feat 完善黑白点过滤

AlgorithmModule/include/ImageResultJudge.h

@@ -107,10 +107,15 @@ public:
     int UpdateConfig(std::string strcameraName);
     int DrawResult(std::shared_ptr<ImageAllResult> pImageResult);
 
-    // 盲失联合判断：主通道(ms_main_channel)检出的盲失(Other)若在过滤通道(ms_filter_channels)同位置存在缺陷，
+    // 盲失联合判断：主通道(ms_main_channel)检出的盲失(Other)若在过滤通道(ms_filter_channels)同位置存在盲失，
     // 则不算盲失(撤销NG)。同位置判断参考暗点联合分析：双方按 ms_expand 扩张后计算 IOU, 大于 ms_iou 认为同位置
     int FilterMsBlindNG(std::shared_ptr<CameraResult> pCheck_Result);
 
+    // cell黑白点联合判断：主通道(cellbw_main_channel)检出的cell黑白点在过滤通道(cellbw_filter_channels)
+    // 同位置存在cell黑白点(白点/黑点均算)时不算cell黑白点(撤销NG)
+    // 同位置判断参考暗点联合分析：双方按 cellbw_expand 扩张后计算 IOU, 大于 cellbw_iou 认为同位置
+    int FilterCellBwNG(std::shared_ptr<CameraResult> pCheck_Result);
+
 private:
     // 获取 缺陷在参数列表的位置
     int GetParamidx();
@@ -142,13 +147,33 @@ private:
     // 撤销单个缺陷的NG结果：恢复为OK，移除对应NG小图并回退计数
     int UndoNGResult(std::shared_ptr<ImageAllResult> pImageResult, int qxidx, QX_ERROR_INFO_ *QX_info);
 
-    // 判断盲失(产品坐标系ROI)在配置的过滤通道是否存在同位置缺陷(双方按 expand 扩张后计算IOU)
+    // 跨通道同位置判断：当前缺陷(产品坐标系ROI)在过滤通道是否存在指定类型的同位置缺陷(双方按 expand 扩张后计算IOU)
+    bool IsOverlapQxInFilterChannels(const std::vector<std::shared_ptr<ImageAllResult>> &imgResults,
+                                     const std::string &cur_channel_name,
+                                     const std::vector<std::string> &filter_channels,
+                                     const std::vector<int> &match_qx_types,
+                                     const cv::Rect &qx_product_roi,
+                                     int roi_expand, float iou_threshold,
+                                     const std::string &strTag,
+                                     std::shared_ptr<DetLog> plog);
+
+    // 判断盲失(产品坐标系ROI)在配置的过滤通道是否存在同位置盲失缺陷(双方按 expand 扩张后计算IOU)
     bool IsOverlapQxInMsFilterChannel(const std::vector<std::shared_ptr<ImageAllResult>> &imgResults,
                                       const std::string &cur_channel_name,
                                       const cv::Rect &qx_product_roi,
                                       int roi_expand, float iou_threshold,
                                       std::shared_ptr<DetLog> plog);
 
+    // 跨通道联合判断(通用)：主通道中指定类型的NG缺陷，若在过滤通道同位置存在指定类型的缺陷，则撤销该NG
+    int FilterCrossChannelNG(std::shared_ptr<CameraResult> pCheck_Result,
+                             const std::vector<std::string> &main_channels,
+                             const std::vector<std::string> &filter_channels,
+                             const std::vector<int> &main_qx_types,
+                             const std::vector<int> &match_qx_types,
+                             int roi_expand, float iou_threshold,
+                             const std::string &strTag,
+                             const std::string &strReason);
+
     // 关联过滤源过滤：撤销与关联通道过滤源缺陷重叠的暗点NG结果(含单图判定的单点NG)
     int FilterCorrelatedDirtyNG(std::shared_ptr<ImageAllResult> pImageResult);
 

AlgorithmModule/src/CameraCheckAnalysisy.cpp

@@ -351,6 +351,16 @@ int CameraCheckAnalysisy::ResultParamJudge()
 		}
 	}
 
+	// cell黑白点联合判断：主通道(cellbw_main_channel)检出的cell黑白点若在过滤通道(cellbw_filter_channels)同位置
+	// 存在cell黑白点(白点/黑点均算)，则不算cell黑白点(撤销NG)
+	{
+		int nCellBwFilterNum = m_imageResultJudge.FilterCellBwNG(m_pCheck_Result);
+		if (nCellBwFilterNum > 0)
+		{
+			m_pdetlog->AddCheckstr(PrintLevel_1, "ResultParamJudge", "cell黑白点联合判断: 过滤通道同位置存在cell黑白点, 过滤NG %d 个", nCellBwFilterNum);
+		}
+	}
+
 	m_pQX_Merge_Analysis->setSendStatus(m_strcameraName, QX_Merge_Analysis::RUN_STATUS_READY);
 	m_pdetlog->AddCheckstr(PrintLevel_1, "ResultParamJudge", "===============QX_Merge_Analysis===start  %s", CheckUtil::getCurTimeHMS().c_str());
 

