BOE_FOG_DETECT/AlgorithmModule/src/ImgCheckAnalysisy.cpp

#include "ImgCheckAnalysisy.hpp"
#include "CheckUtil.hpp"
#include "Define.h"
#include <omp.h>
#include "AICommonDefine.h"
// 用于排序轮廓的比较函数
static bool compareContourAreas(const vector<Point> &contour1, const vector<Point> &contour2)
{
	double i = contourArea(contour1);
	double j = contourArea(contour2);
	return (i > j);
}
ImgCheckAnalysisy::ImgCheckAnalysisy()
{

	m_nErrorCode = CHECK_OK;
	m_nThreadIdx = -1;
	m_bInitSucc = false;
	m_bExit = false;
	m_nRun_Status = CHECK_THREAD_STATUS_IDLE;

	m_fImgage_Scale_X = 0.03f;
	m_fImgage_Scale_Y = 0.03f;
	m_pBasicConfig = NULL;

	m_strCurDetCamChannel = "";
	m_strCurDetChannel = "";

	m_pbaseCheckFunction = &m_AnalysisyConfig.baseFunction;

	m_strLastDate = "";
	m_strRootPath_TA_cls = "/home/aidlux/BOE/FOG/Cls/TA/";
	m_strRootPath_CA_cls = "/home/aidlux/BOE/FOG/Cls/CA/";
	creatsavedir();
	m_pImageStorage = ImageStorage::getInstance();
	m_nConfigIdx = -1;

	det_SmallImgNum = 0;
}

ImgCheckAnalysisy::~ImgCheckAnalysisy()
{
	ExitSystem();
}
int ImgCheckAnalysisy::UpdateConfig(void *pconfig, int nConfigType)
{
	int re = 0;
	switch (nConfigType)
	{
	case CHECK_CONFIG_Run:
		re = LoadRunConfig(pconfig);
		if (re == 0)
		{
			// printf("---> LoadRunConfig  Succ\n");
		}
		else
		{
			// printf("---> LoadRunConfig  Fail\n");
		}
		break;
	case CHECK_CONFIG_Module:
		re = LoadCheckConfig(pconfig);
		if (re == 0)
		{
			// printf("---> LoadAnalysisConfig  Succ\n");
		}
		else
		{
			// printf("---> LoadAnalysisConfig  Fail\n");
		}
		break;
	default:
		break;
	}
	return re;
}
int ImgCheckAnalysisy::RunStart(void *pconfig1)
{

	// 1 、更新参数 并判断参数是否合法
	int re = CHECK_OK;
	re = SetNewConfig();
	if (CHECK_OK != re)
	{
		m_nErrorCode = re;
		return m_nErrorCode;
	}
	printf("---> RunStart  Start m_RunConfig.nThreadIdx %d  \n", m_RunConfig.nThreadIdx);

	m_nThreadIdx = m_RunConfig.nThreadIdx;

	re = InitRun(m_RunConfig.nCpu_start_Idx);
	if (CHECK_OK != re)
	{
		m_nErrorCode = re;
		return m_nErrorCode;
	}
	runner = std::make_shared<AIMulThreadRunBase>();
	runner->Start();

	m_nErrorCode = CHECK_OK;
	// printf("ImgCheckAnalysisy >>>> ImgCheckThread %d Start Succ \n", m_nThreadIdx);
	return m_nErrorCode;
}

int ImgCheckAnalysisy::SetDataRun_SharePtr(std::shared_ptr<ImageAllResult> p)
{
	// 设置正在检测

	m_pImageAllResult = p;
	DetImgInfo_shareP = p->result->in_shareImage;
	m_CheckResult_shareP = p->result;
	m_pImageAllResult->setStep(ImageAllResult::DetStep_Deting);
	m_pdetlog = p->detlog;
	m_pDetResult = p->pDetResult;
	StartCheck();
	m_nErrorCode = CHECK_OK;
	return m_nErrorCode;
}

int ImgCheckAnalysisy::GetCheckReuslt(std::shared_ptr<ImageDetResult> &pResult)
{

	m_CheckResult_shareP.reset();
	DetImgInfo_shareP.reset();
	SetIDLE();
	// m_nErrorCode = CHECK_OK;
	// printf("4 DetImgInfo_shareP count %ld   m_nCheckResultErrorCode %d \n", DetImgInfo_shareP.use_count(), m_nCheckResultErrorCode);
	return m_nCheckResultErrorCode;
}

int ImgCheckAnalysisy::CheckImg(std::shared_ptr<ImageDetconfig> p, std::shared_ptr<ImageDetResult> &pResult)
{

	return 0;
}

int ImgCheckAnalysisy::ReJsonResul(std::shared_ptr<ImageDetconfig> p, std::shared_ptr<ImageDetResult> &pResult)
{

	return 0;
}

int ImgCheckAnalysisy::InitRun(int nId)
{

	int re = CHECK_OK;
	if (m_bInitSucc)
	{
		return CHECK_OK;
	}
	InitModel();
	AI_Factory = AIFactory::GetInstance();

	m_nRun_Status = CHECK_THREAD_STATUS_IDLE;
	re = StartThread(nId);
	if (CHECK_OK != re)
	{
		return re;
	}
	m_bInitSucc = true;
	return re;
}

int ImgCheckAnalysisy::GetStatus()
{
	return m_nRun_Status;
}

std::string ImgCheckAnalysisy::GetVersion()
{
	return std::string("BOE_1.2.4_" + std::string(__DATE__) + "_" + std::string(__TIME__));
}

std::string ImgCheckAnalysisy::GetErrorInfo()
{
	std::string str = GetErrorCodeInfo(m_nErrorCode);
	printf("%s\n", str.c_str());
	return str;
}

int ImgCheckAnalysisy::creatsavedir()
{
	std::string curDate = CheckUtil::getCurrentDate();
	if (curDate == m_strLastDate)
	{
		return 0;
	}
	m_strLastDate = curDate;
	m_strRootPath_TA_cls += m_strLastDate + "/";
	m_strRootPath_CA_cls += m_strLastDate + "/";
	for (int i = 0; i < AI_CLass_QX_NAME_count; i++)
	{
		CheckUtil::CreateDir(m_strRootPath_TA_cls + std::to_string(i) + "/");
		CheckUtil::CreateDir(m_strRootPath_CA_cls + std::to_string(i) + "/");
	}
	return 0;
}

int ImgCheckAnalysisy::LoadRunConfig(void *p)
{
	if (p == NULL)
	{
		m_nErrorCode = CHECK_ERROR_Config_Null;
		return m_nErrorCode;
	}
	RunInfoST *pconfig = (RunInfoST *)p;
	m_RunConfig.copy(*pconfig);

	return CHECK_OK;
}

int ImgCheckAnalysisy::LoadCheckConfig(void *p)
{
	if (p == NULL)
	{
		m_nErrorCode = CHECK_ERROR_Config_Null;
		return m_nErrorCode;
	}
	m_pConfig = (ConfigBase *)p;
	m_nConfigIdx = m_pConfig->GetConfigIdx();
	m_nErrorCode = CHECK_OK;
	return m_nErrorCode;
}

// 开启检测
int ImgCheckAnalysisy::StartCheck()
{
	m_nRun_Status = CHECK_THREAD_STATUS_READY;
	return 0;
}

int ImgCheckAnalysisy::SetIDLE()
{
	// 更新参数
	SetNewConfig();
	m_nRun_Status = CHECK_THREAD_STATUS_IDLE;
	return 0;
}

int ImgCheckAnalysisy::StartThread(int nId)
{
	// 开启检测线程
	ptr_thread_Run = std::make_shared<std::thread>(std::bind(&ImgCheckAnalysisy::Run, this, nId));
	if (!m_RunConfig.bRetest)
	{
		ptr_thread_AI = std::make_shared<std::thread>(std::bind(&ImgCheckAnalysisy::ThreadTask, this, nId + 1));
	}

	return 0;
}

int ImgCheckAnalysisy::StopThread()
{
	m_bExit = true;
	if (ptr_thread_Run != nullptr)
	{
		if (ptr_thread_Run->joinable())
		{
			ptr_thread_Run->join();
		}
	}
	if (ptr_thread_AI != nullptr)
	{
		if (ptr_thread_AI->joinable())
		{
			ptr_thread_AI->join();
		}
	}
	return 0;
}

int ImgCheckAnalysisy::ExitSystem()
{
	StopThread();
	return 0;
}

int ImgCheckAnalysisy::InitModel()
{

	// 获取当前gpu号确定的 AI处理线程

	m_OtherDet_Config.nDeviceId = m_RunConfig.nDeviceId;

	return 0;
}

cv::Scalar ImgCheckAnalysisy::calc_blob_info_withstats(cv::Mat &img, const cv::Mat &mask, cv::Rect &stats, cv::Size k_size, int expand, double threshold)
{

	// 解包 stats（x, y, w, h, area）
	int x = stats.x, y = stats.y, w = stats.width, h = stats.height;

	// 将图像转换为灰度图像

	// 计算感兴趣区域 (ROI)
	cv::Rect roi(x - expand, y - expand, w + 2 * expand, h + 2 * expand);
	roi &= cv::Rect(0, 0, img.cols, img.rows); // 确保ROI在图像内

	cv::Mat cimg = img(roi);

	// cv::cvtColor(cimg, cimg, cv::COLOR_BGR2GRAY);
	// return cv::Scalar(0, 0, 0);
	//	CheckUtil::printROI(roi, "roi-----------");
	// printf("img --%d  %d \n", img.cols, img.rows);
	// printf("mask --%d  %d \n", mask.cols, mask.rows);
	cv::Mat cmask = mask(roi);
	// getchar();
	// 扩张掩膜

	cv::Scalar mean_bk = cv::mean(cimg, ~cmask);
	double fbk = mean_bk[0];

	cv::Scalar mean_det = cv::mean(cimg, cmask);
	double fdet = mean_det[0];

	// 计算差异图像
	cv::Mat diff = cv::abs(cimg - fbk);

	// cv::imwrite("cimg.png",cimg);
	// cv::imwrite("cmask.png",cmask);
	// printf("%f  %f  - %f \n",fbk,fdet,fbk-fdet);
	// getchar();

	// diff = diff.mul(cmask > 0);
	cv::Mat masked_image;
	diff.copyTo(masked_image, cmask);
	// 计算能量
	double energy = cv::sum(masked_image)[0];

	// 计算 hj（差异图像大于0的像素均值）
	// double hj = std::abs(fbk - fdet);
	double hj = CheckUtil::CalHjWeighted(cimg, cmask, fbk, 2.0f);

	int worb = 0;
	if (fdet >= fbk)
	{
		worb = 1;
	}
	// cv::imwrite("cimg.png", cimg);
	// cv::imwrite("cmask.png", cmask);
	// cv::imwrite("diff.png", diff);
	// cv::imwrite("masked_image.png", masked_image);
	// printf("fbk %f fdet %f  energy  %f\n", fbk, fdet, energy);
	// getchar();

	return cv::Scalar(worb, energy, hj);
}

double ImgCheckAnalysisy::CalBlobHJ(cv::Mat &img, const cv::Mat &mask, cv::Rect &det_roi, cv::Rect &qx_roi, int expand)
{

	int x = qx_roi.x, y = qx_roi.y, w = qx_roi.width, h = qx_roi.height;

	// 将图像转换为灰度图像

	// 计算感兴趣区域 (ROI)
	cv::Rect roi(x - expand, y - expand, w + 2 * expand, h + 2 * expand);
	roi &= cv::Rect(det_roi.x, det_roi.y, det_roi.width, det_roi.height); // 确保ROI在图像内

	cv::Mat cimg = img(roi).clone();

	// cv::cvtColor(cimg, cimg, cv::COLOR_BGR2GRAY);
	// return cv::Scalar(0, 0, 0);
	// CheckUtil::printROI(roi, "roi-----------");
	// CheckUtil::printROI(det_roi, "det_roi-----------");
	// printf("%s img --%d  %d \n", m_pImageAllResult->strChannel.c_str(), img.cols, img.rows);
	// printf("%s mask --%d  %d \n", m_pImageAllResult->strChannel.c_str(), mask.cols, mask.rows);
	cv::Mat cmask = mask(roi).clone();
	;
	// getchar();
	// 扩张掩膜

	cv::Scalar mean_bk = cv::mean(cimg, ~cmask);
	double fbk = mean_bk[0];

	cv::Scalar mean_det = cv::mean(cimg, cmask);
	double fdet = mean_det[0];

	// 计算 hj（差异图像大于0的像素均值）
	// double hj = std::abs(fbk - fdet);
	double hj = CheckUtil::CalHjWeighted(cimg, cmask, fbk, 2.0f);
	static int kkk = 0;

	unsigned char *pErrordata = (unsigned char *)cimg.data;
	unsigned char *pMaskdata = (unsigned char *)cmask.data;
	int width = cimg.cols;
	int height = cimg.rows;

	long t21 = CheckUtil::getcurTime();

	int de = CalHJ_Pixel(pErrordata, pMaskdata, width, height, fbk, 0.3);
	long t22 = CheckUtil::getcurTime();
	// printf("de=======  %d usetime  %ld \n", de, t22 - t21);
	std::string strn = m_pImageAllResult->strChannel + "_" + std::to_string(kkk++) + "_" + std::to_string(fbk) + "_" + std::to_string(hj) + "_" + std::to_string(de);

	// cv::imwrite(strn + "cimg.png", cimg);
	// cv::imwrite(strn + "cmask.png", cmask);
	//  printf("%s fbk %f fdet %f  hj  %f\n", m_pImageAllResult->strChannel.c_str(), fbk, fdet, hj);

	int worb = 0;
	if (fdet >= fbk)
	{
		worb = 1;
	}

	return 0.0;
}

int ImgCheckAnalysisy::CheckRun()
{

	// printf(">>>%s ================start \n", m_pImageAllResult->strBaseInfo.c_str());

	long t1, t2, t3, t4, t5, t6, t7;
	SetNewConfig();
	t1 = CheckUtil::getcurTime();

	CheckImgInit();
	if (DetImgInfo_shareP->bDebugsaveImg)
	{
		m_pdetlog->bPrintStr = true;
	}

	m_pdetlog->AddCheckstr(PrintLevel_0, "1、basic Info", "---------------------------1、basic Info---------------------------------");
	m_pdetlog->AddCheckstr(PrintLevel_0, "Version", "%s", GetVersion().c_str());
	m_pdetlog->AddCheckstr(PrintLevel_0, "ConfigVersion", "%s", m_pBasicConfig->strConfigVersion.c_str());
	m_pdetlog->AddCheckstr(PrintLevel_0, "Start", "%s", m_pImageAllResult->strBaseInfo.c_str());
	m_pdetlog->AddCheckstr(PrintLevel_0, "ImgageScale", "Scale_X = %f  Scale_Y = %f", m_fImgage_Scale_X, m_fImgage_Scale_Y);

	// 返回结果状态初始化
	m_CheckResult_shareP->checkStatus = 1;
	m_CheckResult_shareP->nresult = -1;

	m_CheckResult_shareP->basicResult.img_id = m_CheckResult_shareP->in_shareImage->img_id;
	m_CheckResult_shareP->basicResult.imgtype = m_CheckResult_shareP->in_shareImage->imgtype;
	m_CheckResult_shareP->basicResult.imgstr = m_CheckResult_shareP->in_shareImage->imgstr;
	m_CheckResult_shareP->basicResult.strChannel = m_CheckResult_shareP->in_shareImage->strChannel;
	m_strCurDetChannel = m_CheckResult_shareP->basicResult.strChannel;
	m_strCurDetCamChannel = m_pImageAllResult->cameraBaseResult->strCameraName + "_" + m_strCurDetChannel;

	// cout << "Version: " << GetVersion() << endl;
	// cout << "CameraName: " << m_pImageAllResult->cameraBaseResult->strCameraName << endl;
	// cout << "strChannel: " << m_CheckResult_shareP->basicResult.strChannel<< endl;

	// 2、参数检查
	int rec = ConfigCheck(DetImgInfo_shareP->img);
	if (rec != CHECK_OK)
	{
		m_pdetlog->AddCheckstr(PrintLevel_0, "Error", "ConfigCheck is error type = %d", rec);
		m_nErrorCode = rec;
		m_nCheckResultErrorCode = m_nErrorCode;
		return m_nErrorCode;
	}
	m_CutRoi = m_pImageAllResult->cameraBaseResult->pEdgeDetResult->cutRoi;

	m_Crop_Roi_paramImg = m_CutRoi;
	m_pImageAllResult->pDetResult->CutRoi = m_CutRoi;
	m_pImageAllResult->pDetResult->Param_CropRoi = m_Crop_Roi_paramImg;

	m_pFuntion = GetChannelFuntion(m_strCurDetChannel);
	int nfunction = 0;
	if (m_pFuntion != NULL)
	{
		m_pdetlog->AddCheckstr(PrintLevel_0, "Detect function", "%s",
							   m_pFuntion->GetInfo("").c_str());
	}
	else
	{
		nfunction = 1;
		m_pdetlog->AddCheckstr(PrintLevel_0, "Error", "m_pFuntion is NULL");
		m_nErrorCode = 22;
		m_nCheckResultErrorCode = m_nErrorCode;
		return m_nErrorCode;
	}

	// 1、检测前 必要的预处理。
	DetPreImage();

	m_pdetlog->AddCheckstr(PrintLevel_0, "AItask", "=======start:send AI task=======");
	// 多线程开启 AI 推理检测
	long time_AI_s = CheckUtil::getcurTime();
	// Other AI
	m_AI_Other_task = std::make_shared<TaskInfo>();
	m_AI_Other_task->taskname = Task_AI_Other;
	m_task.sendTask(m_AI_Other_task);

	// 缺陷检测
	m_AItask = std::make_shared<TaskInfo>();
	m_AItask->taskname = Task_AI;
	m_task.sendTask(m_AItask);

	ImgPreDet();
	// 更新检测区域
	Update_DetRoiList();

	m_CheckResult_shareP->nresult = 0;

	// 把临时可以绘制的结果都绘制出来。
	DrawResult_Step_1();

	long time_AI_e;
	// AI 推理生成
	{
		long t211 = CheckUtil::getcurTime();
		// 对AI的结果进行 处理，等待 AI 推理全部完成。
		rec = AIMaskDet();
		if (rec != CHECK_OK)
		{
			m_nErrorCode = rec;
			m_nCheckResultErrorCode = m_nErrorCode;
			return m_nErrorCode;
		}
		time_AI_e = CheckUtil::getcurTime();
		m_pdetlog->AddCheckstr(PrintLevel_0, "4、detect", "-------------------------2、AI Detect--------%ld wait AI complate %ld-------\n", time_AI_e - time_AI_s, time_AI_e - t211);

		Edge_Det();

		m_CheckResult_shareP->resultMaskImg = m_pImageAllResult->qx_DetAIResult->AI_MaskImg;

		// cv::imwrite("dddddddd.png", m_pImageAllResult->qx_DetAIResult->AI_MaskImg);
		// if (!m_pImageAllResult->qx_DetAIResult->AI_MaskImg.empty())
		// {
		// 	cv::imwrite("dddddddd.png", m_pImageAllResult->qx_DetAIResult->AI_MaskImg);
		// 	/* code */
		// }
		// else
		// {
		// 	m_pdetlog->AddCheckstr(PrintLevel_0, "4、detect", "m_pImageAllResult->qx_DetAIResult->empty()\n");

		// }
	}

	{

		t4 = CheckUtil::getcurTime();
		rec = GetCheckResultBLob();
		if (rec != CHECK_OK)
		{
			m_nErrorCode = rec;
			m_nCheckResultErrorCode = m_nErrorCode;
			return m_nErrorCode;
		}
		t5 = CheckUtil::getcurTime();
		m_pdetlog->AddCheckstr(PrintLevel_0, "5、BLob ", "------------------------ --------%ld  -------\n", t5 - t4);
	}
	// m_pdetlog->printLog(m_strCurDetChannel);

	long te = CheckUtil::getcurTime();
	if (m_strCurDetChannel == "Down-Particle")
	{
		m_pImageAllResult->cameraBaseResult->DPImg_Status = CameraBaseResult::ImageDet_Status_DetComplete;
		m_pImageAllResult->cameraBaseResult->DP_MaskImg = m_pImageAllResult->qx_DetAIResult->AI_MaskImg;
		m_pdetlog->AddCheckstr(PrintLevel_0, DET_LOG_LEVEL_3, "cameraBaseResult", "Down-Particle PImg_Status DetComplete %s", CheckUtil::getCurTimeHMS().c_str());
	}
	if (m_strCurDetChannel == "Up-Particle")
	{
		m_pImageAllResult->cameraBaseResult->UpImg_Status = CameraBaseResult::ImageDet_Status_DetComplete;
		m_pImageAllResult->cameraBaseResult->UP_MaskImg = m_pImageAllResult->qx_DetAIResult->AI_MaskImg;
		m_pdetlog->AddCheckstr(PrintLevel_0, DET_LOG_LEVEL_3, "cameraBaseResult", "Up-Particle UpImg_Status DetComplete %s", CheckUtil::getCurTimeHMS().c_str());
	}

	m_pdetlog->AddCheckstr(PrintLevel_1, "result", "  ALL use Time %ld   AI %ld blob %ld",
						   te - t1, time_AI_e - time_AI_s, t5 - t4);

	m_pdetlog->AddCheckstr(PrintLevel_0, DET_LOG_LEVEL_3, "End", " Check Run");

	return 0;
}

int ImgCheckAnalysisy::SetNewConfig()
{
	if (m_nConfigIdx < 0)
	{
		return 1;
		/* code */
	}

	if (m_pConfig->GetConfigUpdataStatus(ConfigType_Analysisy_Common_XL, m_nConfigIdx))
	{
		printf("**************  ImgCheckAnalysisy::SetNewConfig    m_nConfigIdx %d\n", m_nConfigIdx);
		m_pConfig->GetConfig(ConfigType_Analysisy_Common_XL, &m_AnalysisyConfig);
		if (m_AnalysisyConfig.commonCheckConfig.nodeConfigArr.size() > 0)
		{
			m_pCommonAnalysisyConfig = &m_AnalysisyConfig.commonCheckConfig.nodeConfigArr.at(0);
			m_pBasicConfig = &m_AnalysisyConfig.commonCheckConfig.baseConfig;
			m_pRegionAnalysisyParam = &m_pCommonAnalysisyConfig->regionConfigArr.at(0);
			GetParamidx();
			UpdateImgageScale();
			UPdateLDConfig();
			if (true)
			{
				printf("SetNewConfig m_nConfigIdx %d m_CheckConfig.strSkuName %s \n", m_nConfigIdx, m_AnalysisyConfig.strSkuName.c_str());
			}
		}
		else
		{
			printf("m_AnalysisyConfig.commonCheckConfig.nodeConfigArr == 0  \n");
		}
	}
	else
	{
		// printf("ConfigType_Analysisy_Common_XL no Update  \n");
	}
	m_nErrorCode = CHECK_OK;
	return CHECK_OK;
}

int ImgCheckAnalysisy::GetParamidx()
{
	int region = 0;
	if (m_pCommonAnalysisyConfig->regionConfigArr.size() <= 0)
	{
		return 1;
	}

