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BOE_FOG_DETECT
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增加弱线检测 xwj

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dev_lsy
xiewenji 3 weeks ago
parent 01247bccb9
commit 68f0d4aa45
8 changed files with 621 additions and 128 deletions
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2
AIEngineModule/include_base/AI_Factory.h
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@ -192,6 +192,8 @@ public:
std::shared_ptr<AIModel_Base> AI_defect_MarkLine; // 缺pol检测
std::shared_ptr<AIModel_Base> AI_defect_Edge_QX; // 边缘缺陷检测
std::shared_ptr<AIModel_Base> AI_defect_RLine_512; // 弱线检测模型 512*512
private:
// 模型是否都加载完成了。
bool m_bInitSucc = false;

11
AIEngineModule/src/AI_Factory.cpp
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@ -264,6 +264,17 @@ int AIFactory::InitALLAIModle(GPU_Config gupconfig)
boe_config.inputType = AIModel_Base::Input_CHW;
boe_config.strName = "Edge_QX";
AI_defect_Edge_QX->Init(boe_config);
}
// 弱线检测模型 512*512
if (!AI_defect_RLine_512)
{
AI_defect_RLine_512 = AIModel_Base::GetInstance();
AIModel_Base::AIModelRun_Config boe_config;
boe_config.gpuconfig.copy(gupconfig);
boe_config.strPath = "/home/aidlux/BOE/UseModel_FOG/FOG_L127line.engine";
boe_config.strName = "RLine_512";
boe_config.inputType = AIModel_Base::Input_CHW;
AI_defect_RLine_512->Init(boe_config);
}
m_bInitSucc = true;
return 0;

8
AlgorithmModule/include/ImageAllResult.h
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@ -45,9 +45,9 @@ public:
};
struct Config_Update
{
bool bUpdate = false;
bool wait_DP= false;
bool wait_UP= false;
bool bUpdate = false;
bool wait_DP = false;
bool wait_UP = false;
};
// AI MaskImg 的相关使用的参数信息。
@ -174,6 +174,7 @@ public:
std::shared_ptr<Image_AI_Det_Result> qx_DetAIResult; // BLob 检测要用到的一些 参数 。
std::shared_ptr<Image_AI_Det_Result> cell127_DetAIResult; // 127 cell 检测要用到的一些 参数 。
std::shared_ptr<Image_AI_Det_Result> bq_DetAIResult; // BQ标签检测要用到的一些 参数 。
std::shared_ptr<Image_AI_Det_Result> RLine_512_DetAIResult; // 弱线512模型 检测要用到的一些 参数 。
// 结果图片
cv::Mat resultImg;
@ -205,7 +206,6 @@ public:
Config_Update config_update;
public:
DetStep m_step = DetStep_NotDet;
std::string strBaseInfo = "";

7
AlgorithmModule/include/ImgCheckAnalysisy.hpp
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@ -193,7 +193,8 @@ private:
int GetBlob_QX();
// 获得 127cell blob
int GetBlob_127cell();
// 获得 RLine_512 blob
int GetBlob_RLine_512();
// 获得 BQ标签 blob
int GetBlob_BQ();
@ -220,6 +221,8 @@ private:
int AI_Detect_QX();
// 127cell
int AI_Detect_127Cell();
// 弱线检测-512模型
int AI_Detect_RLine_512();
// 缺陷分类
int AI_QX_Class_Thread();
@ -240,7 +243,7 @@ private:
// 更新 检测区域
int Update_DetRoiList();
// 边缘检测
// 边缘检测
int Edge_Det();
// 临时绘制结果

55
AlgorithmModule/src/ImageResultJudge.cpp
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@ -387,9 +387,9 @@ int ImageResultJudge::ResultJudge(std::shared_ptr<ImageAllResult> pImageResult)
BOOL_TO_STR(flen >= Len), flen, BOOL_TO_ThanLess(flen > Len), Len);
}
if( config_qx_type == CONFIG_QX_NAME_POL_Cell && area_max > 0)
if (config_qx_type == CONFIG_QX_NAME_POL_Cell && area_max > 0)
{
if(detArea > area_max)
if (detArea > area_max)
{
nerrortype = 0;
result = true;
@ -397,7 +397,7 @@ int ImageResultJudge::ResultJudge(std::shared_ptr<ImageAllResult> pImageResult)
bYS_Status = false;
}
pQxLog->AddCheckstr(PrintLevel_4, DET_LOG_LEVEL_3, "PolCell_Area_Max", "%s -> %f %s %f ",
BOOL_TO_STR(detArea > area_max), detArea, BOOL_TO_ThanLess(detArea > area_max), area_max);
BOOL_TO_STR(detArea > area_max), detArea, BOOL_TO_ThanLess(detArea > area_max), area_max);
}
// AD根据配置检测：未配置通道的AD缺陷不判NG
if (config_qx_type == CONFIG_QX_NAME_AD && m_pbaseCheckFunction && ict == ANALYSIS_TYPE_TF &&
@ -453,7 +453,7 @@ int ImageResultJudge::ResultJudge(std::shared_ptr<ImageAllResult> pImageResult)
m_pbaseCheckFunction->ad_check.analysis_s.NG_3s && bpreSucc)
{
bool b3sChannel = false;
if(std::find(m_pbaseCheckFunction->ad_check.analysis_sf.s_sf.begin(), m_pbaseCheckFunction->ad_check.analysis_sf.s_sf.end(), strChannel) != m_pbaseCheckFunction->ad_check.analysis_sf.s_sf.end())