AlgorithmModule/src/ImageResultJudge.cpp

@@ -1145,6 +1145,247 @@ int ImageResultJudge::FilterMsBlindNG(std::shared_ptr<CameraResult> pCheck_Resul
 	return nFilterNum;
 }
 
+/**
+ * @brief 跨通道同位置判断：判断当前缺陷(产品坐标系ROI)在过滤通道是否存在指定类型的同位置缺陷
+ *        同位置判断方式参考暗点联合分析：当前ROI与过滤通道缺陷ROI双方均按 expand 扩张后计算 IOU
+ * @param imgResults 当前相机所有通道的检测结果
+ * @param cur_channel_name 当前缺陷所属通道(主通道)
+ * @param filter_channels 需要比较的过滤通道
+ * @param match_qx_types 过滤通道中参与比较的缺陷类型(CONFIG_QX_NAME_)
+ * @param qx_product_roi 当前缺陷的产品坐标系ROI
+ * @param roi_expand 扩张像素
+ * @param iou_threshold IOU阈值
+ * @param strTag 日志标签
+ * @param plog 日志
+ * @return bool 过滤通道同位置存在指定类型缺陷返回true
+ */
+bool ImageResultJudge::IsOverlapQxInFilterChannels(const std::vector<std::shared_ptr<ImageAllResult>> &imgResults,
+												   const std::string &cur_channel_name,
+												   const std::vector<std::string> &filter_channels,
+												   const std::vector<int> &match_qx_types,
+												   const cv::Rect &qx_product_roi,
+												   int roi_expand, float iou_threshold,
+												   const std::string &strTag,
+												   std::shared_ptr<DetLog> plog)
+{
+	// 防御：ROI非法/未配置过滤通道/未指定匹配类型时不判断，避免无效计算与除零
+	if (qx_product_roi.width <= 0 || qx_product_roi.height <= 0)
+	{
+		return false;
+	}
+	if (filter_channels.empty() || match_qx_types.empty())
+	{
+		return false;
+	}
+	if (m_pAnalysisyConfig == nullptr)
+	{
+		return false;
+	}
+	float fproduct_offx_mm = m_pAnalysisyConfig->commonCheckConfig.baseConfig.fProduct_Off_X_mm;
+	int fproduct_offx_piexl = int(fproduct_offx_mm / m_fImgage_Scale_X);
+
+	// 与暗点联合分析保持一致：双方均按 expand 扩张后再计算 IOU
+	cv::Rect roi_expanded(qx_product_roi.x - roi_expand, qx_product_roi.y - roi_expand,
+						  qx_product_roi.width + roi_expand * 2, qx_product_roi.height + roi_expand * 2);
+
+	for (int imgidx = 0; imgidx < (int)imgResults.size(); imgidx++)
+	{
+		std::shared_ptr<ImageAllResult> pFilterImage = imgResults.at(imgidx);
+		if (pFilterImage == nullptr)
+		{
+			continue;
+		}
+		// 只与配置的过滤通道比较；当前通道不参与，避免自身重叠导致误过滤
+		if (pFilterImage->strChannel == cur_channel_name)
+		{
+			continue;
+		}
+		if (std::find(filter_channels.begin(), filter_channels.end(), pFilterImage->strChannel) == filter_channels.end())
+		{
+			continue;
+		}
+		std::shared_ptr<One_Image_CheckResult_> pFilterDetResult = pFilterImage->pDetResult;
+		if (pFilterDetResult == nullptr || pFilterDetResult->pQx_ErrorList == nullptr)
+		{
+			continue;
+		}
+
+		// 只统计过滤通道内指定类型的缺陷，与具体判定结果无关
+		for (int j = 0; j < (int)pFilterDetResult->pQx_ErrorList->size(); j++)
+		{
+			const QX_ERROR_INFO_ &filter_qx = pFilterDetResult->pQx_ErrorList->at(j);
+			if (std::find(match_qx_types.begin(), match_qx_types.end(), filter_qx.nconfig_qx_type) == match_qx_types.end())
+			{
+				continue;
+			}
+			cv::Rect filter_roi = filter_qx.roi;
+			filter_roi.x += fproduct_offx_piexl;
+			cv::Rect filter_expanded(filter_roi.x - roi_expand, filter_roi.y - roi_expand,
+									 filter_roi.width + roi_expand * 2, filter_roi.height + roi_expand * 2);
