@ -170,7 +170,7 @@ int ImgCheckAnalysisy::GetStatus()
std : : string ImgCheckAnalysisy : : GetVersion ( )
{
return std : : string ( " BOE_1. 2.0" ) ;
return std : : string ( " BOE_1. 3.0_" + std : : string ( __DATE__ ) + " _ " + std : : string ( __TIME__ ) ) ;
}
std : : string ImgCheckAnalysisy : : GetErrorInfo ( )
@ -332,7 +332,7 @@ cv::Scalar ImgCheckAnalysisy::calc_blob_info_withstats(cv::Mat &img, const cv::M
// 计算 hj（ ）
// double hj = std::abs(fbk - fdet);
double hj = CheckUtil : : CalHj ( cimg , cmask , mean_bk. val [ 0 ] ) ;
double hj = CheckUtil : : CalHj Weighted ( cimg , cmask , fbk, 2.0f ) ;
int worb = 0 ;
if ( fdet > = fbk )
@ -381,7 +381,7 @@ double ImgCheckAnalysisy::CalBlobHJ(cv::Mat &img, const cv::Mat &mask, cv::Rect
// 计算 hj（ ）
// double hj = std::abs(fbk - fdet);
double hj = CheckUtil : : CalHj ( cimg , cmask , fbk ) ;
double hj = CheckUtil : : CalHj Weighted ( cimg , cmask , fbk , 2.0f ) ;
static int kkk = 0 ;
unsigned char * pErrordata = ( unsigned char * ) cimg . data ;
@ -518,6 +518,14 @@ int ImgCheckAnalysisy::CheckRun()
Edge_Det ( ) ;
// BQ标签AI检测
{
long t_BQ_s = CheckUtil : : getcurTime ( ) ;
int recBQ = AI_Detect_BQ ( ) ;
long t_BQ_e = CheckUtil : : getcurTime ( ) ;
m_pdetlog - > AddCheckstr ( PrintLevel_0 , " 4、BQ Detect " , " -------------------------BQ AI Detect--------%ld ms------- \n " , t_BQ_e - t_BQ_s ) ;
}
m_CheckResult_shareP - > resultMaskImg = m_pImageAllResult - > qx_DetAIResult - > AI_MaskImg ;
// cv::imwrite("dddddddd.png", m_pImageAllResult->qx_DetAIResult->AI_MaskImg);
@ -589,6 +597,7 @@ int ImgCheckAnalysisy::SetNewConfig()
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 ( ) ) ;
@ -1448,6 +1457,9 @@ int ImgCheckAnalysisy::GetCheckResultBLob()
BLobToDetResult ( ) ;
// 计算缺陷密度
CalBlobDensity_QX ( ) ;
return 0 ;
}
@ -1691,6 +1703,8 @@ int ImgCheckAnalysisy::GetALLBlob()
re = GetBlob_QX ( ) ;
long t4 = CheckUtil : : getcurTime ( ) ;
re = GetBlob_127cell ( ) ;
long t5 = CheckUtil : : getcurTime ( ) ;
re = GetBlob_BQ ( ) ;
if ( blobs . blobCount > 100 )
{
@ -1700,8 +1714,8 @@ int ImgCheckAnalysisy::GetALLBlob()
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 , t e - t4 ) ;
" ---GetALLBlob End ;use time %ld ms yx %ld ms lack %ld ms qx %ld ms 127 %ld ms bq %ld ms " ,
te - t1 , t2 - t1 , t3 - t2 , t4 - t3 , t 5 - t4 , te - t5 ) ;
// getchar();
return 0 ;
@ -1757,6 +1771,10 @@ int ImgCheckAnalysisy::GetBLob_YX()
cv : : findContours ( erodedImage , contours , RETR_EXTERNAL , CHAIN_APPROX_SIMPLE ) ;
int nresult = 0 ;
// 将 mask 一次性 resize 到 detImg 尺寸，避免循环内反复 resize
cv : : Mat maskImg ;
cv : : resize ( erodedImage , maskImg , cv : : Size ( m_pImageAllResult - > detImg . cols , m_pImageAllResult - > detImg . rows ) , 0 , 0 , cv : : INTER_AREA ) ;
for ( size_t i = 0 ; i < contours . size ( ) ; + + i )
{
@ -1774,7 +1792,15 @@ int ImgCheckAnalysisy::GetBLob_YX()
roi . y * = fy_src ;
roi . height * = fy_src ;
float len = std : : sqrt ( roi . width * roi . width + roi . height * roi . height ) ;
// 精确计算长度
float re_len = Cal_QXLen ( maskImg ( roi ) , config_qx_type , fx_src , fy_src ) ;
cv : : Scalar result = calc_blob_info_withstats ( m_pImageAllResult - > detImg , maskImg , roi ) ;
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 ) ;
if ( true )
{
@ -1784,12 +1810,12 @@ int ImgCheckAnalysisy::GetBLob_YX()
temerror . area = area ;
temerror . JudgArea = judgeArea ;
