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wheeldetect
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update algo

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newClassify
qushuai777 5 years ago
parent 64b420381a
commit 1d2d81c703
5 changed files with 198 additions and 111 deletions
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52
src/ImageCompare/ImageCompareModel.cpp
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@ -380,7 +380,11 @@ bool ImageCompareModel::readFromFile(string filePath)
{
rInner = (float)fn;
}
fn = fs[IMGCMP_STR_INSIDE_CIRCLE_NUM];
if (!fn.empty())
{
mInnerCircleNum = (double)fn;
}
setFilePath(filePath);
genMask();
@ -734,27 +738,6 @@ void ImageCompareModel::train(const vector<Mat>& vec)
{
Mat originalMat = vec[i];
EDCircles edCircles(originalMat);
std::vector<mCircle> circles = edCircles.getCircles();
float rMax = 0;
float rMaxInside = 0;
const int circlesSize = circles.size();
for (int j = 0; j < circlesSize; ++j)
{
double radius = circles[j].r;
if (radius > rMax)
{
rMax = radius;
}
}
for (int j = 0; j < circlesSize; ++j)
{
double radius = circles[j].r;
if (radius < rMax * MAX_INSIDE_RATIO && radius > rMax * MIN_INSIDE_RATIO)
{
insideCircleNumSum++;
}
}
Vec3f bestCircle;
Point2f p = Point2f(originalMat.cols / 2.0, originalMat.rows / 2.0);
@ -797,12 +780,33 @@ void ImageCompareModel::train(const vector<Mat>& vec)
// {
// int a = 0;
// }
float startX = originalMat.cols / 2.0 - MAX_CIRCLE_RADII;//找最大圆外径，固定直径
float startY = originalMat.rows / 2.0 - MAX_CIRCLE_RADII;
Rect rect(startX, startY, MAX_CIRCLE_RADII * 2, MAX_CIRCLE_RADII * 2);
Mat origianlCenterMat;
originalMat(rect).copyTo(origianlCenterMat);
EDCircles edCircles(origianlCenterMat);
std::vector<mCircle> circles = edCircles.getCircles();
float rMax = 0;
float rMaxInside = 0;
const int circlesSize = circles.size();
for (int j = 0; j < circlesSize; ++j)
{
double radius = circles[j].r;
if (radius > rMax)
{
rMax = radius;
}
}
for (int j = 0; j < circlesSize; ++j)
{
double radius = circles[j].r;
if (radius < rMax * MAX_INSIDE_RATIO && radius > rMax * MIN_INSIDE_RATIO)
{
insideCircleNumSum++;
}
}
centerMatVec.push_back(origianlCenterMat);
tmpVec.push_back(vec[i]);
@ -1868,6 +1872,8 @@ void ImageCompareModelInvoker::operator()(const cv::Range& range) const
int i0 = range.start;
int i1 = range.end;
assert(abs(i1 - i0) == 1);
//if (abs(i1 - i0) == 1)
// return;
m_pModel->parallelDetect(i0, m_pData);
}

8
src/ImageCompare/ImageCompareModel.h
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@ -24,6 +24,7 @@
/*#include "CircleDetector.h"*/
#define COLS_SCALE (float)(1200.0/ 416.0)
//#define COLS_SCALE (float)(1200.0/ 600.0)
using std::set;
using std::map;
using std::fstream;
@ -138,7 +139,7 @@ public:
realWidth(0),
realHeight(0),
rInner(DBL_MAX),
mInnerCircleNum(0)
mInnerCircleNum(0.0)
{};
ImageCompareModel(const ImageCompareModel& model)
: mAlignBaseImg(model.getBaseImg().clone())
@ -172,6 +173,7 @@ public:
mTrueSampleDisMin = model.getDisMin();
meanDiameter = model.getMeanDiamter();
rInner = model.getInnerR();
mInnerCircleNum = model.getInnerCircleNum();
}