if (std::find(m_pbaseCheckFunction->ad_check.analysis_sf.s_sf.begin(), m_pbaseCheckFunction->ad_check.analysis_sf.s_sf.end(), strChannel) != m_pbaseCheckFunction->ad_check.analysis_sf.s_sf.end())
{
b3sChannel = true;
}
@ -610,7 +610,7 @@ int ImageResultJudge::ResultJudge(std::shared_ptr<ImageAllResult> pImageResult)
// CheckUtil::printROI(CutRoi, "CutRoi");
cv::Size sz = cv::Size(QX_SAMLLIMG_WIDTH, QX_SAMLLIMG_HEIGHT);
#ifdef SAVE_RESIMG
#ifdef SAVE_RESIMG
if (pImageResult->detImg.channels() == 1)
{
cv::cvtColor(pImageResult->detImg(CutRoi), tem.srcImg, cv::COLOR_GRAY2BGR);
@ -620,7 +620,7 @@ int ImageResultJudge::ResultJudge(std::shared_ptr<ImageAllResult> pImageResult)
tem.srcImg = pImageResult->detImg(CutRoi).clone();
}
cv::resize(tem.srcImg, tem.resizeImg, sz);
#endif
#endif
int nqx_type = ConfigTypeToResultType(config_qx_type);
tem.type = nqx_type;
@ -665,9 +665,9 @@ int ImageResultJudge::ResultJudge(std::shared_ptr<ImageAllResult> pImageResult)
m_CheckResult_shareP->nresult = nqx_type;
}
#ifdef SAVE_RESIMG
#ifdef SAVE_RESIMG
GetAIDetImg(pImageResult, pCenter, tem.AI_in_Img, tem.AI_out_img);
#endif
#endif
m_CheckResult_shareP->qxImageResult.push_back(tem);
}
else
@ -678,15 +678,14 @@ int ImageResultJudge::ResultJudge(std::shared_ptr<ImageAllResult> pImageResult)
m_CheckResult_shareP->nYS_result = nqx_type;
}
#ifdef SAVE_RESIMG
#ifdef SAVE_RESIMG
GetAIDetImg(pImageResult, pCenter, tem.AI_in_Img, tem.AI_out_img);
#endif
#endif
m_CheckResult_shareP->YS_ImageResult.push_back(tem);
}
pQxLog->AddCheckstr(PrintLevel_4, DET_LOG_LEVEL_3, " result ", " name %s ---code %s", tem.strTypeName.c_str(), tem.qx_Code.c_str());
pQxLog->AddCheckstr(PrintLevel_4, DET_LOG_LEVEL_3, " result ", " name %s ---code %s", tem.strTypeName.c_str(), tem.qx_Code.c_str());
}
// 对于大面积 的zara和 异显NG ，可以不接着分析后续的数据了。应为后续估计有很多错误类别。
@ -909,9 +908,9 @@ int ImageResultJudge::FilterCorrelatedDirtyNG(std::shared_ptr<ImageAllResult> pI
if (m_pQX_Merge_Analysis->m_pMergedetlog)
{
m_pQX_Merge_Analysis->m_pMergedetlog->AddCheckstr(PrintLevel_1, 3, "DirtyCorrelatedFilter",
"img %s cam %s blob %d qx %s roi %s : 关联通道存在重叠的过滤源缺陷, 过滤该暗点NG",
pImageResult->strChannel.c_str(), pImageResult->cameraBaseResult->strCameraName.c_str(),
qxidx, QX_info->qx_name.c_str(), CheckUtil::GetRectString(product_roi).c_str());
"img %s cam %s blob %d qx %s roi %s : 关联通道存在重叠的过滤源缺陷, 过滤该暗点NG",
pImageResult->strChannel.c_str(), pImageResult->cameraBaseResult->strCameraName.c_str(),
qxidx, QX_info->qx_name.c_str(), CheckUtil::GetRectString(product_roi).c_str());
}
}
@ -988,7 +987,7 @@ int ImageResultJudge::MergeResult(std::shared_ptr<ImageAllResult> pImageResult,
cv::Rect CutRoi = GetCutRoi(roi, pImageResult->detImg);
cv::Size sz = cv::Size(QX_SAMLLIMG_WIDTH, QX_SAMLLIMG_HEIGHT);
#ifdef SAVE_RESIMG
#ifdef SAVE_RESIMG
if (pImageResult->detImg.channels() == 1)
{
cv::cvtColor(pImageResult->detImg(CutRoi), tem.srcImg, cv::COLOR_GRAY2BGR);
@ -998,7 +997,7 @@ int ImageResultJudge::MergeResult(std::shared_ptr<ImageAllResult> pImageResult,
tem.srcImg = pImageResult->detImg(CutRoi).clone();
}
cv::resize(tem.srcImg, tem.resizeImg, sz);
#endif
#endif
int nerrortype = 1;
int checkFlage = ANALYSIS_TYPE_TF;
@ -1059,9 +1058,9 @@ int ImageResultJudge::MergeResult(std::shared_ptr<ImageAllResult> pImageResult,
{
m_CheckResult_shareP->nresult = nqx_type;
}
#ifdef SAVE_RESIMG
#ifdef SAVE_RESIMG
GetAIDetImg(pImageResult, pCenter, tem.AI_in_Img, tem.AI_out_img);
#endif
#endif
m_CheckResult_shareP->qxImageResult.push_back(tem);
}
}
@ -1433,24 +1432,24 @@ int ImageResultJudge::ConfigTypeToResultType(int nconfigType)
{
bool bdesc = false;
int resultError_type = ERROR_TYPE_OK;
if(nconfigType < CONFIG_QX_NAME_Names.size())
if (nconfigType < CONFIG_QX_NAME_Names.size())
{
string cqn = CONFIG_QX_NAME_Names[nconfigType];
for(int i = 0; i < m_FlawCodeList.size(); i++)
for (int i = 0; i < m_FlawCodeList.size(); i++)
{
for(int j = 0; j < m_FlawCodeList.at(i).config_flaw_name.size(); j++)