	CheckConfig_Regions_type *p = &m_pCommonAnalysisyConfig->regionConfigArr.at(region).checkConfig_Regions_type[0];
	for (int iqx = 0; iqx < CONFIG_QX_NAME_count; iqx++)
	{
		m_QxInParamListIdx[iqx] = -1;
		std::string strqx_name = CONFIG_QX_NAME_Names[iqx];
		for (int i = 0; i < p->checkConfig_Regions_Param.size(); i++)
		{
			std::string strconfig_name = p->checkConfig_Regions_Param[i].param_name;

			// getchar();
			if (strqx_name == strconfig_name)
			{
				printf("strqx_name %s  strconfig_name %s \n", strqx_name.c_str(), strconfig_name.c_str());
				m_QxInParamListIdx[iqx] = i;
				break;
			}
		}
	}
	// getchar();
	return 0;
}

ChannelCheckFunction *ImgCheckAnalysisy::GetChannelFuntion(std::string strChannelName)
{
	ChannelCheckFunction *p = NULL;
	for (int i = 0; i < m_AnalysisyConfig.checkFunction.channelFunctionArr.size(); i++)
	{
		if (CheckUtil::compareIgnoreCase(m_AnalysisyConfig.checkFunction.channelFunctionArr[i].strChannelName, strChannelName))
		{
			p = &m_AnalysisyConfig.checkFunction.channelFunctionArr[i];
		}
	}

	return p;
}
int ImgCheckAnalysisy::Run(int nId)
{
	// std::vector<int> vi;
	// vi.push_back(nId);
	// auto nRet = set_cpu_id(vi);
	// printf("Check So %d bind cpu ret %d, %d\n", m_nThreadIdx, nRet, nId);
	while (!m_bExit)
	{
		// 数据准备完成，开启检测
		if (m_nRun_Status == CHECK_THREAD_STATUS_READY)
		{
			m_nRun_Status = CHECK_THREAD_STATUS_BUSY;
			/* 检测 */
			CheckRun();
			m_nRun_Status = CHECK_THREAD_STATUS_COMPLETE;
			m_pImageAllResult->setStep(ImageAllResult::DetStep_Complet);
			m_nRun_Status = CHECK_THREAD_STATUS_IDLE;
			// printf("*--------%d\n", m_nRun_Status);
		}
		else
		{

			usleep(1000);
		}
		// printf("*-");
		usleep(1000);
	}
	return 0;
}
int ImgCheckAnalysisy::set_cpu_id(const std::vector<int> &cpu_set_vec)
{
	// for cpu affinity
	int nRet = 0;
#ifdef __linux
	cpu_set_t _cur_cpu_set;
	CPU_ZERO(&_cur_cpu_set);
	for (auto _id : cpu_set_vec)
	{
		CPU_SET(_id, &_cur_cpu_set);
	}
	if (0 > pthread_setaffinity_np(pthread_self(), sizeof(cpu_set_t), &_cur_cpu_set))
	{
		perror("set cpu affinity failed: ");
		printf("Warning: set cpu affinity failed ... ...\n");
		nRet = -1;
	}
#endif //__linux
	return nRet;
}

int ImgCheckAnalysisy::CalBlob_Other()
{

	m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, "CalBlob_Other", " Start");
	CalBLobMean_GrayDis();

	float fs_x = m_fImgage_Scale_X;
	float fs_y = m_fImgage_Scale_Y;

	float fs_resize_x = m_pImageAllResult->fscale_detToresult_x;
	float fs_resize_y = m_pImageAllResult->fscale_detToresult_y;
	// 遍历每个检测blob
	for (int i = 0; i < blobs.blobCount; i++)
	{

		// m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, "Blob", "%d/%d   start", i, blobs.blobCount);

		cv::Rect roi;
		roi.x = blobs.blobTab[i].minx;
		roi.y = blobs.blobTab[i].miny;
		roi.width = blobs.blobTab[i].maxx - blobs.blobTab[i].minx + 1;
		roi.height = blobs.blobTab[i].maxy - blobs.blobTab[i].miny + 1;
		int config_qx_type = blobs.blobTab[i].ErrType;

		std::shared_ptr<ImageAllResult::Image_AI_Det_Result> pDetAIResult = m_pImageAllResult->qx_DetAIResult;
		// 127cell 检测类型。
		if (config_qx_type == CONFIG_QX_NAME_white_Cell || config_qx_type == CONFIG_QX_NAME_black_Cell)
		{
			pDetAIResult = m_pImageAllResult->cell127_DetAIResult;
		}

		cv::Mat maskImg = pDetAIResult->AI_MaskImg;

		//  精确计算长度
		float re_len = Cal_QXLen(maskImg(roi), config_qx_type, fs_x, fs_y);

		cv::Scalar result = calc_blob_info_withstats(m_pImageAllResult->detImg, maskImg, roi);

		int QX_whiteBLACK = CONFIG_QX_BLACK;
		if (result[0] > 0)
		{
			QX_whiteBLACK = CONFIG_QX_WHITE;
		}

		double energe = result[1];
		blobs.blobTab[i].energy = energe;

		float JudgArea = blobs.blobTab[i].area * fs_x * fs_y;
		blobs.blobTab[i].JudgArea = JudgArea;
		float flen = roi.width * fs_x;
		if (roi.height * fs_y > flen)
		{
			flen = roi.height * fs_y;
		}

		if (re_len > flen)
		{
			flen = re_len;
		}

		blobs.blobTab[i].len = flen;

		// m_pdetlog->AddCheckstr(PrintLevel_3, " CalBlob_Other ", "qx %d ErrType %d ", i, blobs.blobTab[i].ErrType);
	}
	return 0;
}

int ImgCheckAnalysisy::CalBLobMean_GrayDis()
{
	if (blobs.blobCount <= 0)
	{
		return 0;
	}

	cv::Size sz;
	sz.width = 640;
	sz.height = 480;
	cv::Mat temimg;
	cv::resize(m_pImageAllResult->detImg, temimg, sz, 0, 0, 1);
	cv::Rect roi1;
	roi1.x = 0;
	roi1.y = 0;
	roi1.width = temimg.cols;
	roi1.height = temimg.rows;

	cv::Rect roi2;
	roi2.x = 0;
	roi2.y = 0;
	roi2.width = temimg.cols;
	roi2.height = temimg.rows;

	int mean1 = 0;
	int mean2 = 0;
	// 上黑下白 。。。。
	if (m_pImageAllResult->bWhiteOrBlackImg)
	{
		m_pImageAllResult->pWTB_Check_Result = std::make_shared<ImageAllResult::WTB_Check_Result_>();

		cv::Mat binary_image;
		// 应用模糊

		cv::blur(temimg, temimg, cv::Size(3, 3)); // 15x15 的模糊核
		cv::threshold(temimg, binary_image, 100, 255, cv::THRESH_BINARY);
		// 寻找轮廓
		std::vector<std::vector<cv::Point>> contours;
		cv::findContours(binary_image, contours, cv::RETR_EXTERNAL, cv::CHAIN_APPROX_SIMPLE);

		// 找到最大轮廓
		double max_area = 0;
		int max_area_contour_index = -1;
		for (size_t i = 0; i < contours.size(); ++i)
		{
			double area = cv::contourArea(contours[i]);
			if (area > max_area)
			{
				max_area = area;
				max_area_contour_index = i;
			}
		}
		// cv::imwrite("temimg123.png", temimg);
		// cv::imwrite("binary_image.png", binary_image);
		// printf("max_area_contour_index %d \n", max_area_contour_index);
		// getchar();
		if (max_area_contour_index >= 0)
		{

			float fx = m_pImageAllResult->detImg.cols * 1.0f / temimg.cols;
			float fy = m_pImageAllResult->detImg.rows * 1.0f / temimg.rows;

			float fs_resize_x = m_pImageAllResult->fscale_detToresult_x;
			float fs_resize_y = m_pImageAllResult->fscale_detToresult_y;

			// 计算最大轮廓的外接矩形
			cv::Rect bounding_rect = cv::boundingRect(contours[max_area_contour_index]);

			cv::Rect roi_wtb = bounding_rect;
			if (roi_wtb.x < 5)
			{
				roi_wtb.x = 0;
			}
			// printf("   \n\n\n\n\n%d %d %d %d   %d %d   \n\n",roi_wtb.x ,roi_wtb.y ,roi_wtb.width ,roi_wtb.height,temimg.cols,temimg.rows);
			if (temimg.cols - (roi_wtb.x + roi_wtb.width) < 5)
			{
				roi_wtb.width = temimg.cols - roi_wtb.x;
			}
			// printf("   \n\n\n\n\n%d %d %d %d   %d %d   \n\n",roi_wtb.x ,roi_wtb.y ,roi_wtb.width ,roi_wtb.height,temimg.cols,temimg.rows);
			if (roi_wtb.y < 5)
			{
				roi_wtb.y = 0;
			}
			if (temimg.rows - (roi_wtb.y + roi_wtb.height) < 5)
			{
				roi_wtb.height = temimg.rows - roi_wtb.y;
			}

			m_pImageAllResult->pWTB_Check_Result->roi_src.x = roi_wtb.x * fx;
			m_pImageAllResult->pWTB_Check_Result->roi_src.y = roi_wtb.y * fy;
			m_pImageAllResult->pWTB_Check_Result->roi_src.width = roi_wtb.width * fx;
			m_pImageAllResult->pWTB_Check_Result->roi_src.height = roi_wtb.height * fy;

			// printf("   \n\n\n\n\n%d %d %d %d   %d %d   \n\n",m_OtherResult.WTB_Check_Result.roi_src.x ,m_OtherResult.WTB_Check_Result.roi_src.y ,m_OtherResult.WTB_Check_Result.roi_src.width ,m_OtherResult.WTB_Check_Result.roi_src.height, m_TemCheck.temImgList[TEM_IMG_IDX_SrcCrop].cols, m_TemCheck.temImgList[TEM_IMG_IDX_SrcCrop].rows);

			m_pImageAllResult->pWTB_Check_Result->roi_show.x = m_pImageAllResult->pWTB_Check_Result->roi_src.x * fs_resize_x;
			m_pImageAllResult->pWTB_Check_Result->roi_show.y = m_pImageAllResult->pWTB_Check_Result->roi_src.y * fs_resize_y;
			m_pImageAllResult->pWTB_Check_Result->roi_show.width = m_pImageAllResult->pWTB_Check_Result->roi_src.width * fs_resize_x;
			m_pImageAllResult->pWTB_Check_Result->roi_show.height = m_pImageAllResult->pWTB_Check_Result->roi_src.height * fs_resize_y;

			// printf("   \n\n\n\n\n%d %d %d %d   %d %d   \n\n",m_OtherResult.WTB_Check_Result.roi_show.x ,m_OtherResult.WTB_Check_Result.roi_show.y ,m_OtherResult.WTB_Check_Result.roi_show.width ,m_OtherResult.WTB_Check_Result.roi_show.height,m_TemCheck.temImgList[TEM_IMG_IDX_Result].cols,m_TemCheck.temImgList[TEM_IMG_IDX_Result].rows);

			int dis_w = std::abs(bounding_rect.width - temimg.cols);
			int dis_h = std::abs(bounding_rect.height - temimg.rows);

			if (dis_w < dis_h)
			{
				int line_h_up = std::abs(bounding_rect.y - 0);
				int line_h_dpwn = std::abs(bounding_rect.y + bounding_rect.height - temimg.rows);
				if (line_h_up > line_h_dpwn)
				{
					roi1.x = 0;
					roi1.y = 0;
					roi1.width = temimg.cols;
					roi1.height = bounding_rect.y;

					roi2.x = 0;
					roi2.y = bounding_rect.y;
					roi2.width = temimg.cols;
					roi2.height = temimg.rows - bounding_rect.y;
				}
				else
				{
					roi1.x = 0;
					roi1.y = 0;
					roi1.width = temimg.cols;
					roi1.height = bounding_rect.y + bounding_rect.height;

					roi2.x = 0;
					roi2.y = bounding_rect.y + bounding_rect.height;
					roi2.width = temimg.cols;
					roi2.height = temimg.rows - (bounding_rect.y + bounding_rect.height);
				}
			}
			else
			{
				int line_w_l = std::abs(bounding_rect.x - 0);
				int line_w_r = std::abs(bounding_rect.x + bounding_rect.width - temimg.cols);
				if (line_w_l > line_w_r)
				{
					roi1.x = 0;
					roi1.y = 0;
					roi1.width = bounding_rect.x;
					roi1.height = temimg.rows;

					roi2.x = bounding_rect.x;
					roi2.y = 0;
					roi2.width = temimg.cols - bounding_rect.x;
					roi2.height = temimg.rows;
				}
				else
				{
					roi1.x = 0;
					roi1.y = 0;
					roi1.width = bounding_rect.x + bounding_rect.width;
					roi1.height = temimg.rows;

					roi2.x = bounding_rect.x + bounding_rect.width;
					roi2.y = 0;
					roi2.width = temimg.cols - (bounding_rect.x + bounding_rect.width);
					roi2.height = temimg.rows;
				}
			}

			// 是否要存图
			if (m_pImageAllResult->result->in_shareImage->bDebugsaveImg)
			{
				cv::Mat showimg;
				cv::cvtColor(temimg, showimg, cv::COLOR_GRAY2BGR);
				cv::rectangle(showimg, bounding_rect, cv::Scalar(0, 255, 0), 4);
				cv::rectangle(showimg, roi1, cv::Scalar(255, 0, 0), 2);
				cv::rectangle(showimg, roi2, cv::Scalar(0, 0, 255), 2);
				cv::imwrite(m_strCurDetCamChannel + "graydis.png", showimg);
			}
			// cv::Mat showimg;
			// cv::cvtColor(temimg, showimg, cv::COLOR_GRAY2BGR);
			// cv::rectangle(showimg, bounding_rect, cv::Scalar(0, 255, 0), 2);
			// cv::rectangle(showimg, roi1, cv::Scalar(255, 0, 0), 2);
			// cv::rectangle(showimg, roi2, cv::Scalar(0, 0, 255), 2);
			// cv::imwrite("ddddd.png", showimg);
			// getchar();

			cv::Rect mean_roi1;
			int dw1 = roi1.width * 0.1;
			if (dw1 < 10)
			{
				dw1 = 10;
			}
			int dh1 = roi1.height * 0.1;
			if (dh1 < 10)
			{
				dh1 = 10;
			}
			mean_roi1.x = roi1.x + dw1;
			mean_roi1.y = roi1.y + dh1;
			mean_roi1.width = roi1.width - 2 * dw1;
			mean_roi1.height = roi1.height - 2 * dh1;

			CheckUtil::CheckRect(mean_roi1, temimg.cols, temimg.rows);

			cv::Scalar mean_v1 = cv::mean(temimg(mean_roi1));
			mean1 = mean_v1[0];

			cv::Rect mean_roi2;
			int dw2 = roi2.width * 0.1;
			if (dw2 < 10)
			{
				dw2 = 10;
			}
			int dh2 = roi2.height * 0.1;
			if (dh2 < 10)
			{
				dh2 = 10;
			}
			mean_roi2.x = roi2.x + dw2;
			mean_roi2.y = roi2.y + dh2;
			mean_roi2.width = roi2.width - 2 * dw2;
			mean_roi2.height = roi2.height - 2 * dh2;
			CheckUtil::CheckRect(mean_roi2, temimg.cols, temimg.rows);

			cv::Scalar mean_v2 = cv::mean(temimg(mean_roi2));
			mean2 = mean_v2[0];
			if (m_pImageAllResult->result->in_shareImage->bDebugsaveImg)
			{
				cv::Mat showimg;
				cv::cvtColor(temimg, showimg, cv::COLOR_GRAY2BGR);
				cv::rectangle(showimg, bounding_rect, cv::Scalar(0, 255, 0), 2);
				cv::rectangle(showimg, roi1, cv::Scalar(255, 0, 0), 2);
				cv::rectangle(showimg, roi2, cv::Scalar(0, 0, 255), 2);

				cv::rectangle(showimg, mean_roi1, cv::Scalar(255, 255, 0), 2);

				cv::rectangle(showimg, mean_roi2, cv::Scalar(255, 255, 0), 2);
				cv::imwrite(m_strCurDetCamChannel + "graydis222.png", showimg);
			}
		}
		else
		{
			cv::Scalar mean_v1 = cv::mean(temimg(roi1));
			mean1 = mean_v1[0];
			mean2 = mean1;
		}
	}
	else
	{
		cv::Scalar mean_v1 = cv::mean(temimg(roi1));
		mean1 = mean_v1[0];
		mean2 = mean1;
	}

	// printf("mean1 %d mean2 %d\n", mean1, mean2);

	float fsx = m_pImageAllResult->detImg.cols * 1.0f / temimg.cols;
	float fsy = m_pImageAllResult->detImg.rows * 1.0f / temimg.rows;

	roi1.x *= fsx;
	roi1.y *= fsy;
	roi1.width *= fsx;
	roi1.height *= fsy;

	roi2.x *= fsx;
	roi2.y *= fsy;
	roi2.width *= fsx;
	roi2.height *= fsy;

	int expand = 20;

	for (int i = 0; i < blobs.blobCount; i++)
	{
		cv::Rect roi;
		roi.x = blobs.blobTab[i].minx;
		roi.y = blobs.blobTab[i].miny;
		roi.width = blobs.blobTab[i].maxx - blobs.blobTab[i].minx + 1;
		roi.height = blobs.blobTab[i].maxy - blobs.blobTab[i].miny + 1;
		cv::Point p;
		p.x = roi.x + roi.width * 0.5;
		p.y = roi.y + roi.height * 0.5;
		cv::Rect det_roi = roi1;
		int mean_v = mean1;
		if (p.x >= roi1.x && p.x <= (roi1.x + roi1.width) &&
			p.y >= roi1.y && p.y <= (roi1.y + roi1.height))
		{
			mean_v = mean1;
			det_roi = roi1;
		}
		else
		{
			mean_v = mean2;
			det_roi = roi2;
		}

		int config_qx_type = blobs.blobTab[i].ErrType;

		std::shared_ptr<ImageAllResult::Image_AI_Det_Result> pDetAIResult = m_pImageAllResult->qx_DetAIResult;
		// 127cell 检测类型。
		if (config_qx_type == CONFIG_QX_NAME_white_Cell || config_qx_type == CONFIG_QX_NAME_black_Cell)
		{
			pDetAIResult = m_pImageAllResult->cell127_DetAIResult;
		}

		cv::Mat maskImg = pDetAIResult->AI_MaskImg;

		CalBlobHJ(m_pImageAllResult->detImg, maskImg, det_roi, roi);

		// 寻找图像的最大灰度值和其位置
		double min_val,
			max_val;
		cv::Point min_loc, max_loc;
		cv::minMaxLoc(m_pImageAllResult->detImg(roi), &min_val, &max_val, &min_loc, &max_loc);
		// printf("mean %d  max %f \n", mean_v, max_val);
		cv::Scalar mean123 = cv::mean(m_pImageAllResult->detImg(roi));
		int mean_roi = mean123[0];
		blobs.blobTab[i].maxValue = max_val;
		blobs.blobTab[i].grayDis = std::abs(mean_v - max_val);
		// 黑色
		if (mean_roi < (mean_v - blobs.blobTab[i].grayDis))
		{
			blobs.blobTab[i].grayDis = std::abs(mean_v - mean_roi);
		}
		if (mean_roi < mean_v)
		{
			blobs.blobTab[i].whiteOrblack = CONFIG_QX_BLACK;
		}
		else
		{
			blobs.blobTab[i].whiteOrblack = CONFIG_QX_WHITE;
		}