+
+			float fiou = CheckUtil::CalIoU(roi_expanded, filter_expanded);
+			if (plog)
+			{
+				plog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, strTag,
+								  "main channel %s roi %s <-> filter channel %s qx %d roi %s expand %d iou %f",
+								  cur_channel_name.c_str(), CheckUtil::GetRectString(qx_product_roi).c_str(),
+								  pFilterImage->strChannel.c_str(), j,
+								  CheckUtil::GetRectString(filter_roi).c_str(), roi_expand, fiou);
+			}
+			// IOU 为 NaN(ROI 非法导致的除零)时比较结果为 false，不会误过滤
+			if (fiou > iou_threshold)
+			{
+				if (plog)
+				{
+					plog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, strTag,
+									  "main channel %s roi %s overlap filter channel %s qx %d roi %s expand %d iou %f > %f",
+									  cur_channel_name.c_str(), CheckUtil::GetRectString(qx_product_roi).c_str(),
+									  pFilterImage->strChannel.c_str(), j,
+									  CheckUtil::GetRectString(filter_roi).c_str(), roi_expand, fiou, iou_threshold);
+				}
+				return true;
+			}
+		}
+	}
+
+	return false;
+}
+
+/**
+ * @brief 跨通道联合判断(通用)：主通道中指定类型的NG缺陷，若在过滤通道同位置存在指定类型的缺陷，则撤销该NG
+ *        同位置判断方式参考暗点联合分析：双方按 expand 扩张后计算 IOU, 大于 iou_threshold 认为同位置
+ * @param pCheck_Result 当前相机检测结果(包含该相机所有通道的检测结果)
+ * @param main_channels 主通道
+ * @param filter_channels 过滤通道
+ * @param main_qx_types 参与判断的主通道缺陷类型(CONFIG_QX_NAME_)
+ * @param match_qx_types 过滤通道中参与比较的缺陷类型(CONFIG_QX_NAME_)
+ * @param roi_expand 扩张像素
+ * @param iou_threshold IOU阈值
+ * @param strTag 日志标签
+ * @param strReason 过滤原因(日志)
+ * @return int 被过滤的NG个数
+ */
+int ImageResultJudge::FilterCrossChannelNG(std::shared_ptr<CameraResult> pCheck_Result,
+										   const std::vector<std::string> &main_channels,
+										   const std::vector<std::string> &filter_channels,
+										   const std::vector<int> &main_qx_types,
+										   const std::vector<int> &match_qx_types,
+										   int roi_expand, float iou_threshold,
+										   const std::string &strTag,
+										   const std::string &strReason)
+{
+	if (pCheck_Result == nullptr || m_pAnalysisyConfig == nullptr)
+	{
+		return 0;
+	}
+	// 未配置主通道/过滤通道/判断类型时不需要判断
+	if (main_channels.empty() || filter_channels.empty() || main_qx_types.empty())
+	{
+		return 0;
+	}
+	float fproduct_offx_mm = m_pAnalysisyConfig->commonCheckConfig.baseConfig.fProduct_Off_X_mm;
+	int fproduct_offx_piexl = int(fproduct_offx_mm / m_fImgage_Scale_X);
+
+	int nFilterNum = 0;
+	for (int imgidx = 0; imgidx < (int)pCheck_Result->ImageALLDetResultList.size(); imgidx++)
+	{
+		std::shared_ptr<ImageAllResult> pImageResult = pCheck_Result->ImageALLDetResultList.at(imgidx);
+		if (pImageResult == nullptr)
+		{
+			continue;
+		}
+		// 只处理配置的主通道
+		if (std::find(main_channels.begin(), main_channels.end(), pImageResult->strChannel) == main_channels.end())
+		{
+			continue;
+		}
+		std::shared_ptr<One_Image_CheckResult_> pDetResult = pImageResult->pDetResult; // 检测结果
+		if (pDetResult == nullptr || pDetResult->pQx_ErrorList == nullptr || pImageResult->result == nullptr)
+		{
+			continue;
+		}