for (int j = 0; j < m_FlawCodeList.at(i).config_flaw_name.size(); j++)
{
if(cqn == m_FlawCodeList.at(i).config_flaw_name[j])
if (cqn == m_FlawCodeList.at(i).config_flaw_name[j])
{
resultError_type = i;
bdesc = true;
break;
}
}
}
}
}
// 如果描述没有配置，用默认值
if(!bdesc)
if (!bdesc)
{
switch (nconfigType)
{
@ -1535,6 +1534,12 @@ int ImageResultJudge::ConfigTypeToResultType(int nconfigType)
case CONFIG_QX_NAME_LackPOL:
resultError_type = ERROR_TYPE_LackPol;
break;
case CONFIG_QX_NAME_RLine_X:
resultError_type = ERROR_TYPE_Line_X;
break;
case CONFIG_QX_NAME_RLine_Y:
resultError_type = ERROR_TYPE_Line_Y;
break;
default:
break;
}

526
AlgorithmModule/src/ImgCheckAnalysisy.cpp
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@ -751,6 +751,10 @@ int ImgCheckAnalysisy::CalBlob_Other()
{
pDetAIResult = m_pImageAllResult->cell127_DetAIResult;
}
else if (config_qx_type == CONFIG_QX_NAME_RLine_X || config_qx_type == CONFIG_QX_NAME_RLine_Y)
{
pDetAIResult = m_pImageAllResult->RLine_512_DetAIResult;
}
cv::Mat maskImg = pDetAIResult->AI_MaskImg;
if (maskImg.empty())
@ -1092,6 +1096,10 @@ int ImgCheckAnalysisy::CalBLobMean_GrayDis()
{
pDetAIResult = m_pImageAllResult->cell127_DetAIResult;
}
else if (config_qx_type == CONFIG_QX_NAME_RLine_X || config_qx_type == CONFIG_QX_NAME_RLine_Y)
{
pDetAIResult = m_pImageAllResult->RLine_512_DetAIResult;
}
cv::Mat maskImg = pDetAIResult->AI_MaskImg;
if (maskImg.empty())
@ -1726,6 +1734,7 @@ int ImgCheckAnalysisy::GetALLBlob()
long t4 = CheckUtil::getcurTime();
re = GetBlob_127cell();
long t5 = CheckUtil::getcurTime();
re = GetBlob_RLine_512();
re = GetBlob_BQ();
if (blobs.blobCount > 1000)
@ -2187,6 +2196,135 @@ int ImgCheckAnalysisy::GetBlob_127cell()
return 0;
}
int ImgCheckAnalysisy::GetBlob_RLine_512()
{
std::string strBaseLog = "GetBlob_RLine_512";
if (m_pFuntion &&
m_pFuntion->function.f_RLineDet.bOpen &&
m_pFuntion->function.f_RLineDet.bOpen_512)
{
}
else
{ // 未开启检测
return 0;
}
std::shared_ptr<ImageAllResult::Image_AI_Det_Result> pDetAIResult = m_pImageAllResult->RLine_512_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_RLine_X;
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 (roi.width > roi.height)
{
//m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, strBaseLog, "CONFIG_QX_NAME_RLine_X %d %d --%s \n",roi.width , roi.height,CONFIG_QX_NAME_Names[CONFIG_QX_NAME_RLine_X].c_str());
blobs_all.blobTab[i].ErrType = CONFIG_QX_NAME_RLine_X;
}
else
{
//m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, strBaseLog, "CONFIG_QX_NAME_RLine_Y %d %d -- %s\n",roi.width , roi.height,CONFIG_QX_NAME_Names[CONFIG_QX_NAME_RLine_Y].c_str());
blobs_all.blobTab[i].ErrType = CONFIG_QX_NAME_RLine_Y;
}
}
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 + "_RLine_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;
}
// BQAI检测
int ImgCheckAnalysisy::AI_Detect_BQ()
{
@ -2211,7 +2349,7 @@ int ImgCheckAnalysisy::AI_Detect_BQ()
m_pdetlog->AddCheckstr(PrintLevel_1, strBaseLog, "============= Start, BQ num = %d", bqNum);
long ts = CheckUtil::getcurTime();
std::string BQ_save_path = "/home/aidlux/BOE/FOG/BQ_AI_Det/"+ m_pImageAllResult->productBaseResult->strproductName + "/";
std::string BQ_save_path = "/home/aidlux/BOE/FOG/BQ_AI_Det/" + m_pImageAllResult->productBaseResult->strproductName + "/";
CheckUtil::CreateDir(BQ_save_path);
// 初始化BQ AI检测结果
@ -2249,7 +2387,8 @@ int ImgCheckAnalysisy::AI_Detect_BQ()
{
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);
if (validRoi.width <= 0 || validRoi.height <= 0) continue;
if (validRoi.width <= 0 || validRoi.height <= 0)
continue;
// 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)
@ -2258,7 +2397,7 @@ int ImgCheckAnalysisy::AI_Detect_BQ()
int re = CheckUtil::cutSmallImg(AI_detImage, smallList, validRoi, AIInputImg_width, AIInputImg_height, 0, 0);
if (re == 0)
{
for (const auto& roi : smallList)
for (const auto &roi : smallList)
{
BQ_SmallRoiList.push_back(roi);
}
@ -2275,12 +2414,24 @@ int ImgCheckAnalysisy::AI_Detect_BQ()
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; }
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);
}