void genMask();
@ -231,7 +233,7 @@ public:
Mat getInsideBaseImg() const { return mInSideBaseImg; }
Mat getInsideWeightImg() const { return mInsideWeightMat; }
float getInnerR() const { return rInner; }
float getInnerCircleNum() const { return mInnerCircleNum; }
double getInnerCircleNum() const { return mInnerCircleNum; }
Mat getBaseImg() const { return mAlignBaseImg; }
@ -349,7 +351,7 @@ protected:
float rInner;
float x_aix;
float y_aix;
float mInnerCircleNum;
double mInnerCircleNum;

121
src/algorithm/AlgorithmFluorescence.cpp
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@ -14,8 +14,11 @@
#pragma execution_character_set("utf-8")
#define MIN_INSIDE_RATIO 0.012
#define MAX_INSIDE_RATIO 0.023
#define MAX_CIRCLE_RADII 110
#define MIN_INSIDE_RATIO 0.038
#define MAX_INSIDE_RATIO 0.072
#define INSIDE_NUM_DIS_THRE 1.5
using namespace cv;
using namespace lp;
@ -54,8 +57,11 @@ QString CAlgorithmFluorescence::bestMatch(const QMap<QString, IWheelModel*>* mod
if (!modelMap)
return bestName;
QStringList strDetectModels = pLocal->defectList;
cv::Mat img = pLocal->img;
int similarNum = 0;
const QString hubName1("DH151079");
const QString hubName2("DK151050");
QMap<QString, double> simularModelMap;
while (strDetectModels.size())
{
QString strModelName = strDetectModels.takeFirst();
@ -90,10 +96,16 @@ QString CAlgorithmFluorescence::bestMatch(const QMap<QString, IWheelModel*>* mod
pModel->setIsEnableCache(false);
double dis = pModel->compare(img, NULL, true, 1);
double dis = pModel->compare(pLocal->img, NULL, true, 1);
double disThre = pModel->getDisThre();
double innerCircleNum = pModel->getInnerCircleNum();
if (dis < disThre)
{
similarNum++;
simularModelMap[name] = innerCircleNum;
}
disVec[nIndex] = dis;
/* std::map<float, std::string> disMap;
disMap[dis] = name;*/
if (dis < minDis && dis != -1)
{
minDis = dis;
@ -101,6 +113,7 @@ QString CAlgorithmFluorescence::bestMatch(const QMap<QString, IWheelModel*>* mod
}
nIndex++;
}
if (pMinDis)
{
*pMinDis = minDis;
@ -110,33 +123,96 @@ QString CAlgorithmFluorescence::bestMatch(const QMap<QString, IWheelModel*>* mod
sort(disVec.begin(), disVec.end());
std::copy_n(disVec.begin(), minDisNum, pMinDis);
}
//if (0)
//{
// EDCircles edCircles(img);
// std::vector<mCircle> circles = edCircles.getCircles();
// const int nSize = circles.size();
// float rMax = 0;
if (similarNum < 1)
{
return bestName;
}
const cv::Mat originalMat = pLocal->img;
float startX = originalMat.cols / 2.0 - MAX_CIRCLE_RADII;//找最大圆外径，固定直径
float startY = originalMat.rows / 2.0 - MAX_CIRCLE_RADII;
Rect rect(startX, startY, MAX_CIRCLE_RADII * 2, MAX_CIRCLE_RADII * 2);
cv::Mat centerMat = originalMat(rect).clone();
EDCircles edCircles(centerMat);
std::vector<mCircle> circles = edCircles.getCircles();
const int nSize = circles.size();
float rMax = 0;
for (int i = 0; i < nSize; ++i)
{
float radius = circles[i].r;
if (radius > rMax)
{
rMax = radius;
}
}
double innerCircleNumSum = 0;
double rMaxUp = rMax * MAX_INSIDE_RATIO;
double rMaxLow = rMax * MIN_INSIDE_RATIO;
for (int i = 0; i < nSize; ++i)
{
double radius = circles[i].r;
if (radius < rMaxUp && radius > rMaxLow * MIN_INSIDE_RATIO)