		// 黑色的
		if (blobs.blobTab[i].whiteOrblack == CONFIG_QX_BLACK)
		{
			if (config_qx_type == CONFIG_QX_NAME_white_Cell || config_qx_type == CONFIG_QX_NAME_black_Cell)
			{
				blobs.blobTab[i].ErrType = CONFIG_QX_NAME_black_Cell;
			}
		}
	}
	return 0;
}

int ImgCheckAnalysisy::GetClassImg(const cv::Mat &img, cv::Mat &AIdetImg, cv::Rect qx_roi, int detwidth, int detheight)
{

	cv::Rect cutroi;
	cv::Rect roi = qx_roi;
	bool bresize = false;
	{

		int pc_x = roi.x + roi.width * 0.5;
		int pc_y = roi.y + roi.height * 0.5;

		if (roi.width < detwidth && roi.height < detheight)
		{
			cutroi.width = detwidth;
			cutroi.x = pc_x - detwidth * 0.5;
			cutroi.height = detheight;
			cutroi.y = pc_y - detheight * 0.5;
		}
		else
		{
			// 宽 高
			if (roi.width > roi.height)
			{
				cutroi.width = roi.width + 20;
				cutroi.x = roi.x - 10;

				float fsx = detheight * 1.0f / detwidth;
				cutroi.height = cutroi.width * fsx;
				cutroi.y = pc_y - cutroi.height * 0.5;
			}
			else
			{
				cutroi.height = roi.height + 20;
				cutroi.y = roi.y - 10;

				float fsy = detwidth * 1.0f / detheight;
				cutroi.width = cutroi.height * fsy;
				cutroi.x = pc_x - cutroi.width * 0.5;
			}

			bresize = true;
		}

		if (cutroi.x < 0)
		{
			cutroi.x = 0;
		}
		if (cutroi.y < 0)
		{
			cutroi.y = 0;
		}
		if (cutroi.x + cutroi.width >= img.cols)
		{
			cutroi.x = img.cols - cutroi.width;
			if (cutroi.x < 0)
			{
				cutroi.x = 0;
				if (cutroi.x + cutroi.width >= img.cols)
				{
					cutroi.width = img.cols;
				}
			}
		}
		if (cutroi.y + cutroi.height >= img.rows)
		{
			cutroi.y = img.rows - cutroi.height;
			if (cutroi.y < 0)
			{
				cutroi.y = 0;
				if (cutroi.y + cutroi.height >= img.rows)
				{
					cutroi.height = img.rows;
				}
			}
		}
	}
	if (!CheckUtil::RoiInImg(cutroi, img))
	{
		return 1;
	}
	cv::Size sz;
	sz.width = detwidth;
	sz.height = detheight;
	if (cutroi.width != sz.width || cutroi.height != sz.height)
	{
		cv::resize(img(cutroi), AIdetImg, sz);
	}
	else
	{
		AIdetImg = img(cutroi).clone();
	}

	if (1 != AIdetImg.channels())
	{
		cv::cvtColor(AIdetImg, AIdetImg, cv::COLOR_BGR2GRAY);
	}
	return 0;
}

float ImgCheckAnalysisy::Cal_QXLen(cv::Mat qx_maskImg, int qx_type, float fsc_x, float fsc_y)
{

	float nlen = -1;
	cv::Mat detimg = qx_maskImg;

	// 寻找轮廓
	vector<vector<Point>> contours;
	cv::findContours(detimg, contours, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE);

	// 找到最大面积的轮廓
	double maxArea = -1;
	int maxAreaIdx = -1;
	for (size_t i = 0; i < contours.size(); ++i)
	{
		double area = contourArea(contours[i]);
		if (area > maxArea)
		{
			maxArea = area;
			maxAreaIdx = i;
		}
	}

	// 如果找到了最大面积的轮廓
	if (maxAreaIdx >= 0)
	{

		// 使用minAreaRect找到最小外接矩形
		cv::RotatedRect rect = cv::minAreaRect(contours[maxAreaIdx]);

		// // 绘制最小外接矩形
		// Point2f vertices[4];
		// rect.points(vertices);
		// for (int i = 0; i < 4; ++i)
		// {
		// 	line(detimg, vertices[i], vertices[(i + 1) % 4], Scalar(128, 255, 0), 2); // 绿色线
		// }
		// 输出结果

		// 获取最小外接矩形的尺寸
		float width = rect.size.width;
		float height = rect.size.height;

		// std::cout << "1 Width: " << width << ", Height: " << height << std::endl;
		Point2f vertices[4];
		rect.points(vertices);

		vector<Point2f> newcont;
		for (int i = 0; i < 4; ++i)
		{
			Point2f p;
			p.x = vertices[i].x * fsc_x;
			p.y = vertices[i].y * fsc_y;
			newcont.push_back(p);
		}
		vector<vector<Point2f>> contours_New;
		contours_New.push_back(newcont);
		// Recreate the rotated rectangle with scaled vertices
		RotatedRect scaledRect = minAreaRect(contours_New[0]);

		// Calculate scaled width and height
		width = scaledRect.size.width;
		height = scaledRect.size.height;
		// std::cout << "2 width: " << width << ", height: " << height << std::endl;
		//  float scale = 0.5; // 缩放比例
		//  rect.size.width *= fsc_x;
		//  rect.size.height *= fsc_y;
		//  std::cout << "fsc_x: " << fsc_x << ", fsc_y: " << fsc_y << std::endl;
		//  std::cout << "Width: " << width << ", Height: " << height << std::endl;
		//  获取最小外接矩形的尺寸
		//  width = rect.size.width;
		//  height = rect.size.height;
		if (width > height)
		{
			nlen = width;
			/* code */
		}
		else
		{
			nlen = height;
		}
	}

	// getchar();
	return nlen;
}

float ImgCheckAnalysisy::CalImgScorl(cv::Mat det_img, cv::Mat up_img)
{

	float fs = 0;

	unsigned char *det_img_data = (unsigned char *)det_img.data;
	unsigned char *up_img_data = (unsigned char *)up_img.data;
	int w = det_img.cols;
	int h = det_img.rows;
	int pitch = w;
	int offset = 0;
	int sum_jc = 0; // 交集 都有的
	int sum_bj = 0; // 并集 有一个有的
	int sum_up = 0;
	int sum_det = 0;
	for (int y = 0; y < h; y++)
	{
		offset = y * pitch;
		int kh = 0;
		for (int x = 0; x < w; x++)
		{

			if (det_img_data[offset] != 0 && up_img_data[offset] != 0)
			{
				sum_jc++;
				sum_bj++;
				sum_up++;
				sum_det++;
			}
			else if (det_img_data[offset] != 0 || up_img_data[offset] != 0)
			{
				sum_bj++;
				if (det_img_data[offset] != 0)
				{
					sum_det++;
				}
				if (up_img_data[offset] != 0)
				{
					sum_up++;
				}
			}
			offset++;
		}
	}
	if (sum_bj != 0)
	{
		fs = sum_jc * 1.0f / sum_bj;
	}
	m_pdetlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "Up Mask  ", "sum_bj %d sum_jc %d sum_up %d sum_det %d", sum_bj, sum_jc, sum_up, sum_det);
	if (sum_up > sum_det * 2)
	{
		// fs = 0;
	}

	return fs;
}
float ImgCheckAnalysisy::CalImgScorl_t(cv::Mat det_img, cv::Mat up_img)
{

	float fs = 0;

	unsigned char *det_img_data = (unsigned char *)det_img.data;
	unsigned char *up_img_data = (unsigned char *)up_img.data;
	int w = det_img.cols;
	int h = det_img.rows;
	int pitch = w;
	int offset = 0;
	int sum_jc = 0; // 交集 都有的
	int sum_bj = 0; // 并集 有一个有的
	int sum_up = 0;
	int sum_det = 0;
	for (int y = 0; y < h; y++)
	{
		offset = y * pitch;
		int kh = 0;
		for (int x = 0; x < w; x++)
		{

			if (det_img_data[offset] != 0 && up_img_data[offset] != 0)
			{
				sum_jc++;
				sum_bj++;
				sum_up++;
				sum_det++;
			}
			else if (det_img_data[offset] != 0 || up_img_data[offset] != 0)
			{
				sum_bj++;
				if (det_img_data[offset] != 0)
				{
					sum_det++;
				}
				if (up_img_data[offset] != 0)
				{
					sum_up++;
				}
			}
			offset++;
		}
	}
	if (sum_bj != 0)
	{
		fs = sum_jc * 1.0f / sum_bj;
	}

	return fs;
}
int ImgCheckAnalysisy::GetCheckResultBLob()
{
	m_pdetlog->AddCheckstr(PrintLevel_0, "GetCheckResultBLob", "=======start");
	long t1, t2, t3, t4, t5, t6, t7;
	t1 = CheckUtil::getcurTime();
	// 获得所有的缺陷的blob 信息。
	int re = GetALLBlob();
	if (re != 0)
	{
		return re;
	}
	// 缺陷分类 多线程 实现。
	long t11 = CheckUtil::getcurTime();
	// 只进行blob分析。
	if (m_pFuntion->function.f_OnlyBLob.bOpen)
	{
		m_pdetlog->AddCheckstr(PrintLevel_1, "GetCheckResultBLob", "------ f_OnlyBLob = true\n");
		m_pImageAllResult->bOnlyBlob = true;
	}
	else
	{

		m_Classtask = std::make_shared<TaskInfo>();
		m_Classtask->taskname = Task_Class;
		m_task.sendTask(m_Classtask);
	}

	// 计算blob 的其他信息，如灰阶、长度、密度等待。
	re = CalBlob_Other();
	if (re != 0)
	{
		return re;
	}
	long t12 = CheckUtil::getcurTime();
	// 等待分类 完成。
	if (m_Classtask != nullptr)
	{
		m_Classtask->waitComplate();
	}

	// m_Classtask->waitComplate();

	long t13 = CheckUtil::getcurTime();
	m_pdetlog->AddCheckstr(PrintLevel_1, "GetCheckResultBLob", "=========== ALL time %ld  waite class time %ld\n", t13 - t11, t13 - t12);
	// printf("=========== cls time %ld  waite time %ld\n", t13 - t11, t13 - t12);

	BLobToDetResult();

	return 0;
}

int ImgCheckAnalysisy::LDJudge(int nconfigtype, cv::Rect roi, float JudgeArea, int maxV, int hj, std::shared_ptr<DetLog> pQxlog)
{
	int dbresult = UseDPMask(0, nconfigtype, roi, JudgeArea, maxV, hj, pQxlog);
	if (dbresult > 0)
	{
		return 1;
	}

	return 0;
}

int ImgCheckAnalysisy::UseDPMask(int L0, int nconfigtype, cv::Rect roi, float JudgeArea, int maxV, int hj, std::shared_ptr<DetLog> pQxlog)
{
	if (!m_pFuntion->function.f_LDConfig.bOpen)
	{
		pQxlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "LD Analysis", "function close");
		return 0;
	}
	// 要使用 DP 的结果
	if (m_pFuntion->function.f_LDConfig.bUseDP)
	{
		cv::Mat DPMaskImg = m_pImageAllResult->cameraBaseResult->DP_MaskImg;
		pQxlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "LD Analysis", "Use Dp Mask");
		if (DPMaskImg.empty())
		{
			pQxlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "LD Analysis", "Error  Dp Mask is empty");
			return 0;
		}
		if (true && DetImgInfo_shareP->otherValue == 9)
		{
			cv::imwrite("DPMaskImgj.png", DPMaskImg);
			// getchar();
		}

		bool bhave = false;
		{

			float fiou = CalImgScorl_t(m_pImageAllResult->qx_DetAIResult->AI_MaskImg(roi).clone(), DPMaskImg(roi).clone());

			// IOU
			if (fiou > m_pFuntion->function.f_LDConfig.fDP_IOU)
			{
				pQxlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "LD Analysis", " fiou %f  > %f ", fiou, m_pFuntion->function.f_LDConfig.fDP_IOU);
				bhave = true;
				// break;
			}
			else
			{
				pQxlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "LD Analysis", " fiou %f  <= %f ", fiou, m_pFuntion->function.f_LDConfig.fDP_IOU);
			}

			// m_TemCheck.AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "UseDPMask", " fiou %f  < 0.1 ", fiou);
		}
		// 上电(L0)有 下电（DP）没有
		if (bhave)
		{
			pQxlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "LD Analysis", "  =  DP ");
			return 0;
		}
		else
		{
			pQxlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "LD Analysis", "  !=  DP ");
		}
	}
	else
	{
		pQxlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "LD Analysis", "No Use Dp Mask");
	}

	bool bhave = false;
	if (m_pFuntion->function.f_LDConfig.bHSLD)
	{
		float aT1 = m_LD_HSConfig.minArea;
		float aT2 = m_LD_HSConfig.maxArea;
		int vT = m_LD_HSConfig.hj;
		if (JudgeArea >= aT1 &&
			JudgeArea <= aT2 &&
			hj >= vT)
		{
			bhave = true;
		}
		pQxlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "HS LD check ", "result %s -> JudgeArea %f [%f %f] hj %d %s %d ",
							BOOL_TO_STR(bhave),
							JudgeArea, aT1, aT2,
							hj, BOOL_TO_ThanLess(hj > vT), vT);
	}
	else if (m_pFuntion->function.f_LDConfig.bWTBLD)
	{
		float aT1 = m_LD_WTBConfig.minArea;
		float aT2 = m_LD_WTBConfig.maxArea;
		int vT = m_LD_WTBConfig.hj;
		if (JudgeArea >= aT1 &&
			JudgeArea <= aT2 &&
			hj >= vT)
		{
			bhave = true;
		}
		pQxlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "WTB LD check ", "result %s -> JudgeArea %f [%f %f] hj %d %s %d ",
							BOOL_TO_STR(bhave),
							JudgeArea, aT1, aT2,
							hj, BOOL_TO_ThanLess(hj > vT), vT);
	}
	else
	{
		float aT1 = m_LDConfig.minArea;
		float aT2 = m_LDConfig.maxArea;
		int vT = m_LDConfig.hj;
		if (JudgeArea >= aT1 &&
			JudgeArea <= aT2 &&
			hj >= vT)
		{
			bhave = true;
		}
		pQxlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "L0  LD check ", "result %s -> JudgeArea %f [%f %f] hj %d %s %d ",
							BOOL_TO_STR(bhave),
							JudgeArea, aT1, aT2,
							hj, BOOL_TO_ThanLess(hj > vT), vT);
	}

	if (bhave)
	{
		return 1;
	}

	return 0;
}

int ImgCheckAnalysisy::UPdateLDConfig()
{
	for (int i = 0; i < CONFIG_QX_NAME_count; i++)
	{
		if (i != CONFIG_QX_NAME_LD)
		{
			continue;
		}
		int paramIdx = m_QxInParamListIdx[i];
		if (paramIdx < 0)
		{
			continue;
		}

		CheckConfig_Regions_Param *pParam = &m_pRegionAnalysisyParam->checkConfig_Regions_type[ANALYSIS_TYPE_TF].checkConfig_Regions_Param.at(paramIdx);
		for (int j = 0; j < pParam->useNum; j++)
		{
			if (!pParam->paramArr[j].bEnable)
			{
				continue;
			}
			m_LDConfig.minArea = pParam->paramArr[j].area;
			m_LDConfig.maxArea = pParam->paramArr[j].area_max;
			m_LDConfig.hj = pParam->paramArr[j].hj;
			m_LDConfig.buse = true;
		}
	}
	for (int i = 0; i < CONFIG_QX_NAME_count; i++)
	{
		if (i != CONFIG_QX_NAME_LD_WTB)
		{
			continue;
		}
		int paramIdx = m_QxInParamListIdx[i];
		if (paramIdx < 0)
		{
			continue;
		}
		CheckConfig_Regions_Param *pParam = &m_pRegionAnalysisyParam->checkConfig_Regions_type[ANALYSIS_TYPE_TF].checkConfig_Regions_Param.at(paramIdx);
		for (int j = 0; j < pParam->useNum; j++)
		{
			if (!pParam->paramArr[j].bEnable)
			{
				continue;
			}
			m_LD_WTBConfig.minArea = pParam->paramArr[j].area;
			m_LD_WTBConfig.maxArea = pParam->paramArr[j].area_max;
			m_LD_WTBConfig.hj = pParam->paramArr[j].hj;
			m_LD_WTBConfig.buse = true;
		}
	}
	for (int i = 0; i < CONFIG_QX_NAME_count; i++)
	{
		if (i != CONFIG_QX_NAME_LD_HS)
		{
			continue;
		}
		int paramIdx = m_QxInParamListIdx[i];
		if (paramIdx < 0)
		{
			continue;
		}
		CheckConfig_Regions_Param *pParam = &m_pRegionAnalysisyParam->checkConfig_Regions_type[ANALYSIS_TYPE_TF].checkConfig_Regions_Param.at(paramIdx);
		for (int j = 0; j < pParam->useNum; j++)
		{
			if (!pParam->paramArr[j].bEnable)
			{
				continue;
			}
			m_LD_HSConfig.minArea = pParam->paramArr[j].area;
			m_LD_HSConfig.maxArea = pParam->paramArr[j].area_max;
			m_LD_HSConfig.hj = pParam->paramArr[j].hj;
			m_LD_HSConfig.buse = true;
		}
	}

	return 0;
}

void worker(const unsigned char *img, int w, int startRow, int endRow, unsigned char *rowFlags)
{
	for (int y = startRow; y < endRow; y++)
	{
		const unsigned char *p = img + (size_t)y * w;
		rowFlags[y] = 0;
		for (int x = 0; x < w; x++)
		{
			if (p[x] != 0)
			{
				rowFlags[y] = 1;
				break;
			}
		}
	}
}
int ImgCheckAnalysisy::GetALLBlob()
{

	m_AI_Other_task->waitComplate();

	std::string strBaseLog = "Blob";
	m_pdetlog->AddCheckstr(PrintLevel_0, strBaseLog, "---GetALLBlob  Start");
	long t1 = CheckUtil::getcurTime();
	int re = 0;
	re = GetBLob_YX();

	long t2 = CheckUtil::getcurTime();
	re = GetBlob_LackPol();
	long t3 = CheckUtil::getcurTime();

	re = GetBlob_QX();
	long t4 = CheckUtil::getcurTime();
	re = GetBlob_127cell();

	if (blobs.blobCount > 100)
	{
		blobs.blobCount = 100;
		/* code */
	}

	long te = CheckUtil::getcurTime();
	m_pdetlog->AddCheckstr(PrintLevel_0, strBaseLog,
						   "---GetALLBlob  End ;use time %ld ms  yx %ld ms  lack %ld ms  qx %ld ms  127 %ld ms",
						   te - t1, t2 - t1, t3 - t2, t4 - t3, te - t4);

	// getchar();
	return 0;
}

int ImgCheckAnalysisy::GetBLob_YX()
{
	if (m_pFuntion && m_pFuntion->function.f_YXDet.bOpen)
	{
	}
	else
	{
		return 1;
	}

	cv::Mat maskimg = m_pImageAllResult->YX_MaskImg;
	if (maskimg.empty())
	{
		return 1;
	}
	// 定义腐蚀操作的内核
	int kernelSize = 11; // 内核大小
	cv::Mat kernel = cv::getStructuringElement(cv::MORPH_RECT, cv::Size(kernelSize, kernelSize));
	// 执行腐蚀操作
	cv::Mat erodedImage;
	cv::erode(maskimg, erodedImage, kernel);

	// 屏蔽框屏蔽。
	if (!m_pImageAllResult->shieldImg.empty())
	{
		std::shared_ptr<AIModel_Base> pAI_Model = AI_Factory->AI_defect_YX_1;
		cv::Size sz;
		sz.width = pAI_Model->input_0.width;
		sz.height = pAI_Model->input_0.height;
		cv::Mat detmask_size;
		cv::resize(m_pImageAllResult->shieldImg, detmask_size, sz, 0, 0, cv::INTER_AREA);
		erodedImage.setTo(0, detmask_size);
	}

	cv::Mat showimg;
	if (DetImgInfo_shareP->bDebugsaveImg)
	{
		cv::cvtColor(erodedImage, showimg, cv::COLOR_GRAY2BGR);
	}
	// det To  src
	float fx_src = m_pImageAllResult->detImg.cols * 1.0f / maskimg.cols;
	float fy_src = m_pImageAllResult->detImg.rows * 1.0f / maskimg.rows;
	int config_qx_type = CONFIG_QX_NAME_AD_YX;
	std::string qx_name = CONFIG_QX_NAME_Names[config_qx_type];

	// 轮廓检测
	std::vector<std::vector<cv::Point>> contours;
	cv::findContours(erodedImage, contours, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE);
	int nresult = 0;

	for (size_t i = 0; i < contours.size(); ++i)
	{

		double area = cv::contourArea(contours.at(i));
		double judgeArea = area * fx_src * fy_src * m_fImgage_Scale_X * m_fImgage_Scale_Y;

		int curresult = 0;
		cv::Rect roi = cv::boundingRect(contours[i]);
		if (DetImgInfo_shareP->bDebugsaveImg)
		{
			cv::rectangle(showimg, roi, cv::Scalar(0, 0, 255), 2);
		}
		roi.x *= fx_src;
		roi.width *= fx_src;

		roi.y *= fy_src;
		roi.height *= fy_src;
		float len = std::sqrt(roi.width * roi.width + roi.height * roi.height);

		if (true)
		{
			QX_ERROR_INFO_ temerror;
			temerror.roi = roi;
			temerror.Idx = m_pDetResult->pQx_ErrorList->size();
			temerror.area = area;
			temerror.JudgArea = judgeArea;
			temerror.JudgArea_second = judgeArea;
			temerror.energy = area * fx_src * fy_src;
			temerror.flen = len;
			temerror.nconfig_qx_type = config_qx_type;
			temerror.qx_name = qx_name;
			temerror.maxValue = 0;
			temerror.grayDis = 0;
			temerror.density = 0;
			temerror.fUpIou = 0;

