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增加try catch捕获异常

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屏蔽circle算法（该算法可能存在bug）
jizhi
bob.pan 4 years ago
parent 84dfb14055
commit d534ed13ee
3 changed files with 143 additions and 126 deletions
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246
src/algorithm/AlgorithmFluorescence.cpp
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@ -51,143 +51,149 @@ CAlgorithmFluorescence::~CAlgorithmFluorescence(void)
//检测算法入口函数 由corctl框架回调
int CAlgorithmFluorescence::IImageAnalysis(class IImageObject* pImgObj, TP_ALGORITHM_OPTION* pOpt, class IDetectorEngine* pDE)
{
qDebug() << "start alg";
QMutexLocker locker(&mutex);
CircleParam cParam;
double dStart = cv::getTickCount();
Mat matSrc = getImage(pImgObj).clone();//获取相机原始图像
QVariantMap vMap = pImgObj->IVarFromUI().toMap();//获取由UI传递过来的算法参数
try {
qDebug() << "start alg";
QMutexLocker locker(&mutex);
CircleParam cParam;
double dStart = cv::getTickCount();
Mat matSrc = getImage(pImgObj).clone();//获取相机原始图像
QVariantMap vMap = pImgObj->IVarFromUI().toMap();//获取由UI传递过来的算法参数
//解析出模板库指针 这里获取的是整个模块库
long long modelMapPtr = vMap.value("modelMap").toLongLong();
QMap<QString, IWheelModel*> *ptr = (QMap<QString, IWheelModel*>*)modelMapPtr;
//获取需要检测的列表 型号名
long long defectListPtr = vMap.value("defectList").toLongLong();
QStringList* strModelListptr = (QStringList*)defectListPtr;
QStringList strModelList;
if(strModelListptr)
strModelList = *(strModelListptr);
int IsCutedImg = vMap.value("IsCutImg", 0).toInt();//裁剪后的轮毂图 检测模式 小图
int th = vMap.value("thickness", -1).toInt();//轮毂厚度 轮毂高度数据
bool useThickness = vMap.value("useThickness", 0).toBool();//是否使用厚度检测判断 匹配时过滤不符合范围的模板
bool useDiameter = vMap.value("useDiameter", 0).toBool();//是否使用直径参数检测判断
double dD2H = vMap.value("d2h", -1).toDouble();
int nthreshold = vMap.value("Threshold", 15).toInt();//图像阈值参数 使用背景图抠图算法时使用
bool bUseBackground = vMap.value("useBackground",false).toBool();//true 使用背景图抠图 false 不使用背景
//解析出模板库指针 这里获取的是整个模块库
long long modelMapPtr = vMap.value("modelMap").toLongLong();
QMap<QString, IWheelModel*> *ptr = (QMap<QString, IWheelModel*>*)modelMapPtr;
//获取需要检测的列表 型号名
long long defectListPtr = vMap.value("defectList").toLongLong();
QStringList* strModelListptr = (QStringList*)defectListPtr;
QStringList strModelList;
if(strModelListptr)
strModelList = *(strModelListptr);
int IsCutedImg = vMap.value("IsCutImg", 0).toInt();//裁剪后的轮毂图 检测模式 小图
int th = vMap.value("thickness", -1).toInt();//轮毂厚度 轮毂高度数据
bool useThickness = vMap.value("useThickness", 0).toBool();//是否使用厚度检测判断 匹配时过滤不符合范围的模板
bool useDiameter = vMap.value("useDiameter", 0).toBool();//是否使用直径参数检测判断
double dD2H = vMap.value("d2h", -1).toDouble();
int nthreshold = vMap.value("Threshold", 15).toInt();//图像阈值参数 使用背景图抠图算法时使用