}
@ -2325,9 +2476,7 @@ int ImgCheckAnalysisy::AI_Detect_BQ()
while (completed < totalTasks)
{
// 提交任务：满足并发限制和待处理限制
if (submitted < totalTasks
&& runner->GetProcessingCount() < MAX_CONCURRENT
&& (submitted - completed) < MAX_PENDING)
if (submitted < totalTasks && runner->GetProcessingCount() < MAX_CONCURRENT && (submitted - completed) < MAX_PENDING)
{
std::shared_ptr<AIMulThreadRunBase::AITask> task = std::make_shared<AIMulThreadRunBase::AITask>();
task->id = submitted;
@ -2339,7 +2488,7 @@ int ImgCheckAnalysisy::AI_Detect_BQ()
// 调试存图：保存每个小块
if (m_pFuntion->function.f_Det_BQ.bsaveAll)
{
cv::imwrite(BQ_save_path +m_strCurDetCamChannel + "_" + std::to_string(submitted) + "_BQ_crop_in.png", task->input);
cv::imwrite(BQ_save_path + m_strCurDetCamChannel + "_" + std::to_string(submitted) + "_BQ_crop_in.png", task->input);
}
runner->SubmitTask(task);
@ -2356,7 +2505,7 @@ int ImgCheckAnalysisy::AI_Detect_BQ()
// 调试存图：保存模型原始输出mask
if (m_pFuntion->function.f_Det_BQ.bsaveAll)
{
cv::imwrite(BQ_save_path + m_strCurDetCamChannel+ "_" + std::to_string(result->id) + "_BQ_crop_out.png", outimg);
cv::imwrite(BQ_save_path + m_strCurDetCamChannel + "_" + std::to_string(result->id) + "_BQ_crop_out.png", outimg);
}
cv::Mat AIresult;
@ -2459,9 +2608,9 @@ int ImgCheckAnalysisy::GetBlob_BQ()
PushBlob(&blobs, &blobs_bq);
long te = CheckUtil::getcurTime();
m_pdetlog->AddCheckstr(PrintLevel_1, strBaseLog,
"BQ blob num = %d, merged to main blobs (total=%d), time=%ld ms",
blobs_bq.blobCount, blobs.blobCount, te - t1);
m_pdetlog->AddCheckstr(PrintLevel_1, strBaseLog,
"BQ blob num = %d, merged to main blobs (total=%d), time=%ld ms",
blobs_bq.blobCount, blobs.blobCount, te - t1);
// 调试存图
if (DetImgInfo_shareP->bDebugsaveImg && blobs_bq.blobCount > 0)
@ -2619,6 +2768,72 @@ int ImgCheckAnalysisy::AIMaskDet()
}
}
m_pdetlog->AddCheckstr(PrintLevel_1, "AIMaskDet", "=======cell127_DetAIResult end");
// RLine_512 检测
while (true)
{
std::this_thread::sleep_for(std::chrono::milliseconds(1));
if (!m_pImageAllResult->RLine_512_DetAIResult)
{
// 等待初始化
continue;
}
blobDetParam = m_pImageAllResult->RLine_512_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", "=======RLine_512_DetAIResult end");
m_AItask->waitComplate();
int rec = m_AItask->nresult;
@ -2760,6 +2975,9 @@ int ImgCheckAnalysisy::AI_Detect_Thread()
// 127cell
re = AI_Detect_127Cell();
// RLine_512
re = AI_Detect_RLine_512();
t3 = CheckUtil::getcurTime();
m_pdetlog->AddCheckstr(PrintLevel_0, DET_LOG_LEVEL_3, strBaseLog, "****** AI_Detect End; AI Run Time: sum %ld", t3 - t1);
@ -2839,7 +3057,7 @@ int ImgCheckAnalysisy::AI_Detect_QX()
}
int nSaveCnt = 0;
int AIInputImg_width = pAI_Model->input_0.width;
int AIInputImg_height = pAI_Model->input_0.height;
@ -2890,17 +3108,15 @@ int ImgCheckAnalysisy::AI_Detect_QX()
cv::Mat AIresultMask = pDetAIResult->AI_MaskImg;
// 资源控制：限制最大并发数和最大待处理数，防止GPU/CPU内存压力导致推理异常
const int MAX_CONCURRENT = 5; // 最大同时在推理中的任务数（降低GPU并发压力）
const int MAX_PENDING = 5; // submitted - completed 最大差值（限制内存中待处理结果数）
const int MAX_CONCURRENT = 5; // 最大同时在推理中的任务数（降低GPU并发压力）
const int MAX_PENDING = 5; // submitted - completed 最大差值（限制内存中待处理结果数）
t2 = CheckUtil::getcurTime();
while (completed < totalTasks)
{
// 如果任务还没提交完，且满足并发限制和待处理限制，提交新任务
if (submitted < totalTasks
&& runner->GetProcessingCount() < MAX_CONCURRENT
&& (submitted - completed) < MAX_PENDING)
if (submitted < totalTasks && runner->GetProcessingCount() < MAX_CONCURRENT && (submitted - completed) < MAX_PENDING)
{
std::shared_ptr<AIMulThreadRunBase::AITask> task = std::make_shared<AIMulThreadRunBase::AITask>();
@ -2981,9 +3197,9 @@ int ImgCheckAnalysisy::AI_Detect_QX()
std::string roi_ext = "[" + std::to_string(result->roi.x) + "," + std::to_string(result->roi.y) + "]";
std::string strSaveDir = "/home/aidlux/BOE/FOG/AI_Detect/" + DetImgInfo_shareP->strImgProductID + "/";
CheckUtil::CreateDir(strSaveDir);
std::string strSavePath_in = strSaveDir + m_strCurDetChannel +"_"+ roi_ext + "_"+ "in" + ".png";
std::string strSavePath_out = strSaveDir + m_strCurDetChannel +"_"+ roi_ext + "_"+ "out" + ".png";