			{
				// 添加检测区域 0

				if (temerror.detRegionidxList.size() <= 0)
				{
					temerror.detRegionidxList.push_back(0);
				}
			}

			m_pDetResult->pQx_ErrorList->push_back(temerror);
		}
	}
	// 临时存图
	if (DetImgInfo_shareP->bDebugsaveImg)
	{
		cv::imwrite(m_strCurDetCamChannel + "_YX_det_mask_add_shield.png", showimg);
	}
	m_pdetlog->AddCheckstr(PrintLevel_1, "GetBLob_YX", " YX NUM %ld", contours.size());

	return 0;
}

int ImgCheckAnalysisy::GetBlob_LackPol()
{
	if (m_pFuntion && m_pFuntion->function.f_Dectect_LackPol.bOpen)
	{
	}
	else
	{
		return 1;
	}

	cv::Mat maskimg = m_pImageAllResult->LcakPol_MaskImg;
	if (maskimg.empty())
	{
		return 1;
	}

	cv::Mat erodedImage = maskimg;
	// 屏蔽框屏蔽。
	if (!m_pImageAllResult->shieldImg.empty())
	{
		std::shared_ptr<AIModel_Base> pAI_Model = AI_Factory->AI_defect_LackPol;
		cv::Size sz;
		sz.width = pAI_Model->input_0.width;
		sz.height = pAI_Model->input_0.height;
		cv::Mat detmask_size;
		cv::resize(m_pImageAllResult->shieldImg, detmask_size, sz, 0, 0, cv::INTER_AREA);
		erodedImage.setTo(0, detmask_size);
	}
	cv::Mat showimg;
	if (DetImgInfo_shareP->bDebugsaveImg)
	{
		cv::cvtColor(erodedImage, showimg, cv::COLOR_GRAY2BGR);
	}

	int config_qx_type = CONFIG_QX_NAME_LackPOL;
	std::string qx_name = CONFIG_QX_NAME_Names[config_qx_type];

	// 轮廓检测
	std::vector<std::vector<cv::Point>> contours;
	cv::findContours(erodedImage, contours, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE);
	int nresult = 0;

	// det To  src
	float fx_src = m_pImageAllResult->detImg.cols * 1.0f / maskimg.cols;
	float fy_src = m_pImageAllResult->detImg.rows * 1.0f / maskimg.rows;

	for (size_t i = 0; i < contours.size(); ++i)
	{

		double area = cv::contourArea(contours.at(i));
		double judgeArea = area * fx_src * fy_src * m_fImgage_Scale_X * m_fImgage_Scale_Y;

		int curresult = 0;
		cv::Rect roi = cv::boundingRect(contours[i]);

		if (DetImgInfo_shareP->bDebugsaveImg)
		{
			cv::rectangle(showimg, roi, cv::Scalar(0, 0, 255), 2);
		}
		roi.x *= fx_src;
		roi.width *= fx_src;
		roi.y *= fy_src;
		roi.height *= fy_src;

		float len = std::sqrt(roi.width * roi.width + roi.height * roi.height);

		if (true)
		{
			QX_ERROR_INFO_ temerror;
			temerror.roi = roi;
			temerror.Idx = m_pDetResult->pQx_ErrorList->size();
			temerror.area = area;
			temerror.JudgArea = judgeArea;
			temerror.JudgArea_second = judgeArea;
			temerror.energy = area * fx_src * fy_src;
			temerror.flen = len;
			temerror.nconfig_qx_type = config_qx_type;
			temerror.qx_name = qx_name;
			temerror.maxValue = 0;
			temerror.grayDis = 0;
			temerror.density = 0;
			temerror.fUpIou = 0;

			{
				// 添加检测区域 0

				if (temerror.detRegionidxList.size() <= 0)
				{
					temerror.detRegionidxList.push_back(0);
				}
			}

			m_pDetResult->pQx_ErrorList->push_back(temerror);
		}
	}
	// 临时存图
	if (DetImgInfo_shareP->bDebugsaveImg)
	{

		cv::imwrite(m_strCurDetCamChannel + "_LackPol_det_mask_add_shield.png", showimg);
	}
	m_pdetlog->AddCheckstr(PrintLevel_1, "GetBlob_LackPol", " LackPol NUM %ld", contours.size());

	return 0;
}

int ImgCheckAnalysisy::GetBlob_QX()
{

	std::string strBaseLog = "GetBlob_QX";
	if (!m_pFuntion->function.f_BaseDet.bOpen)
	{
		return 0;
	}

	std::shared_ptr<ImageAllResult::Image_AI_Det_Result> pDetAIResult = m_pImageAllResult->qx_DetAIResult;

	cv::Mat maskimg = pDetAIResult->AI_MaskImg;

	if (maskimg.empty())
	{
		return 1;
	}
	unsigned char *imgBlobHFlagData = pDetAIResult->blobDetParam->imgBlobHFlagData;
	if (imgBlobHFlagData == NULL)
	{
		return 1;
	}

	unsigned char *pGrayErrordata = (unsigned char *)maskimg.data;
	int width = maskimg.cols;
	int height = maskimg.rows;

	long t1 = CheckUtil::getcurTime();
	ERROR_DOTS_BLOBS blobs_all;
	memset(&blobs_all, 0x00, sizeof(ERROR_DOTS_BLOBS));

	ERROR_DOTS_BLOBS blobs_v1;
	memset(&blobs_v1, 0x00, sizeof(ERROR_DOTS_BLOBS));
	ERROR_DOTS_BLOBS blobs_big;
	memset(&blobs_big, 0x00, sizeof(ERROR_DOTS_BLOBS));
	ERROR_DOTS_BLOBS blobs_big_2;
	memset(&blobs_big_2, 0x00, sizeof(ERROR_DOTS_BLOBS));

	GetBlobs_oneLabe(&blobs_v1, pGrayErrordata, imgBlobHFlagData, width, height, 15);
	m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, strBaseLog, "blob 1 num  %d", blobs_v1.blobCount);

	if (blobs_v1.srcBlobCount >= _MAX_ERROR_DOT_BLOB)
	{

		GetBlobs_oneLabe(&blobs_big, pGrayErrordata, m_pImageAllResult->qx_DetAIResult->blobDetParam->imgBlobHFlagData, width, height, 200);
		m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, strBaseLog, "blob 2 num  %d", blobs_big.blobCount);

		if (blobs_big.srcBlobCount >= _MAX_ERROR_DOT_BLOB)
		{

			m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, strBaseLog, "blob 3 num  %d", blobs_big_2.blobCount);
			GetBlobs_oneLabe(&blobs_big_2, pGrayErrordata, m_pImageAllResult->qx_DetAIResult->blobDetParam->imgBlobHFlagData, width, height, 500);
		}
	}

	long t2 = CheckUtil::getcurTime();
	PushBlob(&blobs_all, &blobs_big_2);
	PushBlob(&blobs_all, &blobs_big);
	PushBlob(&blobs_all, &blobs_v1);

	PushBlob(&blobs, &blobs_all);

	m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, strBaseLog, "blob ALL num  %d", blobs_all.blobCount);

	if (DetImgInfo_shareP->bDebugsaveImg)
	{
		int font_face = cv::FONT_HERSHEY_SIMPLEX;
		double font_scale = 0.5;
		int thickness = 1;

		m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, strBaseLog, "Save Tem Img");
		cv::Mat tm;
		cv::cvtColor(maskimg, tm, cv::COLOR_GRAY2RGB); // 彩色 可选项
		for (int i = 0; i < blobs_all.blobCount; i++)
		{
			cv::Rect roi;
			roi.x = blobs_all.blobTab[i].minx;
			roi.y = blobs_all.blobTab[i].miny;
			roi.width = blobs_all.blobTab[i].maxx - blobs_all.blobTab[i].minx + 1;
			roi.height = blobs_all.blobTab[i].maxy - blobs_all.blobTab[i].miny + 1;

			if (blobs_all.blobTab[i].ErrType == 0)
			{
				cv::rectangle(tm, roi, cv::Scalar(0, 0, 255));
			}
			else
			{
				cv::rectangle(tm, roi, cv::Scalar(0, 255, 255));
			}

			char buffer[128];
			sprintf(buffer, " type:%d m %0.1f", blobs.blobTab[i].ErrType, blobs.blobTab[i].density);
			std::string text = buffer;
			cv::Point origin = cv::Point(roi.x, roi.y);
			cv::putText(tm, text, origin, font_face, font_scale, cv::Scalar(0, 255, 0), thickness, 1, 0);

			// printf("type: %d   %d  %d   %d %d %d %d\n", blobs.blobTab[i].ErrType, blobs.blobTab[i].area, blobs.blobTab[i].energy, roi.x, roi.y, roi.width, roi.height);
		}
		cv::imwrite(m_strCurDetCamChannel + "_qx_image_resize_blob.png", tm);
	}

	long te = CheckUtil::getcurTime();
	m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, strBaseLog, "image Blob Analysis  End use time %ld blob %ld ms", te - t1, t2 - t1);

	return 0;
}

int ImgCheckAnalysisy::GetBlob_127cell()
{

	std::string strBaseLog = "GetBlob_127cell";
	if (m_pFuntion && m_pFuntion->function.f_Det127Cell.bOpen)
	{
	}
	else
	{ // 未开启检测
		return 0;
	}

	std::shared_ptr<ImageAllResult::Image_AI_Det_Result> pDetAIResult = m_pImageAllResult->cell127_DetAIResult;

	cv::Mat maskimg = pDetAIResult->AI_MaskImg;
	if (maskimg.empty())
	{
		return 1;
	}
	unsigned char *imgBlobHFlagData = pDetAIResult->blobDetParam->imgBlobHFlagData;
	if (imgBlobHFlagData == NULL)
	{
		return 1;
	}

	unsigned char *pGrayErrordata = (unsigned char *)maskimg.data;
	int width = maskimg.cols;
	int height = maskimg.rows;

	long t1 = CheckUtil::getcurTime();
	ERROR_DOTS_BLOBS blobs_all;
	memset(&blobs_all, 0x00, sizeof(ERROR_DOTS_BLOBS));

	ERROR_DOTS_BLOBS blobs_v1;
	memset(&blobs_v1, 0x00, sizeof(ERROR_DOTS_BLOBS));
	ERROR_DOTS_BLOBS blobs_big;
	memset(&blobs_big, 0x00, sizeof(ERROR_DOTS_BLOBS));
	ERROR_DOTS_BLOBS blobs_big_2;
	memset(&blobs_big_2, 0x00, sizeof(ERROR_DOTS_BLOBS));

	GetBlobs_oneLabe(&blobs_v1, pGrayErrordata, imgBlobHFlagData, width, height, 15);
	m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, strBaseLog, "blob 1 num  %d", blobs_v1.blobCount);

	if (blobs_v1.srcBlobCount >= _MAX_ERROR_DOT_BLOB)
	{

		GetBlobs_oneLabe(&blobs_big, pGrayErrordata, m_pImageAllResult->qx_DetAIResult->blobDetParam->imgBlobHFlagData, width, height, 200);
		m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, strBaseLog, "blob 2 num  %d", blobs_big.blobCount);

		if (blobs_big.srcBlobCount >= _MAX_ERROR_DOT_BLOB)
		{

			m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, strBaseLog, "blob 3 num  %d", blobs_big_2.blobCount);
			GetBlobs_oneLabe(&blobs_big_2, pGrayErrordata, m_pImageAllResult->qx_DetAIResult->blobDetParam->imgBlobHFlagData, width, height, 500);
		}
	}

	long t2 = CheckUtil::getcurTime();
	PushBlob(&blobs_all, &blobs_big_2);
	PushBlob(&blobs_all, &blobs_big);
	PushBlob(&blobs_all, &blobs_v1);
	for (int i = 0; i < blobs_all.blobCount; i++)
	{
		blobs_all.blobTab[i].ErrType = CONFIG_QX_NAME_white_Cell;
	}

	PushBlob(&blobs, &blobs_all);
	m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, strBaseLog, "blob ALL num  %d", blobs_all.blobCount);
	if (DetImgInfo_shareP->bDebugsaveImg)
	{
		int font_face = cv::FONT_HERSHEY_SIMPLEX;
		double font_scale = 0.5;
		int thickness = 1;

		m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, strBaseLog, "Save Tem Img");
		cv::Mat tm;
		cv::cvtColor(maskimg, tm, cv::COLOR_GRAY2RGB); // 彩色 可选项
		for (int i = 0; i < blobs_all.blobCount; i++)
		{
			cv::Rect roi;
			roi.x = blobs_all.blobTab[i].minx;
			roi.y = blobs_all.blobTab[i].miny;
			roi.width = blobs_all.blobTab[i].maxx - blobs_all.blobTab[i].minx + 1;
			roi.height = blobs_all.blobTab[i].maxy - blobs_all.blobTab[i].miny + 1;

			if (blobs_all.blobTab[i].ErrType == 0)
			{
				cv::rectangle(tm, roi, cv::Scalar(0, 0, 255));
			}
			else
			{
				cv::rectangle(tm, roi, cv::Scalar(0, 255, 255));
			}

			char buffer[128];
			sprintf(buffer, " type:%d m %0.1f", blobs.blobTab[i].ErrType, blobs.blobTab[i].density);
			std::string text = buffer;
			cv::Point origin = cv::Point(roi.x, roi.y);
			cv::putText(tm, text, origin, font_face, font_scale, cv::Scalar(0, 255, 0), thickness, 1, 0);

			// printf("type: %d   %d  %d   %d %d %d %d\n", blobs.blobTab[i].ErrType, blobs.blobTab[i].area, blobs.blobTab[i].energy, roi.x, roi.y, roi.width, roi.height);
		}
		cv::imwrite(m_strCurDetCamChannel + "_127cell_image_resize_blob.png", tm);
	}

	long te = CheckUtil::getcurTime();
	m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, strBaseLog, "image Blob Analysis  End use time %ld blob %ld ms", te - t1, t2 - t1);

	return 0;
}

int ImgCheckAnalysisy::AIMaskDet()
{
	m_pdetlog->AddCheckstr(PrintLevel_0, "AIMaskDet", "=======start");
	std::shared_ptr<ImageAllResult::AI_MaskImg_BlobParam> blobDetParam;
	// AI QX 检测
	while (true)
	{

		std::this_thread::sleep_for(std::chrono::milliseconds(1));
		if (!m_pImageAllResult->qx_DetAIResult)
		{
			// 等待初始化
			continue;
		}
		blobDetParam = m_pImageAllResult->qx_DetAIResult->blobDetParam;

		std::shared_ptr<ImageAllResult::AI_Det_MaskImg> AImaskResult;
		{
			std::lock_guard<std::mutex> lock(blobDetParam->mtx_AIMaskImgBLobQueue);
			if (blobDetParam->AIMaskImgBLobQueue.size() > 0)
			{
				AImaskResult = std::move(blobDetParam->AIMaskImgBLobQueue.front());
				blobDetParam->AIMaskImgBLobQueue.pop();
				// printf("size  ============== %ld\n", m_AIMaskImgBLobQueue.size());
			}
		}

		// 有AI mask 的结果
		if (AImaskResult)
		{
			// static int ss = 0;
			cv::Mat outimg = AImaskResult->AI_mask;
			// cv::imwrite(std::to_string(ss++) + ".png", outimg);

			unsigned char *pGrayErrordata = (unsigned char *)outimg.data;
			int width = outimg.cols;
			int height = outimg.rows;
			int start_Y = AImaskResult->roi.y;
			if (cv::countNonZero(outimg != 0) != 0)
			{
				// #pragma omp parallel for
				for (int y = 0; y < height; y++)
				{
					if ((y + start_Y) < blobDetParam->ndatalen && blobDetParam->imgBlobHFlagData[y + start_Y] == 0)
					{
						unsigned char *p = pGrayErrordata + y * width;
						for (int x = 0; x < width; x++)
						{
							if (p[x] != 0)
							{
								// printf("===========qx_DetAIResult======m_ImgBlobHFlagData %d===%d = %d=======0 \n", blobDetParam->ndatalen, y + start_Y, outimg.rows);
								blobDetParam->imgBlobHFlagData[y + start_Y] = 1;
								break;
							}
						}
					}
				}
			}
		}
		else
		{
			/* code */

			if (m_AItask->isComplate())
			{
				break;
			}
		}
	}
	m_pdetlog->AddCheckstr(PrintLevel_1, "AIMaskDet", "=======qx_DetAIResult  end");
	// 127 cell 检测
	while (true)
	{

		std::this_thread::sleep_for(std::chrono::milliseconds(1));
		if (!m_pImageAllResult->cell127_DetAIResult)
		{
			// 等待初始化
			continue;
		}
		blobDetParam = m_pImageAllResult->cell127_DetAIResult->blobDetParam;

		std::shared_ptr<ImageAllResult::AI_Det_MaskImg> AImaskResult;
		{
			std::lock_guard<std::mutex> lock(blobDetParam->mtx_AIMaskImgBLobQueue);
			if (blobDetParam->AIMaskImgBLobQueue.size() > 0)
			{
				AImaskResult = std::move(blobDetParam->AIMaskImgBLobQueue.front());
				blobDetParam->AIMaskImgBLobQueue.pop();
				// printf("size  ============== %ld\n", m_AIMaskImgBLobQueue.size());
			}
		}

		// 有AI mask 的结果
		if (AImaskResult)
		{
			// static int ss = 0;
			cv::Mat outimg = AImaskResult->AI_mask;
			// cv::imwrite(std::to_string(ss++) + ".png", outimg);

			unsigned char *pGrayErrordata = (unsigned char *)outimg.data;
			int width = outimg.cols;
			int height = outimg.rows;
			int start_Y = AImaskResult->roi.y;
			if (cv::countNonZero(outimg != 0) != 0)
			{
				// #pragma omp parallel for
				for (int y = 0; y < height; y++)
				{
					if ((y + start_Y) < blobDetParam->ndatalen && blobDetParam->imgBlobHFlagData[y + start_Y] == 0)
					{
						unsigned char *p = pGrayErrordata + y * width;
						for (int x = 0; x < width; x++)
						{
							if (p[x] != 0)
							{
								// printf("===============cell127_DetAIResult ====m_ImgBlobHFlagData %d===%d = %d=======0 \n", blobDetParam->ndatalen, y + start_Y, outimg.rows);
								blobDetParam->imgBlobHFlagData[y + start_Y] = 1;
								break;
							}
						}
					}
				}
			}
		}
		else
		{
			/* code */

			if (m_AItask->isComplate())
			{
				break;
			}
		}
	}
	m_pdetlog->AddCheckstr(PrintLevel_1, "AIMaskDet", "=======cell127_DetAIResult  end");
	m_AItask->waitComplate();

	int rec = m_AItask->nresult;
	m_pdetlog->AddCheckstr(PrintLevel_1, "AIMaskDet", "=======m_AItask  waitComplate  m_AItask->nresult %d", rec);
	if (rec != CHECK_OK)
	{
		return rec;
	}

	return 0;
}

int ImgCheckAnalysisy::Contours()
{
	// std::string strBaseLog = "Contours";
	// // m_pdetlog->AddCheckstr(PrintLevel_0, DET_LOG_LEVEL_3, strBaseLog, "Contours  Start");
	// cv::Mat detimg;
	// {
	// 	// 膨胀
	// 	cv::Mat se = getStructuringElement(0, Size(5, 5)); // 构造矩形结构元素
	// 	cv::dilate(m_pdetlog->temImgList[TEM_IMG_IDX_AImask], detimg, se);
	// }

	// std::vector<std::vector<cv::Point>> contours;
	// std::vector<cv::Vec4i> hierarchy;
	// cv::findContours(detimg, contours, hierarchy, cv::RETR_EXTERNAL, cv::CHAIN_APPROX_NONE); // 只找最外层轮廓

	// // cv::cvtColor(m_pdetlog->temImgList[TEM_IMG_IDX_SrcCrop], m_pdetlog->temImgList[TEM_IMG_IDX_DrawSrc], cv::COLOR_GRAY2BGR);

	// for (int i = 0; i < contours.size(); ++i)
	// {																										// 绘制所有轮廓
	// 	cv::drawContours(m_pdetlog->temImgList[TEM_IMG_IDX_DrawSrc], contours, i, cv::Scalar(255, 0, 255)); // thickness为-1时为填充整个轮廓
	// }

	// float fx = m_pdetlog->temImgList[TEM_IMG_IDX_Result].cols * 1.0f / m_pdetlog->temImgList[TEM_IMG_IDX_SrcCrop].cols;
	// float fy = m_pdetlog->temImgList[TEM_IMG_IDX_Result].rows * 1.0f / m_pdetlog->temImgList[TEM_IMG_IDX_SrcCrop].rows;
	// for (int i = 0; i < contours.size(); ++i)
	// {
	// 	for (int j = 0; j < contours.at(i).size(); ++j)
	// 	{
	// 		contours.at(i).at(j).x *= fx;
	// 		contours.at(i).at(j).y *= fy;
	// 	}
	// }
	// // cv::cvtColor(m_pdetlog->temImgList[TEM_IMG_IDX_Result], m_pdetlog->temImgList[TEM_IMG_IDX_Result], cv::COLOR_GRAY2BGR);

	// for (int i = 0; i < contours.size(); ++i)
	// {																									   // 绘制所有轮廓
	// 	cv::drawContours(m_pdetlog->temImgList[TEM_IMG_IDX_Result], contours, i, cv::Scalar(255, 0, 255)); // thickness为-1时为填充整个轮廓
	// }
	// cv::imwrite("TEM_IMG_IDX_Result.png", m_pdetlog->temImgList[TEM_IMG_IDX_Result]);
	// cv::imwrite("deeeee.png", m_pdetlog->temImgList[TEM_IMG_IDX_Drawmask]);
	// getchar();
	// m_pdetlog->AddCheckstr(PrintLevel_0, DET_LOG_LEVEL_3, strBaseLog, "Contours  End");
	return 0;
}

int ImgCheckAnalysisy::CheckImgInit()
{
	// 1、初始化

	m_pDetResult->pQx_ErrorList = std::make_shared<std::vector<QX_ERROR_INFO_>>();
	m_pdetlog->Init();
	m_pdetlog->addLogLevel = DET_LOG_LEVEL_3;
	memset(&blobs, 0, sizeof(ERROR_DOTS_BLOBS));
	m_nCheckResultErrorCode = 0;

	m_Draw_qxImageResult.erase(m_Draw_qxImageResult.begin(), m_Draw_qxImageResult.end());

	m_DetRoiList.Init();

	return 0;
}

int ImgCheckAnalysisy::ConfigCheck(cv::Mat img)
{

	m_pdetlog->AddCheckstr(PrintLevel_0, "start", "Config Check");
	int re = CHECK_OK;
	if (img.empty())
	{
		m_nErrorCode = CHECK_ERROR_CheckImg_Empty;
		m_pdetlog->AddCheckstr(PrintLevel_1, "Error", "check Img empty");
		return m_nErrorCode;
	}