bool bUseBackground = vMap.value("useBackground",false).toBool();//true 使用背景图抠图 false 不使用背景
int ratioType = vMap.value("RatioType").toInt();//偏距检测模式 启用方式
double ratioVal = vMap.value("Ratio").toDouble();//偏距系数
bool bEqual = vMap.value("bEqual").toBool();//使用使用图像增强
int filterSize = vMap.value("filterSize").toInt();//过滤圆大小
cParam.CirclePolarity = vMap.value("Circle_Polarity",0).toInt();
cParam.CircleACThres = vMap.value("Circle_ACThres",3).toInt();
cParam.CircleEdgeWidth = vMap.value("Circle_EdgeWidth",3).toInt();
cParam.filterSize = filterSize;
if (nthreshold <= 0)
nthreshold = 15;
QVariantMap rltMap;//算法检测结果值 输出到UI用
rltMap.insert("ratioVal", ratioVal);
luffy_base::luffyCircle lCircle;
static bool bReload = false;//背景图加载判断
Mat matBack = getBackGroundImage(pImgObj, bReload);//获取背景图
int ratioType = vMap.value("RatioType").toInt();//偏距检测模式 启用方式
double ratioVal = vMap.value("Ratio").toDouble();//偏距系数
bool bEqual = vMap.value("bEqual").toBool();//使用使用图像增强
int filterSize = vMap.value("filterSize").toInt();//过滤圆大小
cParam.CirclePolarity = vMap.value("Circle_Polarity",0).toInt();
cParam.CircleACThres = vMap.value("Circle_ACThres",3).toInt();
cParam.CircleEdgeWidth = vMap.value("Circle_EdgeWidth",3).toInt();
cParam.filterSize = filterSize;
if (nthreshold <= 0)
nthreshold = 15;
QVariantMap rltMap;//算法检测结果值 输出到UI用
rltMap.insert("ratioVal", ratioVal);
luffy_base::luffyCircle lCircle;
static bool bReload = false;//背景图加载判断
Mat matBack = getBackGroundImage(pImgObj, bReload);//获取背景图
Mat matMatch;//抠图后的图像 目标图像
if (IsCutedImg == 0) //使用的是原始图像 需要执行圆查找算法找出 轮毂
{
//原始图像的size和背景图size不匹配， 直接返回错误提示
if (bUseBackground == true && (matSrc.size().height != matBack.size().height || matSrc.size().width != matBack.size().width))
Mat matMatch;//抠图后的图像 目标图像
if (IsCutedImg == 0) //使用的是原始图像 需要执行圆查找算法找出 轮毂
{
rltMap.insert("error", 0);
pImgObj->IVariantMapToUI(rltMap);
bReload = true;
return 0;
//原始图像的size和背景图size不匹配， 直接返回错误提示
if (bUseBackground == true && (matSrc.size().height != matBack.size().height || matSrc.size().width != matBack.size().width))
{
rltMap.insert("error", 0);
pImgObj->IVariantMapToUI(rltMap);
bReload = true;
return 0;
}
else{
bReload = false;
}
if (bUseBackground == true)//使用背景图 做减法找圆
{
Point2f centerPoint;
double radius = 0;
matMatch = ImageProcess::findCircleByBackground(matSrc, matBack, centerPoint, radius, bEqual, filterSize, cParam);
lCircle.ptCenter = centerPoint;
lCircle.fRadius = radius;
}
else {
//不需要 背景图找圆算法
Point2f centerPoint;
double radius = 0;
matMatch = ImageProcess::findCircle(matSrc, centerPoint, radius, bEqual,filterSize,cParam);
lCircle.ptCenter = centerPoint;
lCircle.fRadius = radius;
}
if (matMatch.cols >= 900 || matMatch.rows >= 900)//控制检测图像大小不能超过这个范围
{
cv::resize(matMatch, matMatch, cv::Size(matMatch.cols / 2, matMatch.rows / 2));
lCircle.fRadius = lCircle.fRadius / 2;
}
}
else{