{
innerCircleNumSum++;
}
}
if (bestName.toUpper() == hubName1)
{
if (innerCircleNumSum > 1)
{
bestName = hubName2;
}
}
else if (bestName.toUpper() == hubName2)
{
if (innerCircleNumSum < 2)
{
bestName = hubName1;
}
}
// for (int i = 0; i < nSize; ++i)
//if (similarNum == 1)
//{
// float radius = circles[i].r;
// if (radius > rMax)
// double dis = std::fabs(innerCircleNumSum - simularModelMap.begin().value());
// if (dis > INSIDE_NUM_DIS_THRE)
// {
// rMax = radius;
// bestName = QString();
// }
//}
// float insideCircleNumSum = 0;
// for (int i = 0; i < nSize; ++i)
//if (similarNum > 1)
//{
// auto iterEnd = simularModelMap.constEnd();
// double disMin = DBL_MAX;
// for (auto iter = simularModelMap.constBegin(); iter != iterEnd; ++iter)
// {
// double radius = circles[i].r;
// if (radius < rMax * MAX_INSIDE_RATIO && radius > rMax * MIN_INSIDE_RATIO)
// double dis = std::fabs(innerCircleNumSum - iter.value());
// if (dis < disMin)
// {
// insideCircleNumSum++;
// disMin = dis;
// bestName = iter.key();
// }
// }
// //if()
//}
//auto iterEnd = simularModelMap.constEnd();
//bool bestMatchFlag = false;
//for (auto iter = simularModelMap.constBegin(); iter != iterEnd; ++iter)
//{
// double dis = std::fabs(innerCircleNumSum - iter.value());
// if (dis < INSIDE_NUM_DIS_THRE)
// {
// bestName = iter.key();
// bestMatchFlag = true;
// break;
// }
//}
//if (!bestMatchFlag)
//{
// bestName = QString();
//}
return bestName;
}
@ -164,6 +240,7 @@ int CAlgorithmFluorescence::IImageAnalysis(class IImageObject* pImgObj, TP_ALGOR
bool useDiameter = vMap.value("useDiameter", 0).toBool();
double dD2H = vMap.value("d2h", -1).toDouble();
int nthreshold = vMap.value("Threshold", 15).toInt();
bool bUseBackground = vMap.value("useBackground").toBool();
if (nthreshold <= 0)
nthreshold = 15;

122
src/algorithm/ImageProcess.cpp
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@ -5,7 +5,7 @@
#include "EDLines.h"
#include "EDCircles.h"
//摩轮宏定义 表示该算法用于摩轮型号识别检测
//#define MOTO_DETECT
#define MOTO_DETECT
ImageProcess::ImageProcess()
{
@ -50,66 +50,66 @@ cv::Mat ImageProcess::findCircleObject(const Mat &src, const Mat& backgroundImg,
}
//_EnhanImg_sharpen();
assert(backgroundImg.type() == CV_8UC1);
//Mat detectImg;
//cv::resize(src, detectImg, cv::Size(src.cols / REAIZE, src.rows / REAIZE));
//int bBaseX = detectImg.cols;
//int bBaseY = detectImg.rows;
////if (nThres<=1)
//equalizeHist(detectImg, detectImg);
//detectImg = _EnhanImg_sharpen(detectImg);
//EDCircles edcircles(detectImg);
//vector<mCircle> EDCircle = edcircles.getCircles();
//double maxR = 0;
//int nIndex = -1;
//for (int i = 0; i < EDCircle.size(); i++)
//{
// int startX = EDCircle[i].center.x - EDCircle[i].r;
// int startY = EDCircle[i].center.y - EDCircle[i].r;
// if (startX < 0 || startY <0)
// continue;
// if (EDCircle[i].center.x + EDCircle[i].r>bBaseX || EDCircle[i].center.y + EDCircle[i].r>bBaseY)
// continue;
// if (EDCircle[i].r > maxR)
// {
// maxR = EDCircle[i].r;
// nIndex = i;
// }
//}
//if (nIndex != -1)
//{
// int startX = EDCircle[nIndex].center.x * REAIZE - EDCircle[nIndex].r * REAIZE;