	// if (m_pCommonAnalysisyConfig->regionConfigArr.size() <= 0)
	// {
	// 	m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, "Error", "regionConfig Num  = 0");
	// 	m_nErrorCode = CHECK_ERROR_Config_Value;
	// 	return m_nErrorCode;
	// }

	m_pdetlog->AddCheckstr(PrintLevel_0, "Succ", "Config Check Succ");
	return re;
}

int ImgCheckAnalysisy::AI_Detect_Thread()
{

	std::string strBaseLog = "AI_Detect";
	m_pdetlog->AddCheckstr(PrintLevel_0, DET_LOG_LEVEL_3, strBaseLog, "****** AI_Detect  Start");
	long t1, t3;
	t1 = CheckUtil::getcurTime();

	cv::Mat AI_detImage = m_pImageAllResult->AI_detImg;
	std::shared_ptr<AIModel_Base> pAI_Model = AI_Factory->AI_defect_NF;

	int re = CreatAIDetSmallRoi(AI_detImage, pAI_Model, SmallRoiList);
	if (re != 0)
	{
		m_pdetlog->AddCheckstr(PrintLevel_0, DET_LOG_LEVEL_3, strBaseLog, "error small roi。AI_Detect End");
		return 1;
	}

	// 临时存图
	if (DetImgInfo_shareP->bDebugsaveImg)
	{

		cv::Mat imshow;
		if (AI_detImage.channels() == 1)
		{
			cv::cvtColor(AI_detImage, imshow, cv::COLOR_GRAY2RGB); // 彩色 可选项
		}
		else
		{
			imshow = AI_detImage.clone();
		}
		for (int i = 0; i < SmallRoiList.size(); i++)
		{
			cv::rectangle(imshow, SmallRoiList.at(i), cv::Scalar(0, 0, 255), 3);
		}
		cv::imwrite(m_strCurDetCamChannel + "_AI_Det_ROI.jpg", imshow);
	}

	// 缺陷检测
	re = AI_Detect_QX();

	// 127cell
	re = AI_Detect_127Cell();

	t3 = CheckUtil::getcurTime();

	m_pdetlog->AddCheckstr(PrintLevel_0, DET_LOG_LEVEL_3, strBaseLog, "****** AI_Detect  End; AI Run Time: sum  %ld", t3 - t1);

	// getchar();
	return 0;
}

int ImgCheckAnalysisy::AI_Other_Det_Thread()
{
	std::string strBaseLog = "AI_Other_Det";
	m_pdetlog->AddCheckstr(PrintLevel_0, DET_LOG_LEVEL_3, strBaseLog, ">>>>> AI_Detect  Start");
	long t1, t3;
	t1 = CheckUtil::getcurTime();

	// 检测分析 1、先进行异显检测如果，结果是异显，则不进行后续检测判断
	int rec = AI_Det_YX(m_pImageAllResult->detImg);

	// 缺失 POL检测
	rec = Detect_LackPol(m_pImageAllResult->detImg);

	t3 = CheckUtil::getcurTime();

	m_pdetlog->AddCheckstr(PrintLevel_0, DET_LOG_LEVEL_3, strBaseLog, ">>>>> AI_Detect  End; AI Run Time: sum  %ld", t3 - t1);

	// getchar();
	return 0;
}

int ImgCheckAnalysisy::AI_Detect_QX()
{
	std::string strBaseLog = "AI_Detect_QX";
	m_pImageAllResult->qx_DetAIResult = std::make_shared<ImageAllResult::Image_AI_Det_Result>();
	// 未开启检测
	if (!m_pFuntion->function.f_BaseDet.bOpen)
	{
		m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, strBaseLog, " base detect  close");
		return 0;
	}
	long ts, t2, te;
	ts = CheckUtil::getcurTime();

	m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, strBaseLog, "============= Start");
	std::shared_ptr<ImageAllResult::Image_AI_Det_Result> pDetAIResult = m_pImageAllResult->qx_DetAIResult;
	int re = 0;
	cv::Mat AI_detImage = m_pImageAllResult->AI_detImg;

	// 确定检测模型
	std::shared_ptr<AIModel_Base> pAI_Model;
	if (m_pFuntion->function.f_BaseDet.strAIMode == "UP")
	{
		pAI_Model = AI_Factory->AI_defect_UP;
		m_pdetlog->AddCheckstr(PrintLevel_2, DET_LOG_LEVEL_3, strBaseLog, "=======model use UP");
	}
	else
	{
		if (m_pFuntion->function.f_BaseDet.strAIMode == "WandB")
		{
			m_pdetlog->AddCheckstr(PrintLevel_2, DET_LOG_LEVEL_3, strBaseLog, "=======model use WandB");
			pAI_Model = AI_Factory->AI_defect_Type2;
		}
		else if (m_pFuntion->function.f_BaseDet.strAIMode == "Chess")
		{
			m_pdetlog->AddCheckstr(PrintLevel_2, DET_LOG_LEVEL_3, strBaseLog, "=======model use Chess");
			pAI_Model = AI_Factory->AI_defect_Chess;
		}
		else if (m_pFuntion->function.f_BaseDet.strAIMode == "RGB-HGRAY")
		{
			m_pdetlog->AddCheckstr(PrintLevel_2, DET_LOG_LEVEL_3, strBaseLog, "=======model use RE_RGBHGRAY");
			pAI_Model = AI_Factory->AI_defect_RE_RGBHGRAY;
		}
		else
		{
			m_pdetlog->AddCheckstr(PrintLevel_2, DET_LOG_LEVEL_3, strBaseLog, "=======model use base");
			pAI_Model = AI_Factory->AI_defect_NF;
		}
	}

	int AIInputImg_width = pAI_Model->input_0.width;
	int AIInputImg_height = pAI_Model->input_0.height;

	int AIOutputImg_width = pAI_Model->output_0.width;
	int AIOutputImg_height = pAI_Model->output_0.height;

	pDetAIResult->InitBLobHData(AI_detImage.rows);

	// 是否需要 resize到输入图大小进行后续处理。
	bool bResizeToSrc = false;
	if (AIOutputImg_width != AIInputImg_width || AIOutputImg_height != AIInputImg_height)
	{
		bResizeToSrc = true;
	}

	// 如果尺寸不合适，要重新计算 smll roi.一般情况来说，small roi 都是相同的对不同的AI 模型。在模型设计时要做到统一，降低调用复杂度。
	if (SmallRoiList.size() > 0)
	{
		int roi_width = SmallRoiList.at(0).width;
		int roi_height = SmallRoiList.at(0).height;
		if (roi_width != AIInputImg_width || roi_height != AIInputImg_height)
		{
			int re = CreatAIDetSmallRoi(AI_detImage, pAI_Model, SmallRoiList);
			if (re != 0)
			{
				m_pdetlog->AddCheckstr(PrintLevel_2, DET_LOG_LEVEL_3, strBaseLog, "error small roi");
				return 1;
			}
		}
	}

	const int totalTasks = SmallRoiList.size();
	if (totalTasks <= 0)
	{
		m_pdetlog->AddCheckstr(PrintLevel_2, DET_LOG_LEVEL_3, strBaseLog, "error small roi = 0");
		return 0;
	}

	int submitted = 0;
	int completed = 0;

	cv::Size src_sz;
	src_sz.width = AIInputImg_width;
	src_sz.height = AIInputImg_height;

	pDetAIResult->AI_MaskImg = cv::Mat::zeros(AI_detImage.size(), CV_8UC1);
	cv::Mat shieldImg = m_pImageAllResult->AI_shieldImg;
	cv::Mat AIresultMask = pDetAIResult->AI_MaskImg;

	t2 = CheckUtil::getcurTime();

	while (completed < totalTasks)
	{
		// 如果任务还没提交完，且当前处理任务数 < 2，提交新任务
		if (submitted < totalTasks && runner->GetProcessingCount() < 10)
		{

			std::shared_ptr<AIMulThreadRunBase::AITask> task = std::make_shared<AIMulThreadRunBase::AITask>();
			task->id = completed;
			task->roi = SmallRoiList.at(submitted);
			task->input = AI_detImage(task->roi).clone();
			task->output = std::make_shared<cv::Mat>();
			task->engine = pAI_Model;
			if (submitted >= det_SmallImgNum)
			{
				task->userflag = 9;
			}

			runner->SubmitTask(task);
			submitted++;
		}

		// 尝试取结果
		std::shared_ptr<AIMulThreadRunBase::AITask> result;
		if (runner->PopResult(result))
		{
			cv::Mat &outimg = *(result->output);
			if (!outimg.empty())
			{
				cv::Mat AIresult;
				if (bResizeToSrc)
				{
					// 1、 resize 到原始大小。
					cv::resize(outimg, AIresult, src_sz, 0, 0, 0);
				}
				else
				{
					AIresult = outimg;
				}

				cv::Rect srcsize_roi = result->roi;

				// 2、 屏蔽 缺陷
				AIresult.setTo(0, shieldImg(result->roi));

				// 如果是字符区域，则  全部替换
				if (result->userflag == 9)
				{
					AIresult.copyTo(AIresultMask(result->roi));
				}
				else
				{
					AIresult.copyTo(AIresultMask(result->roi), AIresult);
				}

				{
					std::shared_ptr<ImageAllResult::AI_Det_MaskImg> temAIresult = std::make_shared<ImageAllResult::AI_Det_MaskImg>();
					temAIresult->roi = result->roi;
					temAIresult->AI_inImg = result->input;
					temAIresult->AI_mask = outimg;
					pDetAIResult->AI_Qx_MaskList.push_back(temAIresult);
				}

				{
					std::shared_ptr<ImageAllResult::AI_Det_MaskImg> temAIresult = std::make_shared<ImageAllResult::AI_Det_MaskImg>();
					temAIresult->roi = result->roi;
					temAIresult->AI_mask = AIresult;
					{
						std::lock_guard<std::mutex> lock(pDetAIResult->blobDetParam->mtx_AIMaskImgBLobQueue);
						pDetAIResult->blobDetParam->AIMaskImgBLobQueue.push(temAIresult);
					}
				}
			}
			completed++;
		}
		else
		{
			std::this_thread::sleep_for(std::chrono::milliseconds(1));
		}
	}
	te = CheckUtil::getcurTime();
	float mean_AI = (te - t2) / SmallRoiList.size();
	m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, strBaseLog, "============= End; AI Run Time: sum  %ld  pre %ld Run %ld mean One Small Img %f", te - ts, t2 - ts, te - t2, mean_AI);

	// 临时存图
	if (DetImgInfo_shareP->bDebugsaveImg)
	{
		cv::imwrite(m_strCurDetCamChannel + "_AI_QX_mask.png", AIresultMask);
	}

	return 0;
}

int ImgCheckAnalysisy::AI_Detect_127Cell()
{
	std::string strBaseLog = "AI_Detect_127Cell";
	m_pImageAllResult->cell127_DetAIResult = std::make_shared<ImageAllResult::Image_AI_Det_Result>();

	if (m_pFuntion && m_pFuntion->function.f_Det127Cell.bOpen)
	{
	}
	else
	{ // 未开启检测
		m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, strBaseLog, " f_Det127Cell  close");
		return 0;
	}
	long ts, t2, te;
	ts = CheckUtil::getcurTime();

	m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, strBaseLog, "=============  Start");
	std::shared_ptr<ImageAllResult::Image_AI_Det_Result> pDetAIResult = m_pImageAllResult->cell127_DetAIResult;
	cv::Mat AI_detImage = m_pImageAllResult->AI_detImg;

	std::shared_ptr<AIModel_Base> pAI_Model = AI_Factory->AI_defect_127Cell;

	int AIInputImg_width = pAI_Model->input_0.width;
	int AIInputImg_height = pAI_Model->input_0.height;

	int AIOutputImg_width = pAI_Model->output_0.width;
	int AIOutputImg_height = pAI_Model->output_0.height;
	pDetAIResult->InitBLobHData(AI_detImage.rows);
	// 是否需要 resize到输入图大小进行后续处理。
	bool bResizeToSrc = false;
	if (AIOutputImg_width != AIInputImg_width || AIOutputImg_height != AIInputImg_height)
	{
		bResizeToSrc = true;
	}

	// 如果尺寸不合适，要重新计算 smll roi.一般情况来说，small roi 都是相同的对不同的AI 模型。在模型设计时要做到统一，降低调用复杂度。
	if (SmallRoiList.size() > 0)
	{
		int roi_width = SmallRoiList.at(0).width;
		int roi_height = SmallRoiList.at(0).height;
		if (roi_width != AIInputImg_width || roi_height != AIInputImg_height)
		{
			int re = CreatAIDetSmallRoi(AI_detImage, pAI_Model, SmallRoiList);
			if (re != 0)
			{
				m_pdetlog->AddCheckstr(PrintLevel_2, DET_LOG_LEVEL_3, strBaseLog, "error small roi");
				return 1;
			}
		}
	}
	const int totalTasks = SmallRoiList.size();
	if (totalTasks <= 0)
	{
		m_pdetlog->AddCheckstr(PrintLevel_2, DET_LOG_LEVEL_3, strBaseLog, "error small roi = 0");
		return 0;
	}

	int submitted = 0;
	int completed = 0;

	cv::Size src_sz;
	src_sz.width = AIInputImg_width;
	src_sz.height = AIInputImg_height;

	pDetAIResult->AI_MaskImg = cv::Mat::zeros(AI_detImage.size(), CV_8UC1);
	cv::Mat shieldImg = m_pImageAllResult->AI_shieldImg;
	cv::Mat AIresultMask = pDetAIResult->AI_MaskImg;
	t2 = CheckUtil::getcurTime();
	while (completed < totalTasks)
	{
		// 如果任务还没提交完，且当前处理任务数 < 2，提交新任务
		if (submitted < totalTasks && runner->GetProcessingCount() < 10)
		{

			std::shared_ptr<AIMulThreadRunBase::AITask> task = std::make_shared<AIMulThreadRunBase::AITask>();
			task->id = completed;
			task->roi = SmallRoiList.at(submitted);
			task->input = AI_detImage(task->roi).clone();
			task->output = std::make_shared<cv::Mat>();
			task->engine = pAI_Model;
			if (submitted >= det_SmallImgNum)
			{
				task->userflag = 9;
			}

			runner->SubmitTask(task);
			submitted++;
		}

		// 尝试取结果
		std::shared_ptr<AIMulThreadRunBase::AITask> result;
		if (runner->PopResult(result))
		{
			cv::Mat &outimg = *(result->output);
			if (!outimg.empty())
			{
				cv::Mat AIresult;
				if (bResizeToSrc)
				{
					// 1、 resize 到原始大小。
					cv::resize(outimg, AIresult, src_sz, 0, 0, 0);
				}
				else
				{
					AIresult = outimg;
				}

				cv::Rect srcsize_roi = result->roi;

				// 2、 屏蔽 缺陷
				AIresult.setTo(0, shieldImg(result->roi));

				// 如果是字符区域，则  全部替换
				if (result->userflag == 9)
				{
					AIresult.copyTo(AIresultMask(result->roi));
				}
				else
				{
					AIresult.copyTo(AIresultMask(result->roi), AIresult);
				}

				{
					std::shared_ptr<ImageAllResult::AI_Det_MaskImg> temAIresult = std::make_shared<ImageAllResult::AI_Det_MaskImg>();
					temAIresult->roi = result->roi;
					temAIresult->AI_inImg = result->input;
					temAIresult->AI_mask = outimg;
					pDetAIResult->AI_Qx_MaskList.push_back(temAIresult);
				}

				{
					std::shared_ptr<ImageAllResult::AI_Det_MaskImg> temAIresult = std::make_shared<ImageAllResult::AI_Det_MaskImg>();
					temAIresult->roi = result->roi;
					temAIresult->AI_mask = AIresult;
					{
						std::lock_guard<std::mutex> lock(pDetAIResult->blobDetParam->mtx_AIMaskImgBLobQueue);
						pDetAIResult->blobDetParam->AIMaskImgBLobQueue.push(temAIresult);
					}
				}
			}
			completed++;
		}
		else
		{
			std::this_thread::sleep_for(std::chrono::milliseconds(1));
		}
	}
	// 临时存图
	if (DetImgInfo_shareP->bDebugsaveImg)
	{
		cv::imwrite(m_strCurDetCamChannel + "_AI_127cell_mask.png", AIresultMask);
	}
	te = CheckUtil::getcurTime();
	float mean_AI = (te - t2) / SmallRoiList.size();
	m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, strBaseLog, "============= End; AI Run Time: sum  %ld  pre %ld Run %ld mean One Small Img %f", te - ts, t2 - ts, te - t2, mean_AI);

	return 0;
}

int ImgCheckAnalysisy::AI_QX_Class_Thread()
{

	m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, "QX_Class", " Start");

	float fs_x = m_fImgage_Scale_X;
	float fs_y = m_fImgage_Scale_Y;

	for (int i = 0; i < blobs.blobCount; i++)
	{
		if (blobs.blobTab[i].ErrType == CONFIG_QX_NAME_white_Cell || blobs.blobTab[i].ErrType == CONFIG_QX_NAME_black_Cell)
		{
		}
		else
		{
			cv::Rect roi;
			roi.x = blobs.blobTab[i].minx;
			roi.y = blobs.blobTab[i].miny;
			roi.width = blobs.blobTab[i].maxx - blobs.blobTab[i].minx + 1;
			roi.height = blobs.blobTab[i].maxy - blobs.blobTab[i].miny + 1;
			float JudgArea = blobs.blobTab[i].area * fs_x * fs_y;

			float fmaxScore = 0;
			int config_qx_type = 0;

			config_qx_type = AI_Classify_New(m_pImageAllResult->AI_detImg, roi, JudgArea, &fmaxScore);
			// config_qx_type = AI_Classify(sizeimg, roi, JudgArea, &fmaxScore);
			// 方格线判断
			if (config_qx_type == CONFIG_QX_NAME_Y_line || config_qx_type == CONFIG_QX_NAME_X_line)
			{
				bool bchange = false;
				float fwh = roi.width * 1.0f / roi.height;
				if (roi.height > roi.width)
				{
					fwh = roi.height * 1.0f / roi.width;
				}
				else
				{
					fwh = roi.width * 1.0f / roi.height;
				}
				if (fwh < 7)
				{
					bchange = true;
				}
				if (bchange)
				{
					config_qx_type = CONFIG_QX_NAME_Fangge;
				}

				m_pdetlog->AddCheckstr(PrintLevel_3, " Y line to fangge line ", "change =  %d  width %f  < 7", bchange, fwh);
			}
			blobs.blobTab[i].ErrType = config_qx_type;
			// m_pdetlog->AddCheckstr(PrintLevel_3, " AI_QX_Class_Thread ", "qx %d ErrType %d ", i, config_qx_type);
		}
	}

	return 0;
}

int ImgCheckAnalysisy::ThreadTask(int nId)
{

	while (!m_bExit)
	{
		std::this_thread::sleep_for(std::chrono::milliseconds(20));
		// 等待是否有任务
		std::shared_ptr<TaskInfo> task = m_task.GetTask();

		// 把任务发送给对应的任务处理函数进行处理
		switch (task->taskname)
		{
		case Task_AI:
			TaskFun_AIDet(task);
			break;
		case Task_AI_Other:
			TaskFun_AI_Other(task);
			break;
		case Task_Class:
			TaskFun_QxClass(task);
			break;
		default:
			break;
		}
	}
	return 0;
}

int ImgCheckAnalysisy::ResizeImg()
{

	cv::Size sz;
	sz.width = RESIZE_IMAGE_WIDTH;

	float fw = RESIZE_IMAGE_WIDTH * 1.0f / m_pImageAllResult->detImg.cols;
	sz.height = int(m_pImageAllResult->detImg.rows * fw);

	cv::resize(m_pImageAllResult->detImg, m_pImageAllResult->resultImg, sz);