temerror . JudgArea_second = judgeArea ;
temerror . energy = area * fx_src * fy_src ;
temerror . flen = ;
temerror . energy = result[ 1 ] ;
temerror . flen = re_ len;
temerror . nconfig_qx_type = config_qx_type ;
temerror . qx_name = qx_name ;
temerror . maxValue = 0 ;
temerror . grayDis = 0 ;
temerror . maxValue = max_val ;
temerror . grayDis = result [ 2 ] ;
temerror . density = 0 ;
temerror . fUpIou = 0 ;
@ -2139,6 +2165,302 @@ int ImgCheckAnalysisy::GetBlob_127cell()
return 0 ;
}
// BQAI检测
int ImgCheckAnalysisy : : AI_Detect_BQ ( )
{
std : : string strBaseLog = " AI_Detect_BQ " ;
// 检查BQ标签AI检测是否启用
if ( ! m_pImageAllResult - > cameraBaseResult - > pBQ_Result )
{
return 0 ;
}
if ( ! m_pFuntion - > function . f_Det_BQ . bBQ_AI_Det )
{
return 0 ;
}
int bqNum = static_cast < int > ( m_pImageAllResult - > cameraBaseResult - > pBQ_Result - > pBQ_cropImages . size ( ) ) ;
if ( bqNum < = 0 )
{
return 0 ;
}
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 + " / " ;
CheckUtil : : CreateDir ( BQ_save_path ) ;
// 初始化BQ AI检测结果
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 ;
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（ ）
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 ;
// 为每个BQ区域生成小ROI列表，
std : : vector < cv : : Rect > BQ_SmallRoiList ;
for ( int i = 0 ; i < bqNum ; i + + )
{
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 ;
// 如果BQ区域大于等于模型输入尺寸，
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，
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 ( m_pFuntion - > function . f_Det_BQ . bsaveAll )
{
cv : : Mat debugImg ;
if ( AI_detImage . channels ( ) = = 1 )
{
cv : : cvtColor ( AI_detImage , debugImg , cv : : COLOR_GRAY2BGR ) ;
}
else
{
debugImg = AI_detImage . clone ( ) ;
}
for ( size_t i = 0 ; i < BQ_SmallRoiList . size ( ) ; i + + )
{
cv : : rectangle ( debugImg , BQ_SmallRoiList . at ( i ) , cv : : Scalar ( 0 , 0 , 255 ) , 2 ) ;
}
cv : : imwrite ( BQ_save_path + m_strCurDetCamChannel + " _BQ_original_with_rois.png " , debugImg ) ;
}
int submitted = 0 ;
int completed = 0 ;
// 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 ;
long t2 = CheckUtil : : getcurTime ( ) ;
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 )
{
std : : shared_ptr < AIMulThreadRunBase : : AITask > task = std : : make_shared < AIMulThreadRunBase : : AITask > ( ) ;
task - > id = submitted ;
task - > roi = BQ_SmallRoiList . at ( submitted ) ;
task - > input = AI_detImage ( task - > roi ) . clone ( ) ;
task - > output = std : : make_shared < cv : : Mat > ( ) ;
task - > engine = pAI_Model ;
// 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 ) ;
}
runner - > SubmitTask ( task ) ;
submitted + + ;
}
// 收集结果
std : : shared_ptr < AIMulThreadRunBase : : AITask > result ;
if ( runner - > PopResult ( result ) )
{
cv : : Mat & outimg = * ( result - > output ) ;
if ( ! outimg . empty ( ) )
{
// 调试存图：
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 : : Mat AIresult ;
if ( bResizeToSrc )
{
cv : : resize ( outimg , AIresult , src_sz , 0 , 0 , 0 ) ;
}
else
{
AIresult = outimg ;
}
cv : : Rect srcsize_roi = result - > roi ;
AIresult . copyTo ( AIresultMask ( srcsize_roi ) , AIresult ) ;
// 调试存图：
if ( m_pFuntion - > function . f_Det_BQ . bsaveAll & & bResizeToSrc )
{
cv : : imwrite ( BQ_save_path + 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] " ,
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 " , result - > id ) ;