std::string strSavePath_out_raw = strSaveDir + m_strCurDetChannel +"_"+ roi_ext + "_"+ "out_raw" + ".png";
std::string strSavePath_in = strSaveDir + m_strCurDetChannel + "_" + roi_ext + "_" + "in" + ".png";
std::string strSavePath_out = strSaveDir + m_strCurDetChannel + "_" + roi_ext + "_" + "out" + ".png";
std::string strSavePath_out_raw = strSaveDir + m_strCurDetChannel + "_" + roi_ext + "_" + "out_raw" + ".png";
cv::imwrite(strSavePath_in, result->input);
cv::imwrite(strSavePath_out, AIresult);
cv::imwrite(strSavePath_out_raw, AIresult_raw);
@ -3086,9 +3302,7 @@ int ImgCheckAnalysisy::AI_Detect_127Cell()
while (completed < totalTasks)
{
// 如果任务还没提交完，且满足并发限制和待处理限制，提交新任务
if (submitted < totalTasks
&& runner->GetProcessingCount() < MAX_CONCURRENT
&& (submitted - completed) < MAX_PENDING)
if (submitted < totalTasks && runner->GetProcessingCount() < MAX_CONCURRENT && (submitted - completed) < MAX_PENDING)
{
std::shared_ptr<AIMulThreadRunBase::AITask> task = std::make_shared<AIMulThreadRunBase::AITask>();
@ -3170,8 +3384,8 @@ int ImgCheckAnalysisy::AI_Detect_127Cell()
{
std::string strSaveDir = "/home/aidlux/BOE/FOG/AI_Detect_127/" + DetImgInfo_shareP->strImgProductID + "/";
CheckUtil::CreateDir(strSaveDir);
std::string strSavePath_in = strSaveDir + m_strCurDetChannel +"_"+ roi_ext + "_"+ "in" + ".png";
std::string strSavePath_out = strSaveDir + m_strCurDetChannel +"_"+ roi_ext + "_"+ "out" + ".png";
std::string strSavePath_in = strSaveDir + m_strCurDetChannel + "_" + roi_ext + "_" + "in" + ".png";
std::string strSavePath_out = strSaveDir + m_strCurDetChannel + "_" + roi_ext + "_" + "out" + ".png";
cv::imwrite(strSavePath_in, result->input);
cv::imwrite(strSavePath_out, AIresult);
}
@ -3196,6 +3410,199 @@ int ImgCheckAnalysisy::AI_Detect_127Cell()
return 0;
}
int ImgCheckAnalysisy::AI_Detect_RLine_512()
{
std::string strBaseLog = "AI_Detect_RLine_512";
m_pImageAllResult->RLine_512_DetAIResult = std::make_shared<ImageAllResult::Image_AI_Det_Result>();
if (m_pFuntion && m_pFuntion->function.f_RLineDet.bOpen)
{
}
else
{ // 未开启检测
m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, strBaseLog, " f_RLineDet close");
return 0;
}
if (m_pFuntion && m_pFuntion->function.f_RLineDet.bOpen_512)
{
}
else
{ // 未开启检测
m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, strBaseLog, " f_RLineDet 512 Model 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->RLine_512_DetAIResult;
cv::Mat AI_detImage = m_pImageAllResult->AI_detImg;
std::shared_ptr<AIModel_Base> pAI_Model = AI_Factory->AI_defect_RLine_512;
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;
// 资源控制：限制最大并发数和最大待处理数
const int MAX_CONCURRENT = 5;
const int MAX_PENDING = 5;
t2 = CheckUtil::getcurTime();
while (completed < totalTasks)
{
// 如果任务还没提交完，且满足并发限制和待处理限制，提交新任务
if (submitted < totalTasks && runner->GetProcessingCount() < MAX_CONCURRENT && (submitted - completed) < MAX_PENDING)
{
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);
}
#ifdef SAVE_RESIMG
{
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);
}
#endif
{
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);
}
}
// AI检测残点图存图
if (DetImgInfo_shareP->bDebugsaveImg)
{
bool bNeedSave = false;
std::string roi_ext = "[" + std::to_string(result->roi.x) + "," + std::to_string(result->roi.y) + "]";
bNeedSave = true;
if (bNeedSave && !AIresult.empty())
{
std::string strSaveDir = "/home/aidlux/BOE/FOG/AI_Detect_RLine_512/" + DetImgInfo_shareP->strImgProductID + "/";
CheckUtil::CreateDir(strSaveDir);
std::string strSavePath_in = strSaveDir + m_strCurDetChannel + "_" + roi_ext + "_" + "in" + ".png";
std::string strSavePath_out = strSaveDir + m_strCurDetChannel + "_" + roi_ext + "_" + "out" + ".png";
cv::imwrite(strSavePath_in, result->input);
cv::imwrite(strSavePath_out, AIresult);
}
}
}
completed++;
}
else
{
std::this_thread::sleep_for(std::chrono::milliseconds(1));
}
}
// 临时存图
if (DetImgInfo_shareP->bDebugsaveImg)
{
cv::imwrite(m_strCurDetCamChannel + "_AI_RLine_512_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()
{
@ -3206,7 +3613,10 @@ int ImgCheckAnalysisy::AI_QX_Class_Thread()