	// 需要绘制屏蔽区
	if ((m_pBasicConfig && m_pBasicConfig->bDrawShieldRoi) ||
		(m_pFuntion && m_pFuntion->function.f_ShieldRegion.bOpen && m_pFuntion->function.f_ShieldRegion.bDraw))
	{
		m_pdetlog->AddCheckstr(PrintLevel_1, "ResizeImg", "DrawShieldR param is open");
		cv::Mat shieldImg = m_pImageAllResult->shieldImg;
		cv::Mat sizeshieldimg;
		if (!shieldImg.empty())
		{
			cv::resize(shieldImg, sizeshieldimg, sz);
			sizeshieldimg *= 0.2;
			m_pImageAllResult->resultImg += sizeshieldimg;
		}
	}
	if (m_pImageAllResult->resultImg.channels() == 1)
	{
		cv::cvtColor(m_pImageAllResult->resultImg, m_pImageAllResult->resultImg, cv::COLOR_GRAY2BGR);
	}

	m_CheckResult_shareP->resultimg = m_pImageAllResult->resultImg;
	m_pdetlog->AddCheckstr(PrintLevel_1, "ResizeImg", "showImg size [w %d,h %d]-> show img [w %d,h %d] ",
						   m_CutRoi.width, m_CutRoi.height, sz.width, sz.height);
	return 0;
}

void ImgCheckAnalysisy::TaskFun_AIDet(std::shared_ptr<TaskInfo> task)
{
	task->SetStatus(TaskStep_run);
	long t1, t2;
	// AI 推理生成
	{
		t1 = CheckUtil::getcurTime();

		int rec = AI_Detect_Thread();

		t2 = CheckUtil::getcurTime();
		task->nresult = rec;
	}
	task->SetStatus(TaskStep_compate);
}

void ImgCheckAnalysisy::TaskFun_AI_Other(std::shared_ptr<TaskInfo> task)
{
	task->SetStatus(TaskStep_run);
	long t1, t2;
	// AI 推理生成
	{
		t1 = CheckUtil::getcurTime();

		int rec = AI_Other_Det_Thread();

		t2 = CheckUtil::getcurTime();
		task->nresult = rec;
	}
	task->SetStatus(TaskStep_compate);
}

void ImgCheckAnalysisy::TaskFun_QxClass(std::shared_ptr<TaskInfo> task)
{
	task->SetStatus(TaskStep_run);
	long t1, t2;
	// AI 推理生成
	{
		t1 = CheckUtil::getcurTime();

		int rec = AI_QX_Class_Thread();

		t2 = CheckUtil::getcurTime();
		task->nresult = rec;
	}
	task->SetStatus(TaskStep_compate);
}

int ImgCheckAnalysisy::Update_DetRoiList()
{
	m_pdetlog->AddCheckstr(PrintLevel_0, "Update_DetRoiList", "=======start:");
	float fx = m_pImageAllResult->fscale_detToresult_x;
	float fy = m_pImageAllResult->fscale_detToresult_y;

	int num = 0;
	cv::Rect offsetroi = m_Crop_Roi_paramImg;

	// if (m_pEdge_Align_Result && m_pEdge_Align_Result->buseOfft)
	// {
	// 	for (const auto &region : m_pCommonAnalysisyConfig->regionConfigArr)
	// 	{

	// 		if (m_pEdge_Align_Result->H.empty())
	// 		{

	// 			m_DetRoiList.Update_1(region.basicInfo.pointArry, offsetroi, m_pEdge_Align_Result->offt_x, m_pEdge_Align_Result->offt_y, fx, fy);
	// 		}
	// 		else
	// 		{

	// 			m_DetRoiList.Update_Marit(region.basicInfo.pointArry, offsetroi, m_pEdge_Align_Result->H, fx, fy);
	// 		}

	// 		// m_DetRoiList.Update_1(region.basicInfo.pointArry, offsetroi, m_pEdge_Align_Result->offt_x, m_pEdge_Align_Result->offt_y, fx, fy);
	// 	}
	// }
	// else
	{
		for (const auto &region : m_pCommonAnalysisyConfig->regionConfigArr)
		{
			m_DetRoiList.Update(region.basicInfo.pointArry, m_Crop_Roi_paramImg, fx, fy);
		}
	}

	m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, "info", "roiList_Src roi num %ld", m_DetRoiList.roiList_Src.size());
	// m_DetRoiList.print("m_DetRoiList");
	return 0;
}

int ImgCheckAnalysisy::Edge_Det()
{
	std::string strBaseLog = "Edge_Det";

	// return 0;
	// if (m_pImageAllResult->cameraBaseResult->pEdgeDetResult->pEdgeDet_roiList)
	// {
	// 	m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, strBaseLog, "  error pEdgeDet_roiList %ld",
	// 						   m_pImageAllResult->cameraBaseResult->pEdgeDetResult->pEdgeDet_roiList->size());
	// }
	// else
	// {
	// 	m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, strBaseLog, "  error pEdgeDet_roiList 111");
	// }

	if (!m_pFuntion->function.f_BaseDet.bOpen)
	{
		return 0;
	}

	if (m_pImageAllResult->cameraBaseResult->pEdgeDetResult->pEdgeDet_roiList &&
		m_pFuntion &&
		m_pImageAllResult->cameraBaseResult->pEdgeDetResult->pEdgeDet_roiList->size() > 0)
	{
	}
	else
	{
		m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, strBaseLog, "  error pEdgeDet_roiList");
		return 1;
	}
	if (!m_pFuntion->function.f_dege_Det.bOpen)
	{
		m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, strBaseLog, " param colse ");
		return 1;
	}
	long t1 = CheckUtil::getcurTime();
	m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, strBaseLog, " Start EdgeDet_roiList %ld param usetype =  %d ImageDet_shareP->ninstruct %d",
						   m_pImageAllResult->cameraBaseResult->pEdgeDetResult->pEdgeDet_roiList->size(),
						   m_pFuntion->function.f_dege_Det.type, m_pImageAllResult->cameraBaseResult->pEdgeDetResult->ninstruct);

	AI_Edge_QX_Det::DetConfig detconfig;
	detconfig.pEdgeDet_roiList = m_pImageAllResult->cameraBaseResult->pEdgeDetResult->pEdgeDet_roiList;
	detconfig.pdege_Det_config = &m_pFuntion->function.f_dege_Det;
	detconfig.strCamChannel = m_CheckResult_shareP->in_shareImage->strCameraName + m_CheckResult_shareP->in_shareImage->strChannel;
	detconfig.CutRoi = m_CutRoi;
	detconfig.ninstruct = m_CheckResult_shareP->in_shareImage->ninstruct;

	// cv::Mat temMask = cv::Mat::zeros(m_TemCheck.temImgList[TEM_IMG_IDX_AImask].size(),  CV_8UC1);
	if (m_pFuntion->function.f_dege_Det.bOpen)
	{
		if (m_pFuntion->function.f_dege_Det.bdetUse)
		{
			m_AIEdge_QX_Det.Detect(m_CheckResult_shareP->in_shareImage->img, m_pImageAllResult->qx_DetAIResult->AI_MaskImg, &detconfig, m_pdetlog);
		}
		else
		{

			cv::Mat temmask = m_pImageAllResult->qx_DetAIResult->AI_MaskImg.clone();

			m_AIEdge_QX_Det.Detect(m_CheckResult_shareP->in_shareImage->img, temmask, &detconfig, m_pdetlog);
			// m_CheckResult_shareP->resultMaskImg = temmask.clone();
		}
	}

	long t2 = CheckUtil::getcurTime();
	m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, strBaseLog, " End use time %ld ", t2 - t1);

	return 0;
}

int ImgCheckAnalysisy::DrawResult_Step_1()
{
	m_pdetlog->AddCheckstr(PrintLevel_0, "DrawResult_Step_1", "=======start");
	// std::cout << m_pBasicConfig->bDrawPreRoi << std::endl;
	if (m_pBasicConfig->bDrawPreRoi)
	{
		int n = 0;
		// std::cout << m_DetRoiList.roiList_Show.size() << std::endl;
		for (const auto &polygon : m_DetRoiList.roiList_Show)
		{
			// n++;
			// if (n == 1)
			// {
			// 	continue;
			// }

			// std::cout << polygon << std::endl;

			// 绘制多边形的边界（不填充），使用绿色线条，线宽为2
			cv::polylines(m_CheckResult_shareP->resultimg, polygon, true, cv::Scalar(128, 255, 0), 1); // true表示闭合多边形
		}
		// cv::imwrite(DetImgInfo_shareP->strChannel + "roi_src.png", m_pdetlog->temImgList[TEM_IMG_IDX_DrawSrc]);
		// cv::imwrite(DetImgInfo_shareP->strChannel + "roi_ss.png", m_pdetlog->temImgList[TEM_IMG_IDX_Result]);

		// getchar();
	}

	float fs_resize_x = m_pImageAllResult->resultImg.cols * 1.0f / m_pImageAllResult->detImg.cols;
	float fs_resize_y = m_pImageAllResult->resultImg.rows * 1.0f / m_pImageAllResult->detImg.rows;

	// 绘制对齐
	Align_Result *pAlignResult = &m_pImageAllResult->cameraBaseResult->pEdgeDetResult->m_align_Result;
	if (pAlignResult && pAlignResult->bDet && pAlignResult->bDraw)
	{

		std::vector<cv::Point> points;
		for (auto point : pAlignResult->feature_PointList_DetImg)
		{
			cv::Point p;
			p.x = point.x * fs_resize_x;
			p.y = point.y * fs_resize_y;
			points.push_back(p);
		}
		cv::polylines(m_CheckResult_shareP->resultimg, points, true, cv::Scalar(255, 255, 0), 2);

		// cv::Rect droi = ImageDet_shareP->alignResult.Crop_Roi_DetImg;
		// droi.x = 0;
		// droi.y = 0;
		// droi.x *= fs_resize_x;
		// droi.width *= fs_resize_x;

		// droi.y *= fs_resize_y;
		// droi.height *= fs_resize_y;

		// cv::rectangle(m_CheckResult_shareP->resultimg, droi, cv::Scalar(255, 255, 0));
	}
	// 临时存图
	if (DetImgInfo_shareP->bDebugsaveImg)
	{
		cv::imwrite(m_strCurDetCamChannel + "_temDraw.png", m_CheckResult_shareP->resultimg);
	}

	// 绘制 Roi
	if (m_pFuntion->function.f_dege_Det.bOpen && m_pFuntion->function.f_dege_Det.bshowRoi)
	{

		for (int i = 0; i < m_pImageAllResult->cameraBaseResult->pEdgeDetResult->pEdgeDet_roiList->size(); i++)
		{
			cv::Rect r = m_pImageAllResult->cameraBaseResult->pEdgeDetResult->pEdgeDet_roiList->at(i);

			r.x -= m_CutRoi.x;
			r.y -= m_CutRoi.y;

			r.x *= fs_resize_x;
			r.width *= fs_resize_x;
			r.y *= fs_resize_y;
			r.height *= fs_resize_y;

			cv::rectangle(m_CheckResult_shareP->resultimg, r, cv::Scalar(255, 0, 0), 1);
			if (false)
			{

				char buffer[128];

				sprintf(buffer, "%d ", i);

				std::string st1 = buffer;
				cv::Point p(r.x + r.width * 0.5, r.y + r.height * 0.5);
				cv::putText(m_CheckResult_shareP->resultimg, st1, p, cv::FONT_HERSHEY_SIMPLEX, 0.5, cv::Scalar(255, 0, 255), 0.5, 1, 0);
			}
		}
	}
	// cv::imwrite("sss.png", m_CheckResult_shareP->resultimg);
	return 0;
}

int ImgCheckAnalysisy::AIClassTypeToConfigType(int nAIQXType, cv::Rect qx_roi)
{

	// CONFIG_QX_NAME_ok_yisi,				 // 疑似
	// CONFIG_QX_NAME_AD_YX,			 // AD异显(P6873)
	// CONFIG_QX_NAME_X_line,			 // X_line(P3351)
	// CONFIG_QX_NAME_Y_line,			 // Y_line(P3452)
	// CONFIG_QX_NAME_Broken_line,		 // 断线(P3379)
	// CONFIG_QX_NAME_zara,			 // ZARA(P1153)
	// CONFIG_QX_NAME_MTX,				 // MTX(P1164)
	// CONFIG_QX_NAME_POL_Cell,		 // 异物(P1101)
	// CONFIG_QX_NAME_LD,				 // 亮点(P1112)
	// CONFIG_QX_NAME_AD,				 // 暗点(P1111)
	// CONFIG_QX_NAME_Scratch_L1,		 // 一级 轻 划伤(P1557)
	// CONFIG_QX_NAME_Scratch_L2,		 // 二级 严重 划伤(P1557)
	// CONFIG_QX_NAME_Dirty_L0,		 // 疑似浅层脏污(P0000)
	// CONFIG_QX_NAME_Dirty_L1,		 // 轻脏污(P0000)
	// CONFIG_QX_NAME_Dirty_L2,		 // 严重脏污(P0000)
	// CONFIG_QX_NAME_qipao,			 // 气泡(P0001)
	// CONFIG_QX_NAME_PS,				 // ps(P0002)
	// CONFIG_QX_NAME_Weak_Bright_Mura, // 白GAP(P1654)
	// CONFIG_QX_NAME_No_Label,		 // 缺POL(P2833)

	int resultError_type = CONFIG_QX_NAME_ok_yisi;
	switch (nAIQXType)
	{
	case AI_CLass_QX_NAME_ok_yisi:
		resultError_type = CONFIG_QX_NAME_ok_yisi;
		break;
	case AI_CLass_QX_NAME_yixian:
		resultError_type = CONFIG_QX_NAME_Class_AD_YX;
		break;
	case AI_CLass_QX_NAME_POL_CEL:
		resultError_type = CONFIG_QX_NAME_POL_Cell;
		break;
	case AI_CLass_QX_NAME_zara:
		resultError_type = CONFIG_QX_NAME_zara;
		break;
	case AI_CLass_QX_NAME_ps:
		resultError_type = CONFIG_QX_NAME_PS;
		break;
	case AI_CLass_QX_NAME_line:
		if (qx_roi.width > qx_roi.height)
		{
			resultError_type = CONFIG_QX_NAME_X_line;
		}
		else
		{
			resultError_type = CONFIG_QX_NAME_Y_line;
		}

		break;
	case AI_CLass_QX_NAME_fangge_line:
		resultError_type = CONFIG_QX_NAME_Y_line;
		break;
	case AI_CLass_QX_NAME_qipao:
		resultError_type = CONFIG_QX_NAME_qipao;
		break;
	case AI_CLass_QX_NAME_qing_huashang:
		resultError_type = CONFIG_QX_NAME_Scratch_L1;
		break;
	case AI_CLass_QX_NAME_mtx:
		resultError_type = CONFIG_QX_NAME_MTX;
		break;
	case AI_CLass_QX_NAME_yisi_qianzangwu:
		resultError_type = CONFIG_QX_NAME_Dirty_L0;
		break;
	case AI_CLass_QX_NAME_qing_zangwu:
		resultError_type = CONFIG_QX_NAME_Dirty_L1;
		break;
	case AI_CLass_QX_NAME_zhong_zangwu:
		resultError_type = CONFIG_QX_NAME_Dirty_L2;
		break;
	case AI_CLass_QX_NAME_andian:
		resultError_type = CONFIG_QX_NAME_AD;
		break;
	case AI_CLass_QX_NAME_huashang:
		resultError_type = CONFIG_QX_NAME_Scratch_L1;
		break;
	case AI_CLass_QX_NAME_zf:
		resultError_type = CONFIG_QX_NAME_ok_yisi;
		break;
	case AI_CLass_QX_NAME_other:
		resultError_type = CONFIG_QX_NAME_Other;
		break;
	default:
		break;
	}
	return resultError_type;
	return 0;
}

int ImgCheckAnalysisy::UpdateImgageScale()
{

	if (m_pBasicConfig->fImage_Scale_x > 0 && m_pBasicConfig->fImage_Scale_x < 1 &&
		m_pBasicConfig->fImage_Scale_y > 0 && m_pBasicConfig->fImage_Scale_y < 1)
	{

		m_fImgage_Scale_X = m_pBasicConfig->fImage_Scale_x;
		m_fImgage_Scale_Y = m_pBasicConfig->fImage_Scale_y;
	}

	return 0;
}

int ImgCheckAnalysisy::BLobToDetResult()
{
	long t1 = CheckUtil::getcurTime();
	m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, "BLobToDetResult", " Start old qx num  %ld", m_pDetResult->pQx_ErrorList->size());
	float fs_x = m_fImgage_Scale_X;
	float fs_y = m_fImgage_Scale_Y;
	int qx_num = blobs.blobCount;
	// 遍历每个检测blob
	for (int i = 0; i < blobs.blobCount; i++)
	{
		cv::Rect roi;
		roi.x = blobs.blobTab[i].minx;
		roi.y = blobs.blobTab[i].miny;
		roi.width = blobs.blobTab[i].maxx - blobs.blobTab[i].minx;
		roi.height = blobs.blobTab[i].maxy - blobs.blobTab[i].miny;

		int config_qx_type = blobs.blobTab[i].ErrType;

		float JudgArea = blobs.blobTab[i].JudgArea;
		float fsecondArea = JudgArea;
		std::string qx_name = CONFIG_QX_NAME_Names[config_qx_type];

		float flen = blobs.blobTab[i].len; // 长度

		QX_ERROR_INFO_ temerror;

		std::shared_ptr<DetLog> pQxlog = temerror.detlog;
		pQxlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, "BLobToDetResult", " %d /%d roi[%d %d %d %d] qx_name %s qx_type %d JudgArea %0.2f flen %0.2f",
							i, qx_num, roi.x, roi.y, roi.width, roi.height, qx_name.c_str(), config_qx_type, JudgArea, flen);
		// 异物和暗点进行二次分割 精确计算面积和长度的精确计算
		if (config_qx_type == CONFIG_QX_NAME_AD ||
			config_qx_type == CONFIG_QX_NAME_POL_Cell)
		{
			AI_SecondDet::DetConfigResult detconfigresult;
			detconfigresult.pfunction_secondDet = &m_pFuntion->function.f_SecondDetect;
			detconfigresult.SetAreaAndLen(blobs.blobTab[i].area, flen);
			detconfigresult.qx_roi = roi;
			detconfigresult.qx_name = qx_name;
			detconfigresult.qx_type = config_qx_type;
			detconfigresult.strChannel = m_CheckResult_shareP->in_shareImage->strChannel;
			detconfigresult.fImgage_Scale_X = m_fImgage_Scale_X;
			detconfigresult.fImgage_Scale_Y = m_fImgage_Scale_Y;
			detconfigresult.pdetlog = m_pdetlog;

			int detre = ReCalQX_AreaAndLen(&detconfigresult);

			pQxlog->AddCheckstr(PrintLevel_2, DET_LOG_LEVEL_3, " ReCalQX_AreaAndLen", "re =  %d, Old area  %f (mm2) New Area  %f; old len %0.2f new %0.2f",
								detre, JudgArea, detconfigresult.new_Area * fs_x * fs_y, detconfigresult.old_len, detconfigresult.new_len);
			if (detre == 0)
			{
				if (config_qx_type == CONFIG_QX_NAME_POL_Cell)
				{
					if (detconfigresult.pfunction_secondDet->pol_open_SingleCheck)
					{
						fsecondArea = detconfigresult.new_Area * fs_x * fs_y;
					}
					else
					{
						blobs.blobTab[i].area = detconfigresult.new_Area;
						JudgArea = blobs.blobTab[i].area * fs_x * fs_y;
						blobs.blobTab[i].JudgArea = JudgArea;
						fsecondArea = JudgArea;
					}
				}
				else
				{
					blobs.blobTab[i].area = detconfigresult.new_Area;
					JudgArea = blobs.blobTab[i].area * fs_x * fs_y;
					blobs.blobTab[i].JudgArea = JudgArea;
					fsecondArea = JudgArea;
				}
				flen = detconfigresult.new_len;
				blobs.blobTab[i].len = flen;
			}
		}

		if (config_qx_type == CONFIG_QX_NAME_MTX ||
			config_qx_type == CONFIG_QX_NAME_POL_Cell ||
			config_qx_type == CONFIG_QX_NAME_Other ||
			config_qx_type == CONFIG_QX_NAME_LD)
		{
			 qx_name = CONFIG_QX_NAME_Names[config_qx_type];
			// m_TemCheck.AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "LD", "stsrt  config_qx_type %s  ", qx_name.c_str());
			int dbresult = LDJudge(config_qx_type, roi, JudgArea, blobs.blobTab[i].maxValue, blobs.blobTab[i].grayDis, pQxlog);
			//int detre = 1;
			// 表示L0 和 DP 都有的 亮的
			if (dbresult == 1)
			{
				config_qx_type = CONFIG_QX_NAME_LD;
				qx_name = CONFIG_QX_NAME_Names[config_qx_type];
			}
			pQxlog->AddCheckstr(PrintLevel_2, DET_LOG_LEVEL_3, " LD Judge ", "%s  qx  %s ", Re_TO_STR_Pass_1(dbresult), qx_name.c_str());
		}
		// 如果是chess 画面，缺陷类型直接是chess异常。
		if (m_pFuntion->function.f_AIQX.bAllToChess)
		{
			config_qx_type = CONFIG_QX_NAME_Chess;
			qx_name = CONFIG_QX_NAME_Names[config_qx_type];
			pQxlog->AddCheckstr(PrintLevel_2, DET_LOG_LEVEL_3, "AllToChess", " Chess, qx  %d = %s ", config_qx_type, qx_name.c_str());
		}

		if (m_pFuntion->function.f_AIQX.bPOLToWhitePOL && config_qx_type == CONFIG_QX_NAME_POL_Cell)
		{
			bool bchange = true;
			if (m_pFuntion->function.f_AIQX.b127WhitePOl_UseDP)
			{
				cv::Mat DPMaskImg = m_pImageAllResult->cameraBaseResult->DP_MaskImg;
				if (!DPMaskImg.empty())
				{
					float fiou = CalImgScorl_t(m_pImageAllResult->qx_DetAIResult->AI_MaskImg(roi).clone(), DPMaskImg(roi).clone());
					// IOU
					if (fiou > m_pFuntion->function.f_AIQX.f127WhitePOl_DP_IOU)
					{
						pQxlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "pol change 127Cell", " fiou %f  > %f ", fiou, m_pFuntion->function.f_AIQX.f127WhitePOl_DP_IOU);
						bchange = false;
						// break;
					}
					else
					{
						bchange = true;
						pQxlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "pol change 127Cell", " fiou %f  <= %f ", fiou, m_pFuntion->function.f_AIQX.f127WhitePOl_DP_IOU);
					}
				}
				else
				{
					pQxlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "pol change 127Cell", " DPMaskImg is empty() ");
				}

				// m_TemCheck.AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "UseDPMask", " fiou %f  < 0.1 ", fiou);
			}
			else
			{
				pQxlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "pol change 127Cell", " NO Use DP ");
			}

			if (bchange)
			{
				config_qx_type = CONFIG_QX_NAME_127Cell;
				qx_name = CONFIG_QX_NAME_Names[config_qx_type];
				pQxlog->AddCheckstr(PrintLevel_2, DET_LOG_LEVEL_3, "pol change 127Cell", "  Suc, qx  %d = %s ", config_qx_type, qx_name.c_str());
			}
			else
			{
				pQxlog->AddCheckstr(PrintLevel_2, DET_LOG_LEVEL_3, "pol change 127Cell", "  Fail");
			}