+		std::shared_ptr<DetLog> pImageLog = pImageResult->detlog;
+
+		for (int qxidx = 0; qxidx < (int)pDetResult->pQx_ErrorList->size(); qxidx++)
+		{
+			QX_ERROR_INFO_ *QX_info = &pDetResult->pQx_ErrorList->at(qxidx);
+			// 只处理指定类型的 NG 结果(YS 不降级)
+			if (QX_info->result != QX_RESULT_TYPE_NG)
+			{
+				continue;
+			}
+			if (std::find(main_qx_types.begin(), main_qx_types.end(), QX_info->nconfig_qx_type) == main_qx_types.end())
+			{
+				continue;
+			}
+
+			cv::Rect product_roi = QX_info->roi;
+			product_roi.x += fproduct_offx_piexl;
+			// 过滤通道同位置不存在匹配类型的缺陷时，保留该NG
+			if (!IsOverlapQxInFilterChannels(pCheck_Result->ImageALLDetResultList,
+											 pImageResult->strChannel,
+											 filter_channels, match_qx_types,
+											 product_roi,
+											 roi_expand, iou_threshold,
+											 strTag, pImageLog))
+			{
+				continue;
+			}
+
+			// 撤销NG结果
+			UndoNGResult(pImageResult, qxidx, QX_info);
+			nFilterNum++;
+
+			if (pImageLog)
+			{
+				pImageLog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, strTag,
+									   "img %s cam %s blob %d qx %s roi %s : %s",
+									   pImageResult->strChannel.c_str(), pImageResult->cameraBaseResult->strCameraName.c_str(),
+									   qxidx, QX_info->qx_name.c_str(), CheckUtil::GetRectString(product_roi).c_str(),
+									   strReason.c_str());
+			}
+			if (m_pQX_Merge_Analysis != nullptr && m_pQX_Merge_Analysis->m_pMergedetlog)
+			{
+				m_pQX_Merge_Analysis->m_pMergedetlog->AddCheckstr(PrintLevel_1, 3, strTag,
+																  "img %s cam %s blob %d qx %s roi %s : %s",
+																  pImageResult->strChannel.c_str(), pImageResult->cameraBaseResult->strCameraName.c_str(),
+																  qxidx, QX_info->qx_name.c_str(), CheckUtil::GetRectString(product_roi).c_str(),
+																  strReason.c_str());
+			}
+		}
+	}
+
+	return nFilterNum;
+}
+
+/**
+ * @brief cell黑白点联合判断：主通道(cellbw_main_channel)检出的cell黑白点在过滤通道(cellbw_filter_channels)
+ *        同位置存在cell黑白点(白点/黑点均算)时不算cell黑白点(撤销NG)
+ *        同位置判断方式参考暗点联合分析：双方按 cellbw_expand 扩张后计算 IOU, 大于 cellbw_iou 认为同位置
+ * @param pCheck_Result 当前相机检测结果(包含该相机所有通道的检测结果)
+ * @return int 被过滤的cell黑白点NG个数
+ */
+int ImageResultJudge::FilterCellBwNG(std::shared_ptr<CameraResult> pCheck_Result)
+{
+	if (m_pbaseCheckFunction == nullptr)
+	{
+		return 0;
+	}
+	Base_Function_CellBW_Check *pCellBwParam = &m_pbaseCheckFunction->cellbw_check;
+	// 未开启cell黑白点分析时不需要判断(主通道/过滤通道为空时由通用逻辑直接返回)
+	if (!pCellBwParam->bOpen)
+	{
+		return 0;
+	}
+	// 白点/黑点通用：主通道与过滤通道均按 cell 黑白点匹配(白↔白、黑↔黑、白↔黑都算)
+	const std::vector<int> qxTypes = {CONFIG_QX_NAME_white_Cell, CONFIG_QX_NAME_black_Cell};
+	return FilterCrossChannelNG(pCheck_Result,
+								pCellBwParam->cellbw_main_channel, pCellBwParam->cellbw_filter_channels,
+								qxTypes, qxTypes,
+								(int)(round)(pCellBwParam->CellBW_Expand), pCellBwParam->CellBW_IOU,
+								"CellBw", "过滤通道同位置存在cell黑白点, 不算cell黑白点");
+}
+
 int ImageResultJudge::MergeResult(std::shared_ptr<ImageAllResult> pImageResult, QX_Analysis_Result_List *ptemre)
 {