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)
if (blobs.blobTab[i].ErrType == CONFIG_QX_NAME_white_Cell ||
blobs.blobTab[i].ErrType == CONFIG_QX_NAME_black_Cell ||
blobs.blobTab[i].ErrType == CONFIG_QX_NAME_RLine_X ||
blobs.blobTab[i].ErrType == CONFIG_QX_NAME_RLine_Y)
{
}
else
@ -3775,34 +4185,35 @@ int ImgCheckAnalysisy::BLobToDetResult()
config_qx_type == CONFIG_QX_NAME_Other ||
config_qx_type == CONFIG_QX_NAME_LD)
{
qx_name = CONFIG_QX_NAME_Names[config_qx_type];
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 = -1;
if(m_pFuntion->function.f_LDConfig.bOpen && m_pFuntion->function.f_LDConfig.bUseLD_Standard)
if (m_pFuntion->function.f_LDConfig.bOpen && m_pFuntion->function.f_LDConfig.bUseLD_Standard)
{
if(blobs.blobTab[i].JudgArea >= m_pFuntion->function.f_LDConfig.fLD_Area &&
blobs.blobTab[i].grayDis >= m_pFuntion->function.f_LDConfig.fLD_HJ &&
blobs.blobTab[i].energy >= m_pFuntion->function.f_LDConfig.fLD_En &&
blobs.blobTab[i].len >= m_pFuntion->function.f_LDConfig.fLD_Len)
if (blobs.blobTab[i].JudgArea >= m_pFuntion->function.f_LDConfig.fLD_Area &&
blobs.blobTab[i].grayDis >= m_pFuntion->function.f_LDConfig.fLD_HJ &&
blobs.blobTab[i].energy >= m_pFuntion->function.f_LDConfig.fLD_En &&
blobs.blobTab[i].len >= m_pFuntion->function.f_LDConfig.fLD_Len)
{
dbresult = 1;
bLD_Standard = true;
}
pQxlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "LD Analysis", "Area %0.2f > %0.2f , hj %0.2f > %0.2f , Energy %0.2f > %0.2f , len %0.2f > %0.2f",
blobs.blobTab[i].JudgArea, m_pFuntion->function.f_LDConfig.fLD_Area, blobs.blobTab[i].grayDis, m_pFuntion->function.f_LDConfig.fLD_HJ, blobs.blobTab[i].energy, m_pFuntion->function.f_LDConfig.fLD_En, blobs.blobTab[i].len, m_pFuntion->function.f_LDConfig.fLD_Len);
pQxlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "LD Analysis", "Area %0.2f > %0.2f , hj %0.2f > %0.2f , Energy %0.2f > %0.2f , len %0.2f > %0.2f",
blobs.blobTab[i].JudgArea, m_pFuntion->function.f_LDConfig.fLD_Area, blobs.blobTab[i].grayDis, m_pFuntion->function.f_LDConfig.fLD_HJ, blobs.blobTab[i].energy, m_pFuntion->function.f_LDConfig.fLD_En, blobs.blobTab[i].len, m_pFuntion->function.f_LDConfig.fLD_Len);
}
if(dbresult != 1)
if (dbresult != 1)
{
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
// 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()); }
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)
{
@ -4375,7 +4786,7 @@ int ImgCheckAnalysisy::AI_Classify_New(const cv::Mat &src_Img, cv::Rect qx_roi,
// bIsLine = true;
// }
//长宽比满足，判断为线
// 长宽比满足，判断为线
if (flenr > 10)
{
// printf("\n\n\n\n\n\n\n\n\n--------- flenr %f len %d,widt %d,fjustarea %f\n", flenr,len,widt,fjustarea);
@ -4384,7 +4795,7 @@ int ImgCheckAnalysisy::AI_Classify_New(const cv::Mat &src_Img, cv::Rect qx_roi,
strclassName = "line";
bIsLine = true;
}
m_pdetlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "AI_Classify_line", "bIsLine %d, flenr %f len %d,widt %d,fjustarea %f", bIsLine, flenr,len,widt,fjustarea);
m_pdetlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "AI_Classify_line", "bIsLine %d, flenr %f len %d,widt %d,fjustarea %f", bIsLine, flenr, len, widt, fjustarea);
}
}
@ -4509,7 +4920,7 @@ int ImgCheckAnalysisy::ImgPreDet()
}
#ifdef SAVE_RESIMG
m_CheckResult_shareP->cutSrcimg = m_pImageAllResult->detImg;
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;
@ -4683,9 +5094,9 @@ int ImgCheckAnalysisy::UpdateSheildMask(std::string strChannel, cv::Rect roi)
}
else
{
if(!m_pFuntion->function.f_ShieldRegion.bOpen)
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)
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
@ -4873,6 +5284,12 @@ std::string ImgCheckAnalysisy::ConfigTypeToWebDetType(int nconfigType)
case CONFIG_QX_NAME_black_Cell:
strqx = Function_CONFIG_QX_NAME_Names[Function_CONFIG_QX_NAME_Cell];
break;
case CONFIG_QX_NAME_RLine_X:
strqx = Function_CONFIG_QX_NAME_Names[Function_CONFIG_QX_NAME_line];
break;
case CONFIG_QX_NAME_RLine_Y:
strqx = Function_CONFIG_QX_NAME_Names[Function_CONFIG_QX_NAME_line];
break;
break;
default:
