update 标签检测分块(v1.3.3)

AlgorithmModule/src/ImgCheckAnalysisy.cpp

@@ -170,7 +170,7 @@ int ImgCheckAnalysisy::GetStatus()
 
 std::string ImgCheckAnalysisy::GetVersion()
 {
-	return std::string("BOE_1.3.2_" + std::string(__DATE__) + "_" + std::string(__TIME__));
+	return std::string("BOE_1.3.3_" + std::string(__DATE__) + "_" + std::string(__TIME__));
 }
 
 std::string ImgCheckAnalysisy::GetErrorInfo()
@@ -2193,79 +2193,165 @@ int ImgCheckAnalysisy::AI_Detect_BQ()
 	m_pImageAllResult->bq_DetAIResult = std::make_shared<ImageAllResult::Image_AI_Det_Result>();
 	std::shared_ptr<ImageAllResult::Image_AI_Det_Result> pDetAIResult = m_pImageAllResult->bq_DetAIResult;
 
-	// 使用与主检测相同的AI模型（后续更改为BQ AI模型）
+	// 使用BQ AI
 	std::shared_ptr<AIModel_Base> pAI_Model = AI_Factory->AI_defect_Tag;
 
 	int AIInputImg_width = pAI_Model->input_0.width;
 	int AIInputImg_height = pAI_Model->input_0.height;
-	cv::Size modelInputSize(AIInputImg_width, AIInputImg_height);
+
+	int AIOutputImg_width = pAI_Model->output_0.width;
+	int AIOutputImg_height = pAI_Model->output_0.height;
+
+	// 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;
+	}
+
+	cv::Size src_sz;
+	src_sz.width = AIInputImg_width;
+	src_sz.height = AIInputImg_height;
 
 	// 创建全图大小的AI mask（与主检测detImg同尺寸）
 	cv::Mat AI_detImage = m_pImageAllResult->AI_detImg;
 	pDetAIResult->AI_MaskImg = cv::Mat::zeros(AI_detImage.size(), CV_8UC1);
+	cv::Mat AIresultMask = pDetAIResult->AI_MaskImg;
 
-	// 先提交所有BQ AI推理任务（仿照AI_Detect_QX的提交-收集模式）
+	// 为每个BQ区域生成小ROI列表，仿照AI_Detect_QX的裁剪小块方式
-	int submitted = 0;
+	std::vector<cv::Rect> BQ_SmallRoiList;
-	int completed = 0;
+	for (int i = 0; i < bqNum; i++)
-	while (completed < bqNum)
-	{
-		// 提交任务（限制并发数不超过2，避免占用过多资源）
-		if (submitted < bqNum && runner->GetProcessingCount() < 2)
 	{
-			cv::Rect bqRoi = m_pImageAllResult->cameraBaseResult->pBQ_Result->pBQ_expandedRoiList.at(submitted);
+		cv::Rect bqRoi = m_pImageAllResult->cameraBaseResult->pBQ_Result->pBQ_expandedRoiList.at(i);
 		cv::Rect validRoi = bqRoi & cv::Rect(0, 0, AI_detImage.cols, AI_detImage.rows);
-			cv::Mat bqCrop;
+		if (validRoi.width <= 0 || validRoi.height <= 0) continue;
-			if (validRoi.width > 0 && validRoi.height > 0)
+
+		// 如果BQ区域大于等于模型输入尺寸，切分成小块
+		if (validRoi.width >= AIInputImg_width && validRoi.height >= AIInputImg_height)
+		{
+			std::vector<cv::Rect> smallList;
+			int re = CheckUtil::cutSmallImg(AI_detImage, smallList, validRoi, AIInputImg_width, AIInputImg_height, 0, 0);
+			if (re == 0)
+			{
+				for (const auto& roi : smallList)
+				{
+					BQ_SmallRoiList.push_back(roi);
+				}
+			}
+		}
+		else
+		{
+			// BQ区域小于模型输入尺寸，以BQ区域中心创建模型输入大小的ROI
+			int cx = validRoi.x + validRoi.width / 2;
+			int cy = validRoi.y + validRoi.height / 2;
+			cv::Rect newRoi;
+			newRoi.x = cx - AIInputImg_width / 2;
+			newRoi.y = cy - AIInputImg_height / 2;
+			newRoi.width = AIInputImg_width;
+			newRoi.height = AIInputImg_height;
+			// 裁剪到图像边界
+			if (newRoi.x < 0) newRoi.x = 0;
+			if (newRoi.y < 0) newRoi.y = 0;
+			if (newRoi.x + newRoi.width > AI_detImage.cols) newRoi.x = AI_detImage.cols - newRoi.width;
+			if (newRoi.y + newRoi.height > AI_detImage.rows) newRoi.y = AI_detImage.rows - newRoi.height;
+			if (newRoi.x < 0) { newRoi.x = 0; newRoi.width = AI_detImage.cols; }
+			if (newRoi.y < 0) { newRoi.y = 0; newRoi.height = AI_detImage.rows; }
+			BQ_SmallRoiList.push_back(newRoi);
+		}
+	}
+
+	const int totalTasks = BQ_SmallRoiList.size();
+	if (totalTasks <= 0)
+	{
+		m_pdetlog->AddCheckstr(PrintLevel_2, strBaseLog, "no valid small roi for BQ");
+		return 0;
+	}
+
+	m_pdetlog->AddCheckstr(PrintLevel_2, strBaseLog, "BQ small roi num = %d", totalTasks);
+
+	// 调试存图：原图 + BQ小ROI框
+	if (DetImgInfo_shareP->bDebugsaveImg)
+	{
+		cv::Mat debugImg;
+		if (AI_detImage.channels() == 1)
+		{
+			cv::cvtColor(AI_detImage, debugImg, cv::COLOR_GRAY2BGR);
+		}
+		else
 		{
-				bqCrop = AI_detImage(validRoi).clone();
+			debugImg = AI_detImage.clone();
 		}
-			if (!bqCrop.empty())
+		for (size_t i = 0; i < BQ_SmallRoiList.size(); i++)
 		{
-				cv::Mat resizedCrop;
+			cv::rectangle(debugImg, BQ_SmallRoiList.at(i), cv::Scalar(0, 0, 255), 2);
-				cv::resize(bqCrop, resizedCrop, modelInputSize);
+		}
+		cv::imwrite(m_strCurDetCamChannel + "_BQ_original_with_rois.png", debugImg);
+	}
+
+	int submitted = 0;
+	int completed = 0;
+	long t2 = CheckUtil::getcurTime();
 