}
completed + + ;
}
else
{
std : : this_thread : : sleep_for ( std : : chrono : : milliseconds ( 1 ) ) ;
}
}
long te = CheckUtil : : getcurTime ( ) ;
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 ( m_pFuntion - > function . f_Det_BQ . bsaveAll )
{
cv : : imwrite ( BQ_save_path + m_strCurDetCamChannel + " _AI_BQ_mask.png " , pDetAIResult - > AI_MaskImg ) ;
}
return 0 ;
}
int ImgCheckAnalysisy : : GetBlob_BQ ( )
{
std : : string strBaseLog = " GetBlob_BQ " ;
// 检查BQ标签AI检测是否启用
if ( ! m_pImageAllResult - > cameraBaseResult - > pBQ_Result )
{
return 0 ;
}
if ( ! m_pImageAllResult - > cameraBaseResult - > pBQ_Result - > bBQ_AI_Det )
{
return 0 ;
}
if ( ! m_pImageAllResult - > bq_DetAIResult )
{
m_pdetlog - > AddCheckstr ( PrintLevel_2 , strBaseLog , " bq_DetAIResult is null, skip " ) ;
return 0 ;
}
std : : shared_ptr < ImageAllResult : : Image_AI_Det_Result > pDetAIResult = m_pImageAllResult - > bq_DetAIResult ;
cv : : Mat maskimg = pDetAIResult - > AI_MaskImg ;
if ( maskimg . empty ( ) )
{
m_pdetlog - > AddCheckstr ( PrintLevel_2 , strBaseLog , " AI_MaskImg is empty, skip " ) ;
return 0 ;
}
long t1 = CheckUtil : : getcurTime ( ) ;
// 使用与主流程相同的blob提取方式：
// BQ检测的mask中，
ERROR_DOTS_BLOBS blobs_bq ;
memset ( & blobs_bq , 0x00 , sizeof ( ERROR_DOTS_BLOBS ) ) ;
unsigned char * pGrayErrordata = ( unsigned char * ) maskimg . data ;
int width = maskimg . cols ;
int height = maskimg . rows ;
int minArea = 10 ; // BQ标签区域最小缺陷面积阈值
// 使用逐像素扫描方式提取blob（ ）
GetBlobs_V3 ( & blobs_bq , pGrayErrordata , width , height , minArea ) ;
// 设置BQ blob的默认缺陷类型（ ）
// 使用非cell类型，
for ( int i = 0 ; i < blobs_bq . blobCount ; i + + )
{
blobs_bq . blobTab [ i ] . ErrType = CONFIG_QX_NAME_LD ; // 以亮点作为初始类型，后续分类修正
}
// 将BQ的blob汇入主blob列表
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 ) ;
// 调试存图
if ( DetImgInfo_shareP - > bDebugsaveImg & & blobs_bq . blobCount > 0 )
{
cv : : Mat tm ;
cv : : cvtColor ( maskimg , tm , cv : : COLOR_GRAY2RGB ) ;
for ( int i = 0 ; i < blobs_bq . blobCount ; i + + )
{
cv : : Rect roi ;
roi . x = blobs_bq . blobTab [ i ] . minx ;
roi . y = blobs_bq . blobTab [ i ] . miny ;
roi . width = blobs_bq . blobTab [ i ] . maxx - blobs_bq . blobTab [ i ] . minx + 1 ;
roi . height = blobs_bq . blobTab [ i ] . maxy - blobs_bq . blobTab [ i ] . miny + 1 ;
cv : : rectangle ( tm , roi , cv : : Scalar ( 0 , 0 , 255 ) , 2 ) ;
}
cv : : imwrite ( m_strCurDetCamChannel + " _BQ_blob.png " , tm ) ;
}
return 0 ;
}
int ImgCheckAnalysisy : : AIMaskDet ( )
{
m_pdetlog - > AddCheckstr ( PrintLevel_0 , " AIMaskDet " , " =======start " ) ;
@ -2482,6 +2804,11 @@ int ImgCheckAnalysisy::AI_Detect_QX()
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 " ) ;
@ -2611,6 +2938,24 @@ int ImgCheckAnalysisy::AI_Detect_QX()
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/ " + 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 + + ;
}
@ -2621,7 +2966,9 @@ int ImgCheckAnalysisy::AI_Detect_QX()
}
te = CheckUtil : : getcurTime ( ) ;
float mean_AI = ( te - t2 ) / SmallRoiList . size ( ) ;
m_pdetlog - > bPrintStr = true ;
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 ) ;
m_pdetlog - > bPrintStr = false ;
// 临时存图
if ( DetImgInfo_shareP - > bDebugsaveImg )
@ -3351,23 +3698,40 @@ int ImgCheckAnalysisy::BLobToDetResult()
}
}
bool bLD_Standard = false ; // 是否通过LD标准判定（ ）
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 )