break;
@ -4987,15 +5404,14 @@ int ImgCheckAnalysisy::CalBlobDensity_QX()
m_pDetResult->pQx_ErrorList->at(i).density = fD;
m_pdetlog->AddCheckstr(PrintLevel_2, "Density_QX", " idx=%d type=%d(%s) roi[%d,%d,%d,%d] near_num=%d avgDis=%.2f score=%.3f density=%.2f",
i,
m_pDetResult->pQx_ErrorList->at(i).nconfig_qx_type,
m_pDetResult->pQx_ErrorList->at(i).qx_name.c_str(),
roi.x, roi.y, roi.width, roi.height,
num, avdis, fScore, fD);
i,
m_pDetResult->pQx_ErrorList->at(i).nconfig_qx_type,
m_pDetResult->pQx_ErrorList->at(i).qx_name.c_str(),
roi.x, roi.y, roi.width, roi.height,
num, avdis, fScore, fD);
}
m_pdetlog->AddCheckstr(PrintLevel_1, "Density_QX", "End: processed %zu defects", m_pDetResult->pQx_ErrorList->size());
return 0;
}

111
ConfigModule/include/CheckConfigDefine.h
Unescape View File

@ -71,6 +71,8 @@ enum CONFIG_QX_NAME_
CONFIG_QX_NAME_black_Cell, // 白cell
CONFIG_QX_NAME_LD_HS, // 黑闪类画面的亮点
CONFIG_QX_NAME_LackPOL, // 缺失pol检测
CONFIG_QX_NAME_RLine_X, // 弱线 X
CONFIG_QX_NAME_RLine_Y, // 弱线 Y
CONFIG_QX_NAME_count,
};
// 缺陷项对应在参数中的名称
@ -105,7 +107,9 @@ static std::vector<std::string> CONFIG_QX_NAME_Names =
"white_Cell",
"black_Cell",
"LD_HS",
"LackPOL"};
"LackPOL",
"RLine_X",
"RLine_Y"};
// web控制检测的缺陷类型，
enum Function_CONFIG_QX_NAME_
@ -205,8 +209,7 @@ static const std::string IMG_CHANNEL_NAME[] =
"RGB-HGRAY",
"SCANR",
"SCANG",
"SCANB"
};
"SCANB"};
// 分析类型
enum ANALYSIS_TYPE_
{
@ -453,7 +456,7 @@ struct BasicConfig
float fImage_Scale_y; // 成像精度
float fProduct_Off_X_mm; // 产品偏移量
std::string strCamName; //
std::string strConfigVersion; // 配置版本
std::string strConfigVersion; // 配置版本
float density_R_mm; // 密度计算半径 像素
BasicConfig()
@ -854,7 +857,7 @@ struct Function_AI_QX
void print(std::string str)
{
// printf("%s>>bOpen %d POLToWhitePOL %d AllToChess %d 127WhitePOl_UseDP %d 127WhitePOl_DP_IOU %f\n",
// str.c_str(), bOpen, bPOLToWhitePOL, bAllToChess, b127WhitePOl_UseDP, f127WhitePOl_DP_IOU);
// str.c_str(), bOpen, bPOLToWhitePOL, bAllToChess, b127WhitePOl_UseDP, f127WhitePOl_DP_IOU);
}
std::string GetInfo(std::string str)
{
@ -875,10 +878,10 @@ struct Function_AI_LD
float fDP_IOU; // DP的IOU
bool bUseLD_Standard; // 是否使用亮点标准化参数
float fLD_Area; // 亮点面积
float fLD_En; // 亮点的能量
float fLD_HJ; // 亮点灰阶
float fLD_Len; // 亮点长度
float fLD_Area; // 亮点面积
float fLD_En; // 亮点的能量
float fLD_HJ; // 亮点灰阶
float fLD_Len; // 亮点长度
Function_AI_LD()
{
Init();
@ -1554,8 +1557,8 @@ struct AD_Analysisy_S
// 暗点同位置判断(IOU)
struct AD_Analysisy_IOU
{
float AD_IOU; // IOU 阈值
float AD_Expand; // 扩张阈值
float AD_IOU; // IOU 阈值
float AD_Expand; // 扩张阈值
AD_Analysisy_IOU()
{
Init();
@ -1605,7 +1608,7 @@ struct AD_Analysisy_Bind
correlated_channels.clear();
correlated_types.clear();
}
void copy (AD_Analysisy_Bind tem)
void copy(AD_Analysisy_Bind tem)
{
this->bUse = tem.bUse;
this->main_channel_2s = tem.main_channel_2s;
@ -1639,23 +1642,23 @@ struct AD_Analysisy_SF
s_sf.clear();
region_sf.clear();
}
void copy (AD_Analysisy_SF tem)
void copy(AD_Analysisy_SF tem)
{
this->s_sf = tem.s_sf;
this->region_sf = tem.region_sf;
}
std::string GetInfo(std::string str)
{
std::string str123;
for (int i = 0; i < s_sf.size(); i++)
{
str123 += str + ":s_sf " + s_sf[i] + ";";
}
for (int i = 0; i < region_sf.size(); i++)
{
str123 += str + ":region_sf " + region_sf[i] + ";";
}
return str123;
std::string str123;
for (int i = 0; i < s_sf.size(); i++)
{
str123 += str + ":s_sf " + s_sf[i] + ";";
}
for (int i = 0; i < region_sf.size(); i++)
{
str123 += str + ":region_sf " + region_sf[i] + ";";
}
return str123;
}
};
// 异物检测功能
@ -1747,8 +1750,8 @@ struct Function_Edge_Det
}
};
struct Function_Det_BQ
{
bool bBQ_AI_Det; // 是否启用标签独立AI检测
{
bool bBQ_AI_Det; // 是否启用标签独立AI检测
int BQ_expand;
bool bsaveAll;
@ -1781,9 +1784,39 @@ struct Function_Det_BQ
std::string str123 = buffer;
return str123;
}
};
// 启用127cell 独立检测
struct Function_Det_RLine
{
bool bOpen; // 是否开启
bool bOpen_512; // 512模型是否开启。
Function_Det_RLine()
{
Init();
}
void Init()
{
bOpen = false;
bOpen_512 = false;
}
void copy(Function_Det_RLine tem)
{
this->bOpen = tem.bOpen;
this->bOpen_512 = tem.bOpen_512;