+	while (completed < totalTasks)
+	{
+		// 提交任务
+		if (submitted < totalTasks && runner->GetProcessingCount() < 10)
+		{
 			std::shared_ptr<AIMulThreadRunBase::AITask> task = std::make_shared<AIMulThreadRunBase::AITask>();
 			task->id = submitted;
-				task->roi = cv::Rect(0, 0, validRoi.width, validRoi.height);
+			task->roi = BQ_SmallRoiList.at(submitted);
-				task->input = resizedCrop;
+			task->input = AI_detImage(task->roi).clone();
 			task->output = std::make_shared<cv::Mat>();
 			task->engine = pAI_Model;
 
-				runner->SubmitTask(task);
+			// 调试存图：保存每个小块
+			if (DetImgInfo_shareP->bDebugsaveImg)
+			{
+				cv::imwrite(m_strCurDetCamChannel + "_BQ_crop_" + std::to_string(submitted) + ".png", task->input);
 			}
+
+			runner->SubmitTask(task);
 			submitted++;
 		}
 
-		// 收集已完成的结果
+		// 收集结果
 		std::shared_ptr<AIMulThreadRunBase::AITask> result;
 		if (runner->PopResult(result))
 		{
-			int idx = result->id;
+			cv::Mat &outimg = *(result->output);
-			if (idx >= 0 && idx < bqNum)
+			if (!outimg.empty())
 			{
-				cv::Rect bqRoi = m_pImageAllResult->cameraBaseResult->pBQ_Result->pBQ_expandedRoiList.at(idx);
+				// 调试存图：保存模型原始输出mask
-				cv::Rect validRoi = bqRoi & cv::Rect(0, 0, AI_detImage.cols, AI_detImage.rows);
+				if (DetImgInfo_shareP->bDebugsaveImg)
+				{
+					cv::imwrite(m_strCurDetCamChannel + "_BQ_outmask_" + std::to_string(result->id) + ".png", outimg);
+				}
 
-				if (validRoi.width > 0 && validRoi.height > 0)
+				cv::Mat AIresult;
+				if (bResizeToSrc)
 				{
-					cv::Mat &outMask = *(result->output);
+					cv::resize(outimg, AIresult, src_sz, 0, 0, 0);
-					if (!outMask.empty())
+				}
+				else
 				{
-						// 将AI输出mask resize回BQ裁剪图原始尺寸
+					AIresult = outimg;
-						cv::Mat resizedMask;
+				}
-						cv::resize(outMask, resizedMask, cv::Size(bqRoi.width, bqRoi.height));
 
-						// 将BQ的mask结果放到全图mask的对应位置
+				cv::Rect srcsize_roi = result->roi;
-						resizedMask.copyTo(pDetAIResult->AI_MaskImg(validRoi), resizedMask);
+				AIresult.copyTo(AIresultMask(srcsize_roi), AIresult);
+
+				// 调试存图：保存resize后的mask
+				if (DetImgInfo_shareP->bDebugsaveImg && bResizeToSrc)
+				{
+					cv::imwrite(m_strCurDetCamChannel + "_BQ_mask_resized_" + std::to_string(result->id) + ".png", AIresult);
+				}
 
 				m_pdetlog->AddCheckstr(PrintLevel_2, strBaseLog, "BQ[%d] AI done, roi=[%d,%d,%d,%d]",
-											   idx, validRoi.x, validRoi.y, validRoi.width, validRoi.height);
+									   result->id, srcsize_roi.x, srcsize_roi.y, srcsize_roi.width, srcsize_roi.height);
 			}
 			else
 			{
-						m_pdetlog->AddCheckstr(PrintLevel_2, strBaseLog, "BQ[%d] AI output empty", idx);
+				m_pdetlog->AddCheckstr(PrintLevel_2, strBaseLog, "BQ[%d] AI output empty", result->id);
-					}
-				}
 			}
 			completed++;
 		}
@@ -2276,7 +2362,8 @@ int ImgCheckAnalysisy::AI_Detect_BQ()
 	}
 
 	long te = CheckUtil::getcurTime();
-	m_pdetlog->AddCheckstr(PrintLevel_1, strBaseLog, "============= End, time=%ld ms", te - ts);
+	float mean_AI = (te - t2) / totalTasks;
+	m_pdetlog->AddCheckstr(PrintLevel_1, strBaseLog, "============= End; AI Run Time: sum %ld pre %ld Run %ld mean One Small Img %f", te - ts, t2 - ts, te - t2, mean_AI);
 
 	// 调试存图
 	if (DetImgInfo_shareP->bDebugsaveImg)