			// m_TemCheck.AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "DET", " 127  CONFIG_QX_NAME_POL_Cell change  CONFIG_QX_NAME_127Cell ");
		}

		float fupS = UseUpMaskAnalysis(roi, m_pImageAllResult->qx_DetAIResult->AI_MaskImg, pQxlog);

		QX_Stauts qx_status = QX_Stauts_Analysis;

		// 和UP画面进行IOU判断
		if (m_pFuntion->function.f_UseUpQX.bOpen)
		{
			if (fupS >= m_pFuntion->function.f_UseUpQX.fIOU)
			{
				qx_status = QX_Stauts_Draw;
				pQxlog->AddCheckstr(PrintLevel_2, DET_LOG_LEVEL_3, "Up Mask judge", "UseUpQX.bOpen = true ;fupS = %0.2f >= %02f; qx_status = QX_Stauts_Draw", fupS, m_pFuntion->function.f_UseUpQX.fIOU);
			}
			else
			{
				pQxlog->AddCheckstr(PrintLevel_2, DET_LOG_LEVEL_3, "Up Mask judge", "UseUpQX.bOpen = true ;fupS = %0.2f < %02f ", fupS, m_pFuntion->function.f_UseUpQX.fIOU);
			}
		}
		else
		{
			pQxlog->AddCheckstr(PrintLevel_2, DET_LOG_LEVEL_3, "Up Mask judge", "UseUpQX.bOpen = false ;fupS = %0.2f ", fupS);
		}

		// 检测缺陷类型进行判断
		bool ban = JudgeQXAnalysis(config_qx_type, pQxlog);
		if (!ban)
		{
			qx_name = CONFIG_QX_NAME_Names[config_qx_type];
			pQxlog->AddCheckstr(PrintLevel_2, DET_LOG_LEVEL_3, "Judge QX", "qx function close, config_qx_type %s Not Det",
								qx_name.c_str());

			qx_status = QX_Stauts_Draw;
		}
		else
		{
			pQxlog->AddCheckstr(PrintLevel_2, DET_LOG_LEVEL_3, "Judge QX", "qx function open, config_qx_type %s  Det",
								qx_name.c_str());
		}

		// markline 判断，如果某些缺陷在markline内，就屏蔽掉，只绘制。
		bool isMarksheildQX = false;
		isMarksheildQX = Judge_MarkLine_QX(config_qx_type, roi, pQxlog);
		if (isMarksheildQX)
		{
			qx_name = CONFIG_QX_NAME_Names[config_qx_type];
			pQxlog->AddCheckstr(PrintLevel_2, DET_LOG_LEVEL_3, "MarkLine_QX", "MarkLine_QX close, config_qx_type %s Not Det",
								qx_name.c_str());

			qx_status = QX_Stauts_Draw;
		}
		else
		{
			pQxlog->AddCheckstr(PrintLevel_2, DET_LOG_LEVEL_3, "MarkLine_QX", "  config_qx_type %s  Det",
								qx_name.c_str());
		}

		pQxlog->AddCheckstr(PrintLevel_2, DET_LOG_LEVEL_3, "add qx", "config_qx_type %d = %s qx_status %d ", config_qx_type, qx_name.c_str(), qx_status);
		if (true)
		{

			temerror.roi = roi;
			temerror.Idx = m_pDetResult->pQx_ErrorList->size();
			temerror.area = blobs.blobTab[i].area;
			temerror.JudgArea = JudgArea;
			temerror.JudgArea_second = fsecondArea;
			temerror.energy = blobs.blobTab[i].energy;
			temerror.flen = blobs.blobTab[i].len;
			temerror.nconfig_qx_type = config_qx_type;
			temerror.qx_name = qx_name;
			temerror.maxValue = blobs.blobTab[i].maxValue;
			temerror.grayDis = blobs.blobTab[i].grayDis;
			temerror.density = blobs.blobTab[i].density;
			temerror.fUpIou = fupS;
			temerror.whiteOrBlack = blobs.blobTab[i].whiteOrblack;
			temerror.qx_status = qx_status;

			// 添加弱化检测
			{
				cv::Point pCenter;
				pCenter.x = roi.x + roi.width * 0.5;
				pCenter.y = roi.y + roi.height * 0.5;
				for (int iregion = 1; iregion < m_DetRoiList.roiList_Src.size(); iregion++)
				{

					bool bInChannel = false;
					// 当前区域是否有包含的通道。
					if (m_pCommonAnalysisyConfig->regionConfigArr.at(iregion).basicInfo.ChannelArry.size() > 0)
					{
						std::string strchannelshow = "";
						for (const auto &chanel : m_pCommonAnalysisyConfig->regionConfigArr.at(iregion).basicInfo.ChannelArry)
						{
							strchannelshow += chanel;
							strchannelshow += ";";
							if (CheckUtil::compareIgnoreCase(m_strCurDetChannel, chanel))
							{
								bInChannel = true;
							}
						}

						pQxlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "pre Judge", "iregion %d channel  %s ,channellist %s",
											iregion, BOOL_TO_STR(bInChannel), strchannelshow.c_str());
					}
					// 需要弱化处理
					if (bInChannel)
					{
						const std::vector<cv::Point> &polygon = m_DetRoiList.roiList_Src[iregion];
						double result = cv::pointPolygonTest(polygon, pCenter, false);
						if (result < 0)
						{
							continue;
						}
						temerror.detRegionidxList.push_back(iregion);
					}
				}
				// 添加基础检测
				temerror.detRegionidxList.push_back(0);
			}

			m_pDetResult->pQx_ErrorList->push_back(temerror);
			// m_pdetlog->AddCheckstr(PrintLevel_3, " BLobToDetResult ", "qx %d ErrType %d ", i, blobs.blobTab[i].ErrType);
			//  printf("- %s idx %d  a %f v %d h %f l %f\n", DetImgInfo_shareP->strChannel.c_str(), i, JudgArea, blobs.blobTab[i].maxValue, blobs.blobTab[i].grayDis, flen);
		}
	}
	long t2 = CheckUtil::getcurTime();
	m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, "BLobToDetResult", " end  qx num  %ld use time %ld", m_pDetResult->pQx_ErrorList->size(), t2 - t1);
	return 0;
}

int ImgCheckAnalysisy::ReCalQX_AreaAndLen(AI_SecondDet::DetConfigResult *pdetConfig)
{
	int paramIdx = m_QxInParamListIdx[pdetConfig->qx_type];
	if (paramIdx < 0)
	{
		return 0;
		/* code */
	}
	CheckConfig_Regions_Param *pParam = &m_pRegionAnalysisyParam->checkConfig_Regions_type[ANALYSIS_TYPE_TF].checkConfig_Regions_Param.at(paramIdx);

	float min_detArea = 99999;
	bool bhave = false;

	for (int j = 0; j < pParam->useNum; j++)
	{
		if (!pParam->paramArr[j].bEnable)
		{

			continue;
		}
		bhave = true;
		float At = pParam->paramArr[j].area;
		if (At < min_detArea)
		{
			min_detArea = At;
		}
	}
	if (!bhave)
	{
		min_detArea = 0;
	}
	pdetConfig->min_DetArea = min_detArea;
	// printf("******************** mask %d %d \n", m_pImageAllResult->qx_DetAIResult->AI_MaskImg.cols, m_pImageAllResult->qx_DetAIResult->AI_MaskImg.rows);
	int re = m_SecondDet.Detect(m_pImageAllResult->detImg, m_pImageAllResult->qx_DetAIResult->AI_MaskImg, pdetConfig);

	return re;
}

int ImgCheckAnalysisy::CreatAIDetSmallRoi(const cv::Mat &detimg, std::shared_ptr<AIModel_Base> pAI_Model, std::vector<cv::Rect> &SmallList)
{

	SmallRoiList.clear();
	SmallRoiList.erase(SmallRoiList.begin(), SmallRoiList.end());
	cv::Rect cutRoi;
	cutRoi.x = 0;
	cutRoi.y = 0;
	cutRoi.width = detimg.cols - 0;
	cutRoi.height = detimg.rows - 0;

	int AIInputImg_width = pAI_Model->input_0.width;
	int AIInputImg_height = pAI_Model->input_0.height;

	int re = CheckUtil::cutSmallImg(detimg, SmallRoiList, cutRoi, AIInputImg_width, AIInputImg_height, 0, 0);

	m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, "Small roi", " cutSmallImg  Num %d", SmallRoiList.size());
	if (re != 0 || SmallRoiList.size() <= 0)
	{
		m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, "Small roi", " cutSmallImg error  %d", re);

		return 1;
	}

	det_SmallImgNum = SmallRoiList.size();
	// 字符的增加进去
	std::shared_ptr<ZF_Result> pZF_Result = m_pImageAllResult->cameraBaseResult->pZF_Result; // zf 检测结果
	if (pZF_Result && pZF_Result->nresult == 0)
	{
		std::vector<cv::Rect> addroi;
		// 字符 居中 处理
		for (int izf = 0; izf < pZF_Result->ZF_centerPoint.size(); izf++)
		{
			bool bedg = false;
			cv::Point p = pZF_Result->ZF_centerPoint.at(izf);
			for (int i = 0; i < SmallRoiList.size(); i++)
			{
				cv::Rect roi = SmallRoiList.at(i);
				if (std::abs(p.x - roi.x) < 150 ||
					std::abs(p.x - (roi.x + roi.width)) < 150 ||
					std::abs(p.y - roi.y) < 150 ||
					std::abs(p.y - (roi.y + roi.height)) < 150)
				{
					bedg = true;
				}
			}
			if (bedg)
			{
				cv::Rect newroi;
				newroi.x = p.x - AIInputImg_width / 2;
				newroi.width = AIInputImg_width;
				if (newroi.x < 0)
				{
					newroi.x = 0;
				}
				if ((newroi.x + AIInputImg_width) > detimg.cols)
				{
					newroi.x = detimg.cols - AIInputImg_width;
				}
				newroi.y = p.y - AIInputImg_height / 2;
				newroi.height = AIInputImg_height;
				if (newroi.y < 0)
				{
					newroi.y = 0;
				}
				if ((newroi.y + AIInputImg_height) > detimg.rows)
				{
					newroi.y = detimg.rows - AIInputImg_height;
				}

				addroi.push_back(newroi);
			}
		}
		// printf("***zf num  size=%zu,  add New AI roi %zu\n", m_ZF_centerPoint.size(), addroi.size());
		m_pdetlog->AddCheckstr(PrintLevel_1, "Small roi", "zf num  size=%zu,  add New AI roi %zu", pZF_Result->ZF_centerPoint.size(), addroi.size());

		for (int izf = 0; izf < addroi.size(); izf++)
		{
			SmallRoiList.push_back(addroi.at(izf));
			// cv::rectangle(imshow, addroi.at(izf), cv::Scalar(0, 255, 255));
		}
		m_pdetlog->AddCheckstr(PrintLevel_1, "Small roi", " Add New zf AI roi  %d", addroi.size());
		// cv::imwrite("edg.png", imshow);
		// printf("---------- at edg 1111111\n");
		// getchar();
		// 判断 字符 是否在切图的中心
	}

	return 0;
}

int ImgCheckAnalysisy::AI_Classify_New(const cv::Mat &src_Img, cv::Rect qx_roi, float fjustarea, float *fmaxScore)
{

	std::shared_ptr<AIModel_Base> pAIDet;
	pAIDet = AI_Factory->AI_defect_Cls_L0;

	int deal_image_width = pAIDet->input_0.width;
	int deal_image_height = pAIDet->input_0.height;

	int re_ConfigType = CONFIG_QX_NAME_ok_yisi;
	std::vector<cv::Rect> SmallRoiList;
	int re = m_AIClassify.GetDetRoiList(src_Img, qx_roi, SmallRoiList, deal_image_width, deal_image_height);
	int blobNum = SmallRoiList.size();
	if (re != 0)
	{
		m_pdetlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "AI_Classify", "SmallRoiList Error");
		return re_ConfigType;
	}
	if (blobNum <= 0)
	{
		m_pdetlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "AI_Classify", "SmallRoiList is empyt");
		return re_ConfigType;
	}

	cv::Size sz = cv::Size(deal_image_width, deal_image_height);

	int maxcls = 20;
	int ClsList[20] = {0};
	int AI_result = -1;

	int halfnum = std::ceil(blobNum * 1.0f / 2);

	AI_Classify_Info ClassifyList[20];
	for (int i = 0; i < maxcls; i++)
	{
		ClassifyList[i].Init();
	}

	long t2 = CheckUtil::getcurTime();
	const int totalTasks = blobNum;
	int submitted = 0;
	int completed = 0;
	int detblobIdx = 0;
	cv::Mat AI_detImage = m_pImageAllResult->AI_detImg;

	long t211 = CheckUtil::getcurTime();
	while (completed < totalTasks)
	{
		// 如果任务还没提交完，且当前处理任务数 < 2，提交新任务
		if (submitted < totalTasks && runner->GetProcessingCount() < 10)
		{

			std::shared_ptr<AIMulThreadRunBase::AITask> task = std::make_shared<AIMulThreadRunBase::AITask>();
			task->id = completed;
			task->roi = SmallRoiList.at(submitted);

			if (3 != AI_detImage.channels())
			{
				cv::cvtColor(AI_detImage(task->roi), task->input, cv::COLOR_GRAY2BGR);
			}
			else
			{
				task->input = AI_detImage(task->roi).clone();
			}

			task->engine = pAIDet;
			task->bclass = true;
			runner->SubmitTask(task);
			submitted++;
		}

		// 尝试取结果
		std::shared_ptr<AIMulThreadRunBase::AITask> result;
		if (runner->PopResult(result))
		{

			int cls_num = result->cls_label;
			if (cls_num >= 0 && cls_num < maxcls)
			{
				ClassifyList[cls_num].num++;
				ClassifyList[cls_num].score += result->cls_score;
				ClassifyList[cls_num].avgScore = ClassifyList[cls_num].score / ClassifyList[cls_num].num;
			}
			completed++;
		}
		else
		{
			std::this_thread::sleep_for(std::chrono::milliseconds(1));
		}
	}

	int max_num = 0;
	float max_avgScore = 0;
	for (int idx = 0; idx < maxcls; idx++)
	{
		// ClassifyList[idx].print(std::to_string(idx));
		// 数量优先
		if (ClassifyList[idx].num > max_num)
		{
			max_num = ClassifyList[idx].num;
			max_avgScore = ClassifyList[idx].avgScore;
			AI_result = idx;
		}
		else if (ClassifyList[idx].num == max_num)
		{
			// 得分优先
			if (ClassifyList[idx].avgScore > max_avgScore)
			{
				max_num = ClassifyList[idx].num;
				max_avgScore = ClassifyList[idx].avgScore;
				AI_result = idx;
			}
		}
	}

	// printf("*********** Model Out %d  max_num %d halfnum %d\n", AI_result, max_num, halfnum);
	int cls_num = AI_result;
	*fmaxScore = max_avgScore;
	std::string strclassName = "";
	//  启用黑白分类
	{

		int temClass = cls_num;

		{
			switch (temClass)
			{
			case 0:
				cls_num = AI_CLass_QX_NAME_ok_yisi;
				strclassName = "ok_ys";
				break;
			case 1:
				cls_num = AI_CLass_QX_NAME_POL_CEL;
				strclassName = "POL_CEL";
				break;
			case 2:
				cls_num = AI_CLass_QX_NAME_zara;
				strclassName = "zara";
				break;
			case 3:
				cls_num = AI_CLass_QX_NAME_andian;
				strclassName = "andian";
				break;
			case 4:
				cls_num = AI_CLass_QX_NAME_yisi_qianzangwu;
				strclassName = "yisi_qianzangwu";
				break;
			case 5:
				cls_num = AI_CLass_QX_NAME_huashang;
				strclassName = "huashang";
				break;
			case 6:
				cls_num = AI_CLass_QX_NAME_line;
				strclassName = "line";
				break;
			case 7:
				cls_num = AI_CLass_QX_NAME_ps;
				strclassName = "ps";
				break;
			case 8:
				cls_num = AI_CLass_QX_NAME_mtx;
				strclassName = "mtx";
				break;
			case 9:
				cls_num = AI_CLass_QX_NAME_yixian;
				strclassName = "yixian";
				break;
			case 10:
				cls_num = AI_CLass_QX_NAME_zhong_zangwu;
				strclassName = "zhong_zangwu";
				break;
			case 11:
				cls_num = AI_CLass_QX_NAME_qipao;
				strclassName = "qipao";
				break;
			case 12:
				cls_num = AI_CLass_QX_NAME_qing_zangwu;
				strclassName = "qing_zangwu";
				break;
			case 13:
				cls_num = AI_CLass_QX_NAME_other;
				strclassName = "other";
				break;
			default:
				break;
			}
		}
	}

	m_pdetlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "AI_Classify", "AI Model Out %d = AI Class num %d = %s  %f", AI_result, cls_num, strclassName.c_str(), *fmaxScore);
	// 已经分成 线的 进行二次判断
	if (AI_CLass_QX_NAME_line == cls_num)
	{

		cls_num = AI_CLass_QX_NAME_line;
		// printf("\n\n\n\n\n\n\n\n\n--------- flenr %f len %d,widt %d,fjustarea %f\n", flenr, len, widt, fjustarea);
	}
	else
	{
		// 对不是线的 进行也进行二次判断
		//  线的补充分类
		if (true)
		{
			// 长宽比
			float flenr = 1;
			int len = 0;
			int widt = 0;
			if (qx_roi.width > qx_roi.height)
			{
				flenr = qx_roi.width * 1.0 / qx_roi.height;
				len = qx_roi.width;
				widt = qx_roi.height;
			}
			else
			{
				flenr = qx_roi.height * 1.0 / qx_roi.width;
				widt = qx_roi.width;
				len = qx_roi.height;
			}

			// 长宽比过大，判断成
			if (flenr > 18 &&
				len > 70 &&
				widt < 220 &&
				fjustarea < 800)
			{
				// printf("\n\n\n\n\n\n\n\n\n--------- flenr %f len %d,widt %d,fjustarea %f\n", flenr,len,widt,fjustarea);
				// getchar();
				cls_num = AI_CLass_QX_NAME_line;
				strclassName = "line";
			}
			// 长宽比过小，判断成
			else if (flenr > 4 &&
				len > 180 &&
				widt < 220 &&
				fjustarea < 800 &&
				fjustarea > 20)
			{
				// printf("\n\n\n\n\n\n\n\n\n--------- flenr %f len %d,widt %d,fjustarea %f\n", flenr,len,widt,fjustarea);
				// getchar();
				cls_num = AI_CLass_QX_NAME_line;
				strclassName = "line";
			}
		}
	}

