = matSrc;
		}

		Result2Ui *pResult = new Result2Ui;
		pResult->m_pixSrc = QtCVUtils::cvMatToQPixmap(matSrc);//!>原图像发送值UI 用于保存备份和调试
		if (matMatch.empty())//抠图为空，表示抠图失败，直接返回错误
		{
			rltMap.insert("noCircle", 0);
			long long varRlt = (long long)pResult;
			rltMap.insert("result", varRlt);
			pImgObj->IVariantMapToUI(rltMap);
			return 0;
		}

		double dDiameter = dD2H * lCircle.fRadius * 2;//计算轮毂直径
		//打包相关数据
		CLocalWheel wheelLocal;
		wheelLocal.defectList = strModelList;
		wheelLocal.img = matMatch.clone();
		wheelLocal.height = th;
		wheelLocal.diameter = dDiameter;
		wheelLocal.useHeight = useThickness;
		wheelLocal.useDiameter = useDiameter;
		wheelLocal.ratioType = ratioType;
		wheelLocal.dRatioVal = ratioVal;
		//开始匹配
		if (!matMatch.empty() && ptr && ptr->size() > 0) {
			vector<double> minDisVec(ptr->size());//初始化模板匹配分数值
			QString str = bestMatch(ptr, &wheelLocal, &(minDisVec[0]), minDisVec.size());
			pResult->m_strModel = str;
			pResult->m_dMinDis = minDisVec[0];
			if (ptr->contains(str) && ptr->value(str)->getImageComModel()) {
				ICompareModel *pModel = ptr->value(str)->getImageComModel();
				double d = pModel->getDisThre();
				double dValue = (d - minDisVec[0]) / d * 0.4 + 0.6;
				pResult->m_dScore = dValue;
			}
		}

		qDebug() << "pull result";
		QImage img = QtCVUtils::cvMatToQImage(matMatch);
		pResult->m_pixResult = QtCVUtils::cvMatToQPixmap(matMatch);// .scaled(125, 125);
		pResult->m_dDiameter = dDiameter;
		pResult->m_dThickness = th;

		//!>传递检测结果到UI	
		//pImgObj->IDrawImage(img.scaled(300, 300));//!>显示结果图片到UI的第二个窗口上
		double dTime = (cv::getTickCount() - dStart) / cv::getTickFrequency();
		pResult->m_dRunTime = dTime;
		long long varRlt = (long long)pResult;
		rltMap.insert("result", varRlt);
		pImgObj->IVariantMapToUI(rltMap);
		qDebug() << "finish alg";
		return 1;
	}
	catch (...) {
		qDebug() << "algo run Error " << __FUNCTION__;
		return 1;
	}
}

//模板匹配流程
QString CAlgorithmFluorescence::bestMatch(const QMap<QString, IWheelModel*>* modelMap, CLocalWheel* pLocal, double* pMinDis /*= NULL*/, int minDisNum /*= -1*/) const
{
	double minDis = DBL_MAX;
	QString bestName;
	vector<double> disVec(modelMap->size());
	int nIndex = 0;
	if (!modelMap)
		return bestName;
	QStringList strDetectModels = pLocal->defectList;

	int similarNum = 0;
	const QString hubName1("DH151079");
	const QString hubName2("DK151050");
	QMap<QString, double> simularModelMap;
	while (strDetectModels.size())
	{
		QString strModelName = strDetectModels.takeFirst();
		if (!modelMap->contains(strModelName))
			continue;

		QMap<QString, IWheelModel*>::const_iterator itsModel = modelMap->find(strModelName);
		disVec[nIndex] = DBL_MAX;
		IWheelModel *pWheel = itsModel.value();
		if (!pWheel)
			break;
		if (pLocal->useDiameter) {
			if (abs(pLocal->diameter - pWheel->getDiameter()) >= 15) {
				nIndex++;
				continue;
			}
		}
		if (pLocal->useHeight) {
			if (abs(pLocal->height - pWheel->getThickness()) >= 15) {
				nIndex++;
				continue;
			}
		}
		if (pLocal->ratioType == 1) {//开启使用偏距过滤检测模板的功能
			//必须三个数值不为0才进行 否则可能导致不明问题
			double curRatioVal = pLocal->dRatioVal;
			double minRatio = pWheel->getMinRotia();
			double maxRatio = pWheel->getMaxRotia();

			if (curRatioVal > 0 && minRatio > 0 && maxRatio > 0)
			{
				if (curRatioVal < minRatio || curRatioVal > maxRatio)
				{
					nIndex++;
					continue;
				}
			}
		}

		QString name = strModelName;