{
std : : string 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 = LDJudge ( config_qx_type , roi , JudgArea , blobs . blobTab [ i ] . maxValue , blobs . blobTab [ i ] . grayDis , pQxlog ) ;
int detre = 1 ;
int dbresult = - 1 ;
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 )
{
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 ) ;
}
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
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_False ( detre ) , 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，
if ( m_pFuntion - > function . f_AIQX . bAllToChess )
{
@ -3428,8 +3792,8 @@ int ImgCheckAnalysisy::BLobToDetResult()
QX_Stauts qx_status = QX_Stauts_Analysis ;
// 和UP画面进行IOU判断
if ( m_pFuntion - > function . f_UseUpQX . bOpen )
// 和UP画面进行IOU判断 (通过亮点标准的缺陷跳过此检查)
if ( ! bLD_Standard & & m_pFuntion - > function . f_UseUpQX . bOpen )
{
if ( fupS > = m_pFuntion - > function . f_UseUpQX . fIOU )
{
@ -3441,6 +3805,10 @@ int ImgCheckAnalysisy::BLobToDetResult()
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 if ( bLD_Standard )
{
pQxlog - > AddCheckstr ( PrintLevel_2 , DET_LOG_LEVEL_3 , " Up Mask judge " , " bLD_Standard = true, skip UP/DP IOU check ;fupS = %0.2f " , fupS ) ;
}
else
{
pQxlog - > AddCheckstr ( PrintLevel_2 , DET_LOG_LEVEL_3 , " Up Mask judge " , " UseUpQX.bOpen = false ;fupS = %0.2f " , fupS ) ;
@ -3450,7 +3818,7 @@ int ImgCheckAnalysisy::BLobToDetResult()
bool ban = JudgeQXAnalysis ( config_qx_type , pQxlog ) ;
if ( ! ban )
{
std: : string qx_name = CONFIG_QX_NAME_Names [ config_qx_type ] ;
= 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 ( ) ) ;
@ -3467,7 +3835,7 @@ int ImgCheckAnalysisy::BLobToDetResult()
isMarksheildQX = Judge_MarkLine_QX ( config_qx_type , roi , pQxlog ) ;
if ( isMarksheildQX )
{
std: : string qx_name = CONFIG_QX_NAME_Names [ config_qx_type ] ;
= 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 ( ) ) ;
@ -3496,6 +3864,7 @@ int ImgCheckAnalysisy::BLobToDetResult()
temerror . grayDis = blobs . blobTab [ i ] . grayDis ;
temerror . density = blobs . blobTab [ i ] . density ;
temerror . fUpIou = fupS ;
temerror . bIsStandardLD = bLD_Standard ;
temerror . whiteOrBlack = blobs . blobTab [ i ] . whiteOrblack ;
temerror . qx_status = qx_status ;
@ -3738,11 +4107,13 @@ int ImgCheckAnalysisy::AI_Classify_New(const cv::Mat &src_Img, cv::Rect qx_roi,
if ( 3 ! = AI_detImage . channels ( ) )
{
cv : : cvtColor ( AI_detImage ( task - > roi ) , task - > input , cv : : COLOR_GRAY2BGR ) ;
cv : : Mat temsizeimg ;
cv : : resize ( AI_detImage ( task - > roi ) , temsizeimg , sz ) ;
cv : : cvtColor ( temsizeimg , task - > input , cv : : COLOR_GRAY2BGR ) ;
}
else
{
task- > input = AI_detImage ( task - > roi ) . clone ( ) ;
cv: : resize ( AI_detImage ( task - > roi ) , task - > input , sz ) ;
}
task - > engine = pAIDet ;
@ -3756,6 +4127,12 @@ int ImgCheckAnalysisy::AI_Classify_New(const cv::Mat &src_Img, cv::Rect qx_roi,
if ( runner - > PopResult ( result ) )
{
// if (true)
// {
// printf("result->cls_score %f\n",result->cls_score);
// std::string classpath = std::to_string(result->cls_label) + "_" + std::to_string(result->cls_score) + ".png";
// cv::imwrite(classpath, result->input);
// }
int cls_num = result - > cls_label ;
if ( cls_num > = 0 & & cls_num < maxcls )
{
@ -3884,6 +4261,7 @@ int ImgCheckAnalysisy::AI_Classify_New(const cv::Mat &src_Img, cv::Rect qx_roi,