bReload = false;
matMatch = matSrc;
}
if (bUseBackground == true)//使用背景图 做减法找圆
Result2Ui *pResult = new Result2Ui;
pResult->m_pixSrc = QtCVUtils::cvMatToQPixmap(matSrc);//!>原图像发送值UI 用于保存备份和调试
if (matMatch.empty())//抠图为空，表示抠图失败，直接返回错误
{
Point2f centerPoint;
double radius = 0;
matMatch = ImageProcess::findCircleByBackground(matSrc, matBack, centerPoint, radius, bEqual, filterSize, cParam);
lCircle.ptCenter = centerPoint;
lCircle.fRadius = radius;
}
else {
//不需要 背景图找圆算法
Point2f centerPoint;
double radius = 0;
matMatch = ImageProcess::findCircle(matSrc, centerPoint, radius, bEqual,filterSize,cParam);
lCircle.ptCenter = centerPoint;
lCircle.fRadius = radius;
rltMap.insert("noCircle", 0);
long long varRlt = (long long)pResult;
rltMap.insert("result", varRlt);
pImgObj->IVariantMapToUI(rltMap);
return 0;
}
if (matMatch.cols >= 900 || matMatch.rows >= 900)//控制检测图像大小不能超过这个范围
{
cv::resize(matMatch, matMatch, cv::Size(matMatch.cols / 2, matMatch.rows / 2));
lCircle.fRadius = lCircle.fRadius / 2;
double dDiameter = dD2H * lCircle.fRadius * 2;//计算轮毂直径
//打包相关数据
CLocalWheel wheelLocal;
wheelLocal.defectList = strModelList;
wheelLocal.img = matMatch.clone();
wheelLocal.height = th;
wheelLocal.diameter = dDiameter;
wheelLocal.useHeight = useThickness;
wheelLocal.useDiameter = useDiameter;
wheelLocal.ratioType = ratioType;
wheelLocal.dRatioVal = ratioVal;
//开始匹配
if (!matMatch.empty() && ptr && ptr->size() > 0) {
vector<double> minDisVec(ptr->size());//初始化模板匹配分数值
QString str = bestMatch(ptr, &wheelLocal, &(minDisVec[0]), minDisVec.size());
pResult->m_strModel = str;
pResult->m_dMinDis = minDisVec[0];
if (ptr->contains(str) && ptr->value(str)->getImageComModel()) {
ICompareModel *pModel = ptr->value(str)->getImageComModel();
double d = pModel->getDisThre();
double dValue = (d - minDisVec[0]) / d * 0.4 + 0.6;
pResult->m_dScore = dValue;
}
}
}
else{
matMatch = matSrc;
}
Result2Ui *pResult = new Result2Ui;
pResult->m_pixSrc = QtCVUtils::cvMatToQPixmap(matSrc);//!>原图像发送值UI 用于保存备份和调试
if (matMatch.empty())//抠图为空，表示抠图失败，直接返回错误
{
rltMap.insert("noCircle", 0);
qDebug() << "pull result";
QImage img = QtCVUtils::cvMatToQImage(matMatch);
pResult->m_pixResult = QtCVUtils::cvMatToQPixmap(matMatch);// .scaled(125, 125);
pResult->m_dDiameter = dDiameter;
pResult->m_dThickness = th;
//!>传递检测结果到UI
//pImgObj->IDrawImage(img.scaled(300, 300));//!>显示结果图片到UI的第二个窗口上
double dTime = (cv::getTickCount() - dStart) / cv::getTickFrequency();
pResult->m_dRunTime = dTime;
long long varRlt = (long long)pResult;
rltMap.insert("result", varRlt);
pImgObj->IVariantMapToUI(rltMap);
return 0;
qDebug() << "finish alg";
return 1;
}
double dDiameter = dD2H * lCircle.fRadius * 2;//计算轮毂直径
//打包相关数据
CLocalWheel wheelLocal;
wheelLocal.defectList = strModelList;
wheelLocal.img = matMatch.clone();
wheelLocal.height = th;