		ICompareModel* pModel = pWheel->getImageComModel();
		if (pModel->getBaseImg().data == NULL)
		{
			nIndex++;
			continue;
		}

		pModel->setIsEnableCache(false);

		double dis = pModel->compare(pLocal->img, NULL, true, 1);
		double disThre = pModel->getDisThre();
		double innerCircleNum = pModel->getInnerCircleNum();
		if (dis < disThre)
		{
			similarNum++;
			simularModelMap[name] = innerCircleNum;
		}
		disVec[nIndex] = dis;

		if (dis < minDis && dis != -1)
		{
			minDis = dis;
			bestName = name;
		}
		nIndex++;
	}

	if (pMinDis)
	{
		*pMinDis = minDis;
	}
	if (minDisNum > 1)
	{
		sort(disVec.begin(), disVec.end());
		std::copy_n(disVec.begin(), minDisNum, pMinDis);
	}
	if (similarNum < 1)
	{
		return bestName;
	}
	const cv::Mat originalMat = pLocal->img;
	float startX = originalMat.cols / 2.0 - MAX_CIRCLE_RADII;//找最大圆外径，固定直径
	float startY = originalMat.rows / 2.0 - MAX_CIRCLE_RADII;
	Rect rect(startX, startY, MAX_CIRCLE_RADII * 2, MAX_CIRCLE_RADII * 2);
	cv::Mat centerMat = originalMat(rect).clone();
	EDCircles edCircles(centerMat);
	std::vector<mCircle> circles = edCircles.getCircles();
	const int nSize = circles.size();
	float rMax = 0;

	for (int i = 0; i < nSize; ++i)
	{
		float radius = circles[i].r;
		if (radius > rMax)
		{
			rMax = radius;
		}
	}
	double innerCircleNumSum = 0;
	double rMaxUp = rMax * MAX_INSIDE_RATIO;
	double rMaxLow = rMax * MIN_INSIDE_RATIO;
	for (int i = 0; i < nSize; ++i)
	{
		double radius = circles[i].r;
		if (radius < rMaxUp && radius > rMaxLow * MIN_INSIDE_RATIO)
		{
			innerCircleNumSum++;
		}
	}
	if (bestName.toUpper() == hubName1)
	{
		if (innerCircleNumSum > 1)
		{
			QStringList modelList = pLocal->defectList;
			bool bFind = false;
			while (modelList.size())
			{
				QString modelName = modelList.takeFirst();
				if (modelName == hubName2)
				{
					bestName = hubName2;
					bFind = true;
					break;
				}
			}
			if (!bFind)
			{
				// bestName = QString();
			}
		}
	}
	else if (bestName.toUpper() == hubName2)
	{
		if (innerCircleNumSum < 2)
		{
			QStringList modelList = pLocal->defectList;
			bool bFind = false;
			while (modelList.size())
			{
				QString modelName = modelList.takeFirst();
				if (modelName == hubName1)
				{
					bestName = hubName1;
					bFind = true;
					break;
				}
			}
			if (!bFind)
			{
				// bestName = QString();
			}
		}
	}

	return bestName;
}


cv::Mat CAlgorithmFluorescence::getImage(class IImageObject *pImgObj)
{
	emTpColorFormat colorFormat = pImgObj->IColorFormat();
	int nImageW;
	int nImageH;
	int nBitsPerPixel;
	int nBytesPerLine;
	BYTE* pImageData = pImgObj->IImageData(nImageW, nImageH, nBitsPerPixel, nBytesPerLine);
	Mat matSrc;

	if (TP_COLOR_Y800 != colorFormat)
	{
		Mat colorMat = Mat(nImageH, nImageW, CV_8UC4, pImageData, nBytesPerLine);
		matSrc = getFirstChannel(colorMat);
	}
	else
	{
		matSrc = Mat(nImageH, nImageW, CV_8UC1, pImageData, nBytesPerLine);
	}
	return matSrc;
}

cv::Mat CAlgorithmFluorescence::getBackGroundImage(class IImageObject *pObj, bool bReLoad)
{
	static Mat matback;
	if (matback.empty()) {
		QString filepath =  ".\\user\\background.png";
		matback = cv::imread(string((const char *)filepath.toLocal8Bit()), 0);
		if (matback.empty()) {
			QString filepath = getPath(pObj) + "\\user\\background_r.png";
			matback = cv::imread(string((const char *)filepath.toLocal8Bit()), 0);
			cv::flip(matback, matback, 1);
		}
	}
	else {
		if (bReLoad) {
			QString filepath = getPath(pObj) + "\\user\\background.png";
			matback = cv::imread(string((const char *)filepath.toLocal8Bit()), 0);
			if (matback.empty()) {
				QString filepath = getPath(pObj) + "\\user\\background_r.png";
				matback = cv::imread(string((const char *)filepath.toLocal8Bit()), 0);
				cv::flip(matback, matback, 1);
			}
		}
	}
	return matback;
}

QString CAlgorithmFluorescence::getPath(class IImageObject *pObj)
{
	IAlgorithmShared* pShare = pObj->IGetShared();
	if (!pShare)
		return QString();
	QStringList mlist = pObj->IGetShared()->IGetStringList("filepath");
	if (mlist.empty()) {
		return QString();
	}
	return mlist.first();
}