// int startY = EDCircle[nIndex].center.y * REAIZE - EDCircle[nIndex].r* REAIZE;
// double radius = EDCircle[nIndex].r;
// int hight = 2 * radius * REAIZE;
//
// if (startX > 0 && startY > 0 && hight > 0 \
// && startX < src.cols &&startY < src.rows \
// &&hight < src.cols&&hight < src.rows \
// && startX+hight<src.cols && startY+hight<src.rows)
// {
// Mat cutMat = src(Rect(startX, startY, hight, hight));
// if (cutMat.data != NULL)
// {
// //Mat dst;
// //double rate = src.cols*1.0 / ALG_RESIZE_IMAGE_WIDTH;
// //const cv::Size cSize = cv::Size(cutMat.cols*1.0 / rate, cutMat.rows*1.0 / rate);
// //cv::resize(cutMat, dst, cSize);
// if (hight < 50)
// return Mat();
// cv::Point2d center;
// center.x = EDCircle[nIndex].center.x * REAIZE;
// center.y = EDCircle[nIndex].center.y * REAIZE;
// pCircle->ptCenter = center;
// //float fScale = src.cols / ALG_RESIZE_IMAGE_WIDTH;
// //pCircle->fRadius = hight*1.0 / fScale;
// pCircle->fRadius = radius * REAIZE;
// return cutMat;
// }
// }
//}
//return Mat();
Mat detectImg;
cv::resize(src, detectImg, cv::Size(src.cols / REAIZE, src.rows / REAIZE));
int bBaseX = detectImg.cols;
int bBaseY = detectImg.rows;
//if (nThres<=1)
equalizeHist(detectImg, detectImg);
detectImg = _EnhanImg_sharpen(detectImg);
EDCircles edcircles(detectImg);
vector<mCircle> EDCircle = edcircles.getCircles();
double maxR = 0;
int nIndex = -1;
for (int i = 0; i < EDCircle.size(); i++)
{
int startX = EDCircle[i].center.x - EDCircle[i].r;
int startY = EDCircle[i].center.y - EDCircle[i].r;
if (startX < 0 || startY <0)
continue;
if (EDCircle[i].center.x + EDCircle[i].r>bBaseX || EDCircle[i].center.y + EDCircle[i].r>bBaseY)
continue;
if (EDCircle[i].r > maxR)
{
maxR = EDCircle[i].r;
nIndex = i;
}
}
if (nIndex != -1)
{
int startX = EDCircle[nIndex].center.x * REAIZE - EDCircle[nIndex].r * REAIZE;
int startY = EDCircle[nIndex].center.y * REAIZE - EDCircle[nIndex].r* REAIZE;
double radius = EDCircle[nIndex].r;
int hight = 2 * radius * REAIZE;
if (startX > 0 && startY > 0 && hight > 0 \
&& startX < src.cols &&startY < src.rows \
&&hight < src.cols&&hight < src.rows \
&& startX+hight<src.cols && startY+hight<src.rows)
{
Mat cutMat = src(Rect(startX, startY, hight, hight));
if (cutMat.data != NULL)
{
//Mat dst;
//double rate = src.cols*1.0 / ALG_RESIZE_IMAGE_WIDTH;
//const cv::Size cSize = cv::Size(cutMat.cols*1.0 / rate, cutMat.rows*1.0 / rate);
//cv::resize(cutMat, dst, cSize);
if (hight < 50)
return Mat();
cv::Point2d center;
center.x = EDCircle[nIndex].center.x * REAIZE;
center.y = EDCircle[nIndex].center.y * REAIZE;
pCircle->ptCenter = center;
//float fScale = src.cols / ALG_RESIZE_IMAGE_WIDTH;
//pCircle->fRadius = hight*1.0 / fScale;
pCircle->fRadius = radius * REAIZE;
return cutMat;
}
}
}
return Mat();

2
src/interface/ICompareModel.h
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@ -36,6 +36,8 @@ public:
virtual double getDisMin() const = 0;
virtual double getDisMax() const = 0;
virtual double getInnerCircleNum() const = 0;
virtual double getFalseSampleMinDis() const = 0;
virtual double getMeanDiamter() const = 0;

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