if ( true )
{
// 长宽比
bool bIsLine = false ;
float flenr = 1 ;
int len = 0 ;
int widt = 0 ;
@ -3900,29 +4278,42 @@ int ImgCheckAnalysisy::AI_Classify_New(const cv::Mat &src_Img, cv::Rect qx_roi,
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 )
// // 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";
// bIsLine = true;
// }
// // 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";
// bIsLine = true;
// }
//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);
// getchar();
cls_num = AI_CLass_QX_NAME_line ;
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 ) ;
}
}
@ -4433,3 +4824,104 @@ bool ImgCheckAnalysisy::JudgeQXAnalysis(int nqx_configType, std::shared_ptr<DetL
return re ;
}
int ImgCheckAnalysisy : : CalBlobDensity_QX ( )
{
float fs_x = m_fImgage_Scale_X ;
float fs_y = m_fImgage_Scale_Y ;
double dis_T = m_pBasicConfig - > density_R_mm ;
if ( dis_T < = 0 | | dis_T > 99999 )
{
dis_T = 5 ;
}
if ( ! m_pDetResult | | ! m_pDetResult - > pQx_ErrorList | | m_pDetResult - > pQx_ErrorList - > size ( ) < = 0 )
{
m_pdetlog - > AddCheckstr ( PrintLevel_1 , " Density_QX " , " pQx_ErrorList is empty, skip density calc " ) ;
return 0 ;
}
m_pdetlog - > AddCheckstr ( PrintLevel_1 , " Density_QX " , " Start: dis_T=%.1fmm qx_count=%zu " , dis_T , m_pDetResult - > pQx_ErrorList - > size ( ) ) ;
for ( int i = 0 ; i < m_pDetResult - > pQx_ErrorList - > size ( ) ; i + + )
{
m_pDetResult - > pQx_ErrorList - > at ( i ) . density = 1 ;
if ( m_pDetResult - > pQx_ErrorList - > at ( i ) . nconfig_qx_type = = CONFIG_QX_NAME_MTX | |
m_pDetResult - > pQx_ErrorList - > at ( i ) . nconfig_qx_type = = CONFIG_QX_NAME_POL_Cell | |
m_pDetResult - > pQx_ErrorList - > at ( i ) . nconfig_qx_type = = CONFIG_QX_NAME_LD | |
m_pDetResult - > pQx_ErrorList - > at ( i ) . nconfig_qx_type = = CONFIG_QX_NAME_AD )
{
/* code */
}
else
{
continue ;
}
cv : : Rect roi = m_pDetResult - > pQx_ErrorList - > at ( i ) . roi ;
cv : : Point p ;
p . x = roi . x + roi . width * 0.5 ;
p . y = roi . y + roi . height * 0.5 ;
int num = 1 ;
double sum_dis = 0 ;
for ( int j = 0 ; j < m_pDetResult - > pQx_ErrorList - > size ( ) ; j + + )
{
if ( i = = j )
{
continue ;
}
if ( m_pDetResult - > pQx_ErrorList - > at ( j ) . nconfig_qx_type = = CONFIG_QX_NAME_MTX | |
m_pDetResult - > pQx_ErrorList - > at ( j ) . nconfig_qx_type = = CONFIG_QX_NAME_POL_Cell | |
m_pDetResult - > pQx_ErrorList - > at ( j ) . nconfig_qx_type = = CONFIG_QX_NAME_LD | |
m_pDetResult - > pQx_ErrorList - > at ( j ) . nconfig_qx_type = = CONFIG_QX_NAME_AD )
{
/* code */
}
else
{
continue ;
}
cv : : Rect roi123 = m_pDetResult - > pQx_ErrorList - > at ( j ) . roi ;
cv : : Point p123 ;
p123 . x = roi123 . x + roi123 . width * 0.5 ;
p123 . y = roi123 . y + roi123 . height * 0.5 ;
double dis_x = std : : abs ( p123 . x - p . x ) * fs_x ;
double dis_y = std : : abs ( p123 . y - p . y ) * fs_y ;
double dis = std : : sqrt ( dis_x * dis_x + dis_y * dis_y ) ;
if ( dis > dis_T )
{
continue ;
}
num + + ;
sum_dis + = dis ;
}
float avdis = dis_T ;
if ( num > 1 )
{
avdis = sum_dis / ( num - 1 ) ;
}
float fScore = ( dis_T - avdis ) / dis_T ;
double fD = num + fScore ;
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 ) ;
}
m_pdetlog - > AddCheckstr ( PrintLevel_1 , " Density_QX " , " End: processed %zu defects " , m_pDetResult - > pQx_ErrorList - > size ( ) ) ;
return 0 ;
}