	// printf("--------- 0   cls_num %d \n", cls_num);
	re_ConfigType = AIClassTypeToConfigType(cls_num, qx_roi);

	m_pdetlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "AI_Classify", "AI Class %d = %s --> Config Class %d , score %f ", cls_num, strclassName.c_str(), re_ConfigType, *fmaxScore);
	// getchar();

	return re_ConfigType;
}

float ImgCheckAnalysisy::UseUpMaskAnalysis(cv::Rect teroi, const cv::Mat AIMaskImg, std::shared_ptr<DetLog> pQxlog)
{
	float fs = 0;
	if (!m_pFuntion->function.f_UseUpQX.bOpen)
	{
		pQxlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "Up Mask  ", "bUseUpImg close  ");
		// printf(">>>>>>>>>>>>>bUseUpImg close \n");
		return fs;
	}
	if (AIMaskImg.empty())
	{
		pQxlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "Up Mask  ", "AIMaskImg.empty() ");
		return fs;
	}
	cv::Mat upMaskImg = m_pImageAllResult->cameraBaseResult->UP_MaskImg;
	if (upMaskImg.empty())
	{
		pQxlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "Up Mask  ", "upMaskImg.empty() ");
		return fs;
	}
	if (teroi.width > 500 || teroi.height > 500)
	{
		pQxlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "Up Mask  ", "teroi.width > 500 || teroi.height > 500");
		return fs;
	}
	CheckUtil::SizeRect(teroi, AIMaskImg.cols, AIMaskImg.rows, 20, 20);

	fs = CalImgScorl(AIMaskImg(teroi).clone(), upMaskImg(teroi).clone());
	// m_TemCheck.AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "Up Mask  ", "x w h d %d %d %d %d fs =  %f", teroi.x, teroi.y, teroi.width, teroi.height, fs);
	// getchar();

	return fs;
}

bool ImgCheckAnalysisy::Judge_MarkLine_QX(int nqx_configType, cv::Rect detqx_Roi, std::shared_ptr<DetLog> pQxlog)
{
	if (!m_pbaseCheckFunction->markLine.bOpen || !m_pbaseCheckFunction->markLine.bUse_qx_Sheild)
	{
		pQxlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "MarkLine_QX ", "markline qx sheild is close ");
		return false;
	}

	bool re = false;
	std::string qx_name = CONFIG_QX_NAME_Names[nqx_configType];
	std::string det_qx = ConfigTypeToWebDetType(nqx_configType);
	for (int i = 0; i < m_pbaseCheckFunction->markLine.sheil_qx_List.size(); i++)
	{
		std::string strqx = m_pbaseCheckFunction->markLine.sheil_qx_List.at(i);
		if (det_qx == strqx)
		{
			re = true;
			break;
		}
	}
	if (!re)
	{
		return re;
	}
	if (m_pImageAllResult->cameraBaseResult->pMarkLineResult->markLine_Roi_X.width > 0 &&
		m_pImageAllResult->cameraBaseResult->pMarkLineResult->markLine_Roi_X.height > 0)
	{
		float ioux = CheckUtil::CalRoi2RoiPre(detqx_Roi, m_pImageAllResult->cameraBaseResult->pMarkLineResult->markLine_Roi_X);
		pQxlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "Judge_MarkLine_QX ", "det qx %s  -> markline qx %s  x iou %f  : %f ",
							qx_name.c_str(), det_qx.c_str(), ioux, m_pbaseCheckFunction->markLine.qx_sheild_iou);

		if (ioux > m_pbaseCheckFunction->markLine.qx_sheild_iou)
		{
			return true;
		}
	}
	if (m_pImageAllResult->cameraBaseResult->pMarkLineResult->markLine_Roi_Y.width > 0 &&
		m_pImageAllResult->cameraBaseResult->pMarkLineResult->markLine_Roi_Y.height > 0)
	{
		float iouy = CheckUtil::CalRoi2RoiPre(detqx_Roi, m_pImageAllResult->cameraBaseResult->pMarkLineResult->markLine_Roi_Y);
		pQxlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "Judge_MarkLine_QX ", "det qx %s  -> markline qx %s  y iou %f  : %f ",
							qx_name.c_str(), det_qx.c_str(), iouy, m_pbaseCheckFunction->markLine.qx_sheild_iou);

		if (iouy > m_pbaseCheckFunction->markLine.qx_sheild_iou)
		{
			return true;
		}
	}

	return false;
}

int ImgCheckAnalysisy::CalProductSize()
{
	float fw = m_CutRoi.width * m_fImgage_Scale_X;
	float fh = m_CutRoi.height * m_fImgage_Scale_Y;
	fw = std::ceil(fw * 10) / 10;
	fh = std::ceil(fh * 10) / 10;
	m_CheckResult_shareP->productWidht_mm = fw;
	m_CheckResult_shareP->productHeight_mm = fh;

	m_pdetlog->AddCheckstr(PrintLevel_1, "CalProductSize", "Det ROI [w %d,h %d] (piexl) -> [w %f h %f](mm),scale %f %f",
						   m_CutRoi.width, m_CutRoi.height, fw, fh, m_fImgage_Scale_X, m_fImgage_Scale_Y);
	return 0;
}

int ImgCheckAnalysisy::ImgPreDet()
{
	m_pdetlog->AddCheckstr(PrintLevel_0, "ImgPreDet", "=======start");
	// 计算产品尺寸
	CalProductSize();

	if (m_pbaseCheckFunction->saveImg.bSaveClsImg)
	{
		creatsavedir();
	}

	m_CheckResult_shareP->cutSrcimg = m_pImageAllResult->detImg;
	ResizeImg();

	m_pImageAllResult->fscale_detToresult_x = m_pImageAllResult->resultImg.cols * 1.0f / m_pImageAllResult->detImg.cols;
	m_pImageAllResult->fscale_detToresult_y = m_pImageAllResult->resultImg.rows * 1.0f / m_pImageAllResult->detImg.rows;
	return 0;
}

int ImgCheckAnalysisy::DetPreImage()
{
	m_pdetlog->AddCheckstr(PrintLevel_0, "DetPreImage", "=======start");
	// 生成 检测的图片
	cv::Mat image;
	image = m_CheckResult_shareP->in_shareImage->img;
	if (image.channels() == 3)
	{
		cv::cvtColor(image(m_CutRoi), m_pImageAllResult->detImg, cv::COLOR_RGB2GRAY);
	}
	else
	{
		m_pImageAllResult->detImg = image(m_CutRoi).clone();
	}

	// 对边缘填充 180
	{
		if (!m_pImageAllResult->cameraBaseResult->pEdgeDetResult->edge_cutMask.empty())
		{
			cv::Mat shieldmask = m_pImageAllResult->cameraBaseResult->pEdgeDetResult->edge_cutMask;
			if (shieldmask.size() == m_pImageAllResult->detImg.size())
			{
				m_pImageAllResult->detImg.setTo(180, shieldmask);
				// 在 mask 区域设置值为 180
				// cv::imwrite(m_CheckResult_shareP->in_shareImage->strChannel + "sss.png", m_TemCheck.temImgList[TEM_IMG_IDX_SrcCrop]);
				// getchar();
			}
		}
	}

	Align_Result *pAlignResult = &m_pImageAllResult->cameraBaseResult->pEdgeDetResult->m_align_Result;

	m_pdetlog->AddCheckstr(PrintLevel_1, "DetPreImage", "Align_Result Align : det :%d  or use :%d", pAlignResult->bDet, pAlignResult->bUse);
	// 更新 参数图片的crop。
	if (pAlignResult->bDet && pAlignResult->bUse)
	{
		m_pdetlog->AddCheckstr(PrintLevel_1, "DetPreImage", " =========== Use Align");
		m_Crop_Roi_paramImg = pAlignResult->Crop_Roi_ParmImg;
		if (m_Crop_Roi_paramImg.x < 0)
		{
			m_Crop_Roi_paramImg.x = 0;
		}
		if (m_Crop_Roi_paramImg.x + m_Crop_Roi_paramImg.width > image.cols)
		{
			m_Crop_Roi_paramImg.x = image.cols - m_Crop_Roi_paramImg.width;
		}
		if (m_Crop_Roi_paramImg.y < 0)
		{
			m_Crop_Roi_paramImg.y = 0;
		}
		if (m_Crop_Roi_paramImg.y + m_Crop_Roi_paramImg.height > image.rows)
		{
			m_Crop_Roi_paramImg.y = image.rows - m_Crop_Roi_paramImg.height;
		}
		m_pImageAllResult->pDetResult->Param_CropRoi = m_Crop_Roi_paramImg;
	}
	else
	{
		m_pdetlog->AddCheckstr(PrintLevel_1, "DetPreImage", " ===========NO Use Align");
	}

	int re = UpdateSheildMask(m_CheckResult_shareP->in_shareImage->strChannel, m_Crop_Roi_paramImg);

	// AI 检测的最小尺寸
	{
		std::shared_ptr<AIModel_Base> pAI_Model;
		pAI_Model = AI_Factory->AI_defect_NF;
		m_pImageAllResult->AI_Det_Img_Width = pAI_Model->input_0.width;
		m_pImageAllResult->AI_Det_Img_Height = pAI_Model->input_0.height;

		// 有一边 不小于模型输入尺寸
		// 1、如果输入图不够 模型 输入的最小尺寸，需要调整。
		if (m_pImageAllResult->detImg.cols < m_pImageAllResult->AI_Det_Img_Width || m_pImageAllResult->detImg.rows < m_pImageAllResult->AI_Det_Img_Height)
		{
			cv::Rect tem_ROI = cv::Rect(0, 0, m_pImageAllResult->detImg.cols, m_pImageAllResult->detImg.rows);
			int imgw = m_pImageAllResult->detImg.cols;
			int imgh = m_pImageAllResult->detImg.rows;
			if (m_pImageAllResult->detImg.cols < m_pImageAllResult->AI_Det_Img_Width)
			{
				imgw = m_pImageAllResult->AI_Det_Img_Width;
			}
			if (m_pImageAllResult->detImg.rows < m_pImageAllResult->AI_Det_Img_Height)
			{
				imgh = m_pImageAllResult->AI_Det_Img_Height;
			}
			m_pImageAllResult->AI_detImg = cv::Mat(imgh, imgw, CV_8U, cv::Scalar(180));
			m_pImageAllResult->detImg.copyTo(m_pImageAllResult->AI_detImg(tem_ROI));

			m_pImageAllResult->AI_shieldImg = cv::Mat(imgh, imgw, CV_8U, cv::Scalar(180));
			m_pImageAllResult->shieldImg.copyTo(m_pImageAllResult->AI_shieldImg(tem_ROI));

			// shieldImg.copyTo(temImg(tem_ROI));
			// shieldImg = temImg.clone();
			m_pImageAllResult->bChangeSize = true;
			m_pdetlog->AddCheckstr(PrintLevel_1, "DetPreImage", "AI_Detect Imge size[%d %d] < AI model size[%d %d] change size true",
								   m_pImageAllResult->detImg.cols, m_pImageAllResult->detImg.rows,
								   m_pImageAllResult->AI_Det_Img_Width, m_pImageAllResult->AI_Det_Img_Height);
			// 是否要存图
			if (m_pImageAllResult->result->in_shareImage->bDebugsaveImg)
			{
				cv::imwrite(m_strCurDetCamChannel + "_AI_shield.png", m_pImageAllResult->AI_shieldImg);
				cv::imwrite(m_strCurDetCamChannel + "_AI_detimg.png", m_pImageAllResult->AI_detImg);
			}
		}
		else
		{
			m_pImageAllResult->AI_detImg = m_pImageAllResult->detImg;
			m_pImageAllResult->AI_shieldImg = m_pImageAllResult->shieldImg;
		}
	}

	return 0;
}

int ImgCheckAnalysisy::UpdateSheildMask(std::string strChannel, cv::Rect roi)
{
	cv::Mat L255shieldMask = m_pImageAllResult->cameraBaseResult->pEdgeDetResult->shieldMask;
	if (L255shieldMask.empty())
	{
		m_pImageAllResult->shieldImg = cv::Mat(roi.height, roi.width, CV_8UC1, cv::Scalar(0));
	}
	else
	{
		m_pImageAllResult->shieldImg = L255shieldMask.clone();
	}

	cv::Mat curdstshieldMask = m_pImageAllResult->shieldImg;

	if (m_pFuntion != NULL && m_pFuntion->function.f_ShieldRegion.bOpen)
	{
		// 这个是界面绘制的 屏蔽区域图片
		cv::Mat temmask = m_pFuntion->function.f_ShieldRegion.shieldMask;
		if (!temmask.empty())
		{
			// 是否要存图
			if (m_pImageAllResult->result->in_shareImage->bDebugsaveImg)
			{
				cv::imwrite(m_strCurDetCamChannel + "_parma_shieldImg.png", temmask);
			}

			if (CheckUtil::RoiInImg(roi, temmask))
			{
				if (curdstshieldMask.cols == roi.width &&
					curdstshieldMask.rows == roi.height)
				{
					curdstshieldMask.setTo(255, temmask(roi));
					// cv::imwrite(strChannel+"1.png",DetImgInfo_shareP->other_channel_Result_mask);
					// cv::imwrite(strChannel+"2.png",temmask(roi));
					m_pdetlog->AddCheckstr(PrintLevel_1, "UpdateSheildMask", "strChannel %s  Succ", strChannel.c_str());
				}
			}
			else
			{
				m_pdetlog->AddCheckstr(PrintLevel_1, "UpdateSheildMask", " strChannel %s  roi %d %d %d %d != img %d %d error", strChannel.c_str(),
									   roi.x, roi.y, roi.width, roi.height, temmask.cols, temmask.rows);
			}
		}
		else
		{
			m_pdetlog->AddCheckstr(PrintLevel_1, "UpdateSheildMask", "strChannel %s m_SheildMask empty  error ", strChannel.c_str());
		}
	}
	else
	{
		if(!m_pFuntion->function.f_ShieldRegion.bOpen)
			m_pdetlog->AddCheckstr(PrintLevel_1, "UpdateSheildMask", "strChannel %s m_pFuntion bOpen is false ", strChannel.c_str());
		if(m_pFuntion == NULL)
			m_pdetlog->AddCheckstr(PrintLevel_1, "UpdateSheildMask", "strChannel %s m_pFuntion is NULL error ", strChannel.c_str());
	}
	// 是否要存图
	if (m_pImageAllResult->result->in_shareImage->bDebugsaveImg)
	{
		cv::imwrite(m_strCurDetCamChannel + "_shield_Result.png", m_pImageAllResult->shieldImg);
	}
	// getchar();
	return 0;
}

int ImgCheckAnalysisy::AI_Det_YX(const cv::Mat &cropImg)
{

	m_pdetlog->AddCheckstr(PrintLevel_1, "AI_Det_YX", "============ Start");
	std::shared_ptr<AIModel_Base> pAI_Model = AI_Factory->AI_defect_YX_1;
	if (m_pFuntion && m_pFuntion->function.f_YXDet.bOpen)
	{
		if (m_pFuntion->function.f_YXDet.strModle == "YX_1")
		{
			pAI_Model = AI_Factory->AI_defect_YX_1;
		}
		else
		{
			pAI_Model = AI_Factory->AI_defect_YX_2;
		}
	}
	else
	{
		m_pdetlog->AddCheckstr(PrintLevel_2, "AI_Det_YX", "============  function close");
		return 1;
	}

	cv::Mat inImg;
	cv::Size sz;

	sz.width = pAI_Model->input_0.width;
	sz.height = pAI_Model->input_0.height;
	cv::resize(cropImg, inImg, sz, 0, 0, cv::INTER_AREA);

	pAI_Model->AIDet(inImg, m_pImageAllResult->YX_MaskImg);
	if (m_pImageAllResult->result->in_shareImage->bDebugsaveImg)
	{
		cv::imwrite(m_strCurDetCamChannel + "_YX_in.png", inImg);
		cv::imwrite(m_strCurDetCamChannel + "_YX_in_mask.png", m_pImageAllResult->YX_MaskImg);
	}

	m_pdetlog->AddCheckstr(PrintLevel_1, "AI_Det_YX", "============ end");

	return 0;
}

int ImgCheckAnalysisy::Detect_LackPol(const cv::Mat &cropImg)
{
	m_pdetlog->AddCheckstr(PrintLevel_1, "AI_LackPol", "============ Start");
	std::shared_ptr<AIModel_Base> pAI_Model = AI_Factory->AI_defect_LackPol;
	if (m_pFuntion && m_pFuntion->function.f_Dectect_LackPol.bOpen)
	{
	}
	else
	{
		m_pdetlog->AddCheckstr(PrintLevel_2, "AI_LackPol", "============  function close");
		return 1;
	}

	cv::Mat inImg;
	cv::Size sz;

	sz.width = pAI_Model->input_0.width;
	sz.height = pAI_Model->input_0.height;
	cv::resize(cropImg, inImg, sz, 0, 0, cv::INTER_AREA);

	pAI_Model->AIDet(inImg, m_pImageAllResult->LcakPol_MaskImg);
	if (m_pImageAllResult->result->in_shareImage->bDebugsaveImg)
	{
		cv::imwrite(m_strCurDetCamChannel + "_LcakPol_in.png", inImg);
		cv::imwrite(m_strCurDetCamChannel + "_LcakPol_in_mask.png", m_pImageAllResult->LcakPol_MaskImg);
	}
	m_pdetlog->AddCheckstr(PrintLevel_1, "AI_LackPol", "============ end");

	return 0;
}

std::string ImgCheckAnalysisy::ConfigTypeToWebDetType(int nconfigType)
{

	// Function_CONFIG_QX_NAME_ok_yisi,		  // 疑似
	// 	Function_CONFIG_QX_NAME_YX,				  // AD异显(P6873)
	// 	Function_CONFIG_QX_NAME_line,			  // X_line(P3351)
	// 	Function_CONFIG_QX_NAME_zara,			  // ZARA(P1153)
	// 	Function_CONFIG_QX_NAME_MTX,			  // MTX(P1164)
	// 	Function_CONFIG_QX_NAME_POL_Cell,		  // 异物(P1101)
	// 	Function_CONFIG_QX_NAME_LD,				  // 亮点(P1112)
	// 	Function_CONFIG_QX_NAME_AD,				  // 暗点(P1111)
	// 	Function_CONFIG_QX_NAME_Scratch,		  // 划伤(P1557)
	// 	Function_CONFIG_QX_NAME_Dirty,			  // 脏污(P0000)
	// 	Function_CONFIG_QX_NAME_qipao,			  // 气泡(P0001)
	// 	Function_CONFIG_QX_NAME_PS,				  // ps(P0002)
	// 	Function_CONFIG_QX_NAME_Weak_Bright_Mura, // 白GAP(P1654)
	// 	Function_CONFIG_QX_NAME_No_Label,		  // 缺POL(P2833)
	// 	Function_CONFIG_QX_NAME_Other,			  // 缺POL(P2833)
	// 	Function_CONFIG_QX_NAME_Chess,			  // Chess 异常
	// 	Function_CONFIG_QX_NAME_127Cell,		  // 白cell
	std::string strqx = "";
	switch (nconfigType)
	{
	case CONFIG_QX_NAME_ok_yisi:
		strqx = Function_CONFIG_QX_NAME_Names[Function_CONFIG_QX_NAME_ok_yisi];
		break;
	case CONFIG_QX_NAME_AD_YX:
		strqx = Function_CONFIG_QX_NAME_Names[Function_CONFIG_QX_NAME_YX];
		break;
	case CONFIG_QX_NAME_LackPOL:
		strqx = Function_CONFIG_QX_NAME_Names[Function_CONFIG_QX_NAME_YX];
		break;
	case CONFIG_QX_NAME_Class_AD_YX:
		strqx = Function_CONFIG_QX_NAME_Names[Function_CONFIG_QX_NAME_YX];
		break;
	case CONFIG_QX_NAME_X_line:
		strqx = Function_CONFIG_QX_NAME_Names[Function_CONFIG_QX_NAME_line];
		break;
	case CONFIG_QX_NAME_Y_line:
		strqx = Function_CONFIG_QX_NAME_Names[Function_CONFIG_QX_NAME_line];
		break;
	case CONFIG_QX_NAME_Fangge:
		strqx = Function_CONFIG_QX_NAME_Names[Function_CONFIG_QX_NAME_line];
		break;
	case CONFIG_QX_NAME_Broken_line:
		strqx = Function_CONFIG_QX_NAME_Names[Function_CONFIG_QX_NAME_line];
		break;
	case CONFIG_QX_NAME_zara:
		strqx = Function_CONFIG_QX_NAME_Names[Function_CONFIG_QX_NAME_zara];
		break;
	case CONFIG_QX_NAME_MTX:
		strqx = Function_CONFIG_QX_NAME_Names[Function_CONFIG_QX_NAME_MTX];
		break;
	case CONFIG_QX_NAME_POL_Cell:
		strqx = Function_CONFIG_QX_NAME_Names[Function_CONFIG_QX_NAME_POL_Cell];
		break;
	case CONFIG_QX_NAME_LD:
		strqx = Function_CONFIG_QX_NAME_Names[Function_CONFIG_QX_NAME_LD];
		break;
	case CONFIG_QX_NAME_AD:
		strqx = Function_CONFIG_QX_NAME_Names[Function_CONFIG_QX_NAME_AD];
		break;
	case CONFIG_QX_NAME_Scratch_L1:
		strqx = Function_CONFIG_QX_NAME_Names[Function_CONFIG_QX_NAME_Scratch];
		break;
	case CONFIG_QX_NAME_Scratch_L2:
		strqx = Function_CONFIG_QX_NAME_Names[Function_CONFIG_QX_NAME_Scratch];
		break;
	case CONFIG_QX_NAME_Dirty_L0:
		strqx = Function_CONFIG_QX_NAME_Names[Function_CONFIG_QX_NAME_Dirty];
		break;
	case CONFIG_QX_NAME_Dirty_L1:
		strqx = Function_CONFIG_QX_NAME_Names[Function_CONFIG_QX_NAME_Dirty];
		break;
	case CONFIG_QX_NAME_Dirty_L2:
		strqx = Function_CONFIG_QX_NAME_Names[Function_CONFIG_QX_NAME_Dirty];
		break;
	case CONFIG_QX_NAME_qipao:
		strqx = Function_CONFIG_QX_NAME_Names[Function_CONFIG_QX_NAME_qipao];
		break;
	case CONFIG_QX_NAME_PS:
		strqx = Function_CONFIG_QX_NAME_Names[Function_CONFIG_QX_NAME_PS];
		break;
	case CONFIG_QX_NAME_Weak_Bright_Mura:
		strqx = Function_CONFIG_QX_NAME_Names[Function_CONFIG_QX_NAME_Weak_Bright_Mura];
		break;
	case CONFIG_QX_NAME_No_Label:
		strqx = Function_CONFIG_QX_NAME_Names[Function_CONFIG_QX_NAME_No_Label];
		break;
	case CONFIG_QX_NAME_Other:
		strqx = Function_CONFIG_QX_NAME_Names[Function_CONFIG_QX_NAME_Other];
		break;
	case CONFIG_QX_NAME_Chess:
		strqx = Function_CONFIG_QX_NAME_Names[Function_CONFIG_QX_NAME_Chess];
		break;
	case CONFIG_QX_NAME_127Cell:
		strqx = Function_CONFIG_QX_NAME_Names[Function_CONFIG_QX_NAME_127Cell];
		break;
	case CONFIG_QX_NAME_white_Cell:
		strqx = Function_CONFIG_QX_NAME_Names[Function_CONFIG_QX_NAME_Cell];
		break;
	case CONFIG_QX_NAME_black_Cell:
		strqx = Function_CONFIG_QX_NAME_Names[Function_CONFIG_QX_NAME_Cell];
		break;
		break;
	default:
		break;
	}
	return strqx;
}
bool ImgCheckAnalysisy::JudgeQXAnalysis(int nqx_configType, std::shared_ptr<DetLog> pQxlog)
{
	bool re = false;
	std::string qx_name = CONFIG_QX_NAME_Names[nqx_configType];
	std::string det_qx = ConfigTypeToWebDetType(nqx_configType);
	for (int i = 0; i < m_pFuntion->function.f_BaseDet.DetQXList.size(); i++)
	{
		std::string strqx = m_pFuntion->function.f_BaseDet.DetQXList.at(i);
		if (det_qx == strqx)
		{
			re = true;
			break;
		}
	}

	pQxlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "Judge QX ", "det qx %s  -> Funtion qx %s  open  = %s ", qx_name.c_str(), det_qx.c_str(), BOOL_TO_STR(re));

	return re;
}