diff --git a/Main_TrafficSignRecognition.cpp b/Main_TrafficSignRecognition.cpp index e83b4f1..b812a5f 100644 --- a/Main_TrafficSignRecognition.cpp +++ b/Main_TrafficSignRecognition.cpp @@ -32,12 +32,12 @@ int Frame_pos;//µ±Ç°Ö¡Î»Öà bool isTrain=false;//traffic signs bool TRAIN=false;//TL bool HORZ=false;//TL -bool TLRecTrain=true;//是否训练信号灯识别分类器 -bool saveFlag=true; +bool TLRecTrain=false;//是否训练信号灯识别分类器 +//bool saveFlag=true; Mat re_src;//for traffic signs detection IplImage *resize_TLR=cvCreateImage(Size(800,600),8,3); -vector found_TL;//the bounding box for traffic lights +//vector found_TL;//the bounding box for traffic lights vector found_TSR;//the bounding box for traffic signs Scalar colorMode[]={CV_RGB(255,255,0),CV_RGB(0,0,255),CV_RGB(255,0,0)};//the color mode for the traffic sign detection(Y,B,R) CvANN_MLP nnetwork,nnetwork_RoundRim,nnetwork_RectBlue;//neural networks for three different kinds of traffic signs @@ -169,9 +169,10 @@ void savePCA(string filepath,string outputPath) void TLDetectionPerFrame(IplImage *frame,float *TLDSend) { - IplImage *imageSeg=NULL,*imageNoiseRem =NULL; + IplImage *imageSeg=NULL; + //IplImage*imageNoiseRem =NULL; - found_TL.clear(); + //found_TL.clear(); cvResize(frame,resize_TLR); /*//此处先使用顶帽算法，再使用闭操作 IplImage* tmpGray=cvCreateImage(cvSize(frame->width,frame->height),IPL_DEPTH_8U,1); @@ -193,16 +194,11 @@ void TLDetectionPerFrame(IplImage *frame,float *TLDSend) cvReleaseStructuringElement(&t);*/ imageSeg = colorSegmentationTL(resize_TLR); - - - IplImage *closeImg=cvCreateImage(Size(imageSeg->width,imageSeg->height),imageSeg->depth,imageSeg->nChannels); IplConvKernel *t=cvCreateStructuringElementEx(7,7,3,3,CV_SHAPE_ELLIPSE); cvMorphologyEx(imageSeg,closeImg,NULL,t,CV_MOP_CLOSE); - cvShowImage("closeImg",closeImg); - - - imageNoiseRem=noiseRemoval(imageSeg); + //cvShowImage("closeImg",closeImg); + //imageNoiseRem=noiseRemoval(imageSeg); #if ISDEBUG_TL cvNamedWindow("imgseg"); cvShowImage("imgseg",imageSeg); @@ -213,7 +209,7 @@ void TLDetectionPerFrame(IplImage *frame,float *TLDSend) //componentExtraction(imageNoiseRem,resize_TLR,TLDSend,found_TL); componentExtractionTL(closeImg,resize_TLR,TLDSend); cvReleaseImage(&imageSeg); - cvReleaseImage(&imageNoiseRem); + //cvReleaseImage(&imageNoiseRem); cvReleaseImage(&closeImg); } @@ -657,7 +653,7 @@ void openMP_MultiThreadVideo() bool saveFlag=false; IplImage * frame,*copyFrame; float connectResult[8]={0,0,0,0,0,0,0,0}; - CvCapture * cap=cvCreateFileCapture("D:\\JY\\JY_TrainingSamples\\changshu data\\TL\\TL_HORZ.avi"); + CvCapture * cap=cvCreateFileCapture("D:\\JY\\JY_TrainingSamples\\changshu data\\TL\\RedFalsePositive.avi"); //CvCapture * cap=cvCreateFileCapture("D:\\JY\\JY_TrainingSamples\\2014.11.16\\1_clip.mp4"); float startTime=1000*(float)getTickCount()/getTickFrequency(); CvVideoWriter * writer=NULL; @@ -714,9 +710,9 @@ void openMP_MultiThreadVideo() cvShowImage("TL",resize_TLR); cvWaitKey(5); //show the detection result of TSR - //namedWindow("TSR"); - //imshow("TSR",re_src); - //waitKey(5); + namedWindow("TSR"); + imshow("TSR",re_src); + waitKey(5); #endif if (saveFlag) { diff --git a/TLRec.xml b/TLRec.xml index a76f3ba..dc0744a 100644 --- a/TLRec.xml +++ b/TLRec.xml @@ -18,282 +18,281 @@ 3 <_> - -3.66984954e-004 -1.64220128e-002 4.14069593e-002 9.29261616e-004 - -1.08939903e-002 6.83433609e-005 0. -9.28339869e-005 - -2.45595817e-003 7.83397555e-002 4.14817408e-002 5.32875629e-003 - -8.86171982e-002 -3.89052974e-003 -5.43939299e-004 - -3.62524157e-003 -1.09921424e-002 6.62939902e-003 -1.87368486e-002 - -1.37168482e-001 2.67514829e-002 1.00597076e-001 4.93561514e-002 - -2.07548365e-002 -8.74130707e-003 -1.66603848e-002 - -2.78377347e-003 -1.29583469e-002 -6.64563105e-002 2.70433282e-003 - -2.41761599e-002 -2.16947105e-002 -2.98039149e-003 - -1.33113917e-002 -3.23858969e-002 -7.25760823e-003 8.95305201e-002 - 5.90834767e-002 -3.44358571e-002 -6.76304027e-002 -5.75542171e-003 - -1.92993023e-002 -3.33700590e-002 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-9.19925496e-002 9.12545342e-003 2.50382815e-002 + 8.02188292e-002 1.09554254e-001 3.26660350e-002 -4.00755554e-003 + -2.97789671e-003 -9.90046486e-002 -3.61461155e-002 6.19677454e-002 + 3.41240913e-002 5.74139021e-002 2.10940912e-002 -4.18583443e-003 + 4.26754728e-003 3.84154450e-003 -9.62266475e-002 -5.97726852e-002 + -3.29174288e-002 -5.74878789e-003 6.78805038e-002 8.05041790e-002 + 7.94399437e-003 -8.44845083e-003 -2.49379911e-002 -5.09865358e-002 + -9.53830257e-002 -5.55639947e-003 1.51573662e-002 7.60720894e-002 + 7.75261074e-002 1.38993131e-003 6.91420352e-003 -7.51895085e-003 + -5.21787927e-002 <_> 1 - -1.1694794282915051e-001 + -1.1816981001489091e-001 1. 0 <_> 1 - -1.3657966967026666e-001 + -1.6551418797444781e-001 1. 1 <_> 1 - 5.4147968730023616e-002 + -4.7125192473508958e-002 1. diff --git a/TrafficLightDetection/RectangleDetection.cpp b/TrafficLightDetection/RectangleDetection.cpp index 752b8c1..78d75e6 100644 --- a/TrafficLightDetection/RectangleDetection.cpp +++ b/TrafficLightDetection/RectangleDetection.cpp @@ -7,7 +7,7 @@ void GetImageRect(IplImage* orgImage, CvRect rectInImage, IplImage* imgRect) CvSize size; size.width=rectInImage.width; size.height=rectInImage.height; - //result=cvCreateImage( size, orgImage->depth, orgImage->nChannels ); + //ͼȡͼ cvSetImageROI(orgImage,rectInImage); cvCopy(orgImage,result); @@ -50,28 +50,24 @@ bool isLighInBox(Mat src) return false; } -bool rectangleDetection(IplImage* inputImage,IplImage* srcImage,CvRect iRect,int iColor,int* p1,int* p2)//p1Ϊǰλp2Ϊתλ +void rectangleDetection(IplImage* inputImage,IplImage* srcImage,CvRect iRect,int iColor,int* p1,int* p2)//p1Ϊǰλp2Ϊתλ { - const int iWidth = inputImage->width; const int iHeight = inputImage->height; - IplImage* imageGrayScale = cvCreateImage(cvSize(iWidth,iHeight),IPL_DEPTH_8U,1); - int iWidthStep = imageGrayScale->widthStep; - cvCvtColor(srcImage,imageGrayScale,CV_BGR2GRAY); + + //ˮƽֱ״̬ bool VerticalReturnStatus = false; bool HorzReturnStatus=false; // int HorzRectHeight=(iRect.width+iRect.height)/2 + 6; - int HorzRectWidth=3*(HorzRectHeight-4)+6; + int HorzRectWidth=3*(HorzRectHeight-4)+3; int HorzRectX1=0, HorzRectY1=0; int HorzRectX2=0, HorzRectY2=0; - //int iSrcWidthStep = srcImage->widthStep; - //thresholding for graylevel differences between seedpoints and its neibours - const int grayThresholding =70;//70 + const int grayThresholding =80;//70 const int RatioThreshold = 55;//кɫռ // @@ -89,62 +85,98 @@ bool isLighInBox(Mat src) HorzRectX1=iRect.x-HorzRectWidth/3*2; } + //ֱⴰ iDrawRectY2 = iDrawRectY1 + iDrawRectHeight; iDrawRectX1 = iRect.x-3; iDrawRectX2 = iDrawRectX1 + iDrawRectWidth; + //ˮƽ HorzRectX2= HorzRectX1+HorzRectWidth; HorzRectY1= iRect.y-3; HorzRectY2= HorzRectY1+HorzRectHeight; if(HorzRectX1<0 || HorzRectY1<0 || HorzRectX2>=iWidth || HorzRectY2>=iHeight) { - cvReleaseImage(&imageGrayScale);//when return the result, the image must be released, otherwise,the memory will be leaked - return HorzReturnStatus; + //cvReleaseImage(&imageGrayScale);//when return the result, the image must be released, otherwise,the memory will be leaked + return; } if( iDrawRectX1<0 || iDrawRectY1<0 || iDrawRectX2>=iWidth || iDrawRectY2>=iHeight) { - cvReleaseImage(&imageGrayScale);//when return the result, the image must be released, otherwise,the memory will be leaked