wheelLocal.diameter = dDiameter;
wheelLocal.useHeight = useThickness;
wheelLocal.useDiameter = useDiameter;
wheelLocal.ratioType = ratioType;
wheelLocal.dRatioVal = ratioVal;
//开始匹配
if (!matMatch.empty() && ptr && ptr->size() > 0) {
vector<double> minDisVec(ptr->size());//初始化模板匹配分数值
QString str = bestMatch(ptr, &wheelLocal, &(minDisVec[0]), minDisVec.size());
pResult->m_strModel = str;
pResult->m_dMinDis = minDisVec[0];
if (ptr->contains(str) && ptr->value(str)->getImageComModel()) {
ICompareModel *pModel = ptr->value(str)->getImageComModel();
double d = pModel->getDisThre();
double dValue = (d - minDisVec[0]) / d * 0.4 + 0.6;
pResult->m_dScore = dValue;
}
catch (...) {
qDebug() << "algo run Error " << __FUNCTION__;
return 1;
}
qDebug() << "pull result";
QImage img = QtCVUtils::cvMatToQImage(matMatch);
pResult->m_pixResult = QtCVUtils::cvMatToQPixmap(matMatch);// .scaled(125, 125);
pResult->m_dDiameter = dDiameter;
pResult->m_dThickness = th;
//!>传递检测结果到UI
//pImgObj->IDrawImage(img.scaled(300, 300));//!>显示结果图片到UI的第二个窗口上
double dTime = (cv::getTickCount() - dStart) / cv::getTickFrequency();
pResult->m_dRunTime = dTime;
long long varRlt = (long long)pResult;
rltMap.insert("result", varRlt);
pImgObj->IVariantMapToUI(rltMap);
qDebug() << "finish alg";
return 1;
}
//模板匹配流程

9
tpvs17/tpMain/QAlgParamDlg.cpp
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@ -127,9 +127,12 @@ Q_SLOT void QAlgParamDlg::onChangeBG()
createfile->remove(DstPath);
//}
}
if (!QFile::copy(sourcePath, DstPath)) {
//return false;
}
// if (!QFile::copy(sourcePath, DstPath)) {
// //return false;
// }
QImage img;
img.load(sourcePath);
img.save(DstPath);
//emit sgChangeBG(DstPath);
QMessageBox infobox(QMessageBox::Information, tr("提示"), tr("背景图更新完成，请重启本软件."), QMessageBox::Yes, NULL);
infobox.setWindowIcon(QIcon(":/image/leaper"));

14
tpvs17/tpMain/lpMainWin.cpp
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@ -23,9 +23,9 @@
#include <QProcess>
#include "lpCryptokey.h"
#define VERSION_HUB "3.0.1.7"
#define VERSION_HUB "3.0.2.0"
#define VERSION_ALG "3.0.1.5"
#define UPDATE_TIME "2021-10-09"
#define UPDATE_TIME "2021-11-24"
#pragma execution_character_set("utf-8")
lpMainWin::lpMainWin(QWidget *parent)
@ -586,7 +586,10 @@ void lpMainWin::INewCameraImage(const QString& camKey, QImage img)
/*多线程发送算法结果*/
void lpMainWin::IVariantMapToUI(const QString& camKey, const QVariantMap& vMap)
{
{
try {
m_glbalRatio = 0;
emit(sgShowImgState(tr("显示识别结果")));
Result2Ui *pResult = (Result2Ui*)vMap.value("result").toLongLong();
@ -708,6 +711,11 @@ void lpMainWin::IVariantMapToUI(const QString& camKey, const QVariantMap& vMap)
m_pCtrl->saveResult(pResult);
delete pResult;
}
catch(...)
{
qWarning() << "dump result " << __FUNCTION__;
}
}
/*多线程获取算法参数*/

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