}
void print(std::string str)
{
printf("%s>>bOpen %d bOpen_512 %d \n", str.c_str(), bOpen, bOpen_512);
}
std::string GetInfo(std::string str)
{
char buffer[64];
sprintf(buffer, "%s>>bOpen %d bOpen_512 %d \n", str.c_str(), bOpen, bOpen_512);
std::string str123 = buffer;
return str123;
}
};
// 检测功能
struct CheckFunction
{
@ -1803,6 +1836,7 @@ struct CheckFunction
Function_POL_Check f_POL_Check; // 异物的检测功能
Function_Edge_Det f_dege_Det;
Function_Det_BQ f_Det_BQ;
Function_Det_RLine f_RLineDet; // 弱线检测参数
CheckFunction()
{
Init();
@ -1825,6 +1859,7 @@ struct CheckFunction
f_POL_Check.Init();
f_dege_Det.Init();
f_Det_BQ.Init();
f_RLineDet.Init();
}
void copy(CheckFunction tem)
{
@ -1845,6 +1880,7 @@ struct CheckFunction
this->f_POL_Check.copy(tem.f_POL_Check);
this->f_dege_Det.copy(tem.f_dege_Det);
this->f_Det_BQ.copy(tem.f_Det_BQ);
this->f_RLineDet.copy(tem.f_RLineDet);
}
void print(std::string str)
{
@ -1865,6 +1901,7 @@ struct CheckFunction
f_POL_Check.print("f_POL_Check");
f_dege_Det.print("f_dege_Det");
f_Det_BQ.print("f_Det_BQ");
f_RLineDet.print("f_RLineDet");
}
std::string GetInfo(std::string str)
{
@ -1886,6 +1923,7 @@ struct CheckFunction
str123 += f_POL_Check.GetInfo("f_POL_Check");
str123 += f_dege_Det.GetInfo("f_dege_Det");
str123 += f_Det_BQ.GetInfo("f_Det_BQ");
str123 += f_RLineDet.GetInfo("f_RLineDet");
return str123;
}
};
@ -2262,17 +2300,16 @@ struct Base_Function_Edge_Det
struct Base_Function_AD_Check
{
bool bOpen; // 是否开启
AD_S_Standard S_standard_3s; // 3s 标准
AD_S_Standard S_standard_2s; // 2s 标准
AD_S_Standard S_standard_1s; // 1s 标准
AD_Analysisy_Num analysis_num; // 数量分析
AD_Analysisy_Dis analysis_dis; // 距离分析
AD_Analysisy_S analysis_s; // s 标准分析
AD_Analysisy_IOU analysis_iou; // IOU 分析
bool bOpen; // 是否开启
AD_S_Standard S_standard_3s; // 3s 标准
AD_S_Standard S_standard_2s; // 2s 标准
AD_S_Standard S_standard_1s; // 1s 标准
AD_Analysisy_Num analysis_num; // 数量分析
AD_Analysisy_Dis analysis_dis; // 距离分析
AD_Analysisy_S analysis_s; // s 标准分析
AD_Analysisy_IOU analysis_iou; // IOU 分析
AD_Analysisy_Bind analysis_bind; // 绑定分析
AD_Analysisy_SF analysis_sf; // 同画面参数分析
AD_Analysisy_SF analysis_sf; // 同画面参数分析
Base_Function_AD_Check()
{
@ -2316,7 +2353,7 @@ struct Base_Function_AD_Check
analysis_s.GetInfo("analysis_s").c_str(),
analysis_iou.GetInfo("analysis_iou").c_str(),
analysis_bind.GetInfo("analysis_bind").c_str(),
analysis_sf.GetInfo("analysis_sf").c_str());
analysis_sf.GetInfo("analysis_sf").c_str());
}
std::string GetInfo(std::string str)
{

29
ConfigModule/src/JsonConfig.cpp
Unescape View File

@ -48,11 +48,11 @@ void CommonParamToCheckConfigJson::toObjectFromValue(Json::Value root)
if (value.isObject())
{
_config.baseConfig.strConfigVersion = value["version"].asString();
if ( _config.baseConfig.strConfigVersion == "")
if (_config.baseConfig.strConfigVersion == "")
{
_config.baseConfig.strConfigVersion = "NULL";
}
_config.baseConfig.strConfigVersion = "NULL";
}
_config.baseConfig.image_widht = value["image_widht"].asInt();
_config.baseConfig.Image_height = value["Image_height"].asInt();
_config.baseConfig.bDrawShieldRoi = value["bDrawShieldRoi"].asBool();
@ -567,7 +567,7 @@ int ChannelFuntonConfigJson::GetFunction(Json::Value value, CheckFunction &funct
{
function.f_LDConfig.fDP_IOU = value_f["form"]["LD_Det"]["DP_IOU"].asFloat();
}
if (value_f["form"]["LD_Standard"]["LD_Area"])
{
function.f_LDConfig.fLD_Area = value_f["form"]["LD_Standard"]["LD_Area"].asFloat();
@ -1060,6 +1060,25 @@ int ChannelFuntonConfigJson::GetFunction(Json::Value value, CheckFunction &funct
function.f_Det_BQ.bsaveAll = true;
}
}
if ("Det_RLine" == strCode)
{
auto value_f = value[i];
// std::cout << value_f << std::endl;
function.f_RLineDet.bOpen = value_f["isOpen"].asBool();
if (function.f_RLineDet.bOpen)
{
if (value_f["form"]["Config_Model_512"]["bOpen"])
{
function.f_RLineDet.bOpen_512 = value_f["form"]["Config_Model_512"]["bOpen"].asBool();
}
}
else
{
function.f_RLineDet.Init();
}
// function.f_RLineDet.print("");
// getchar();
}
}
}
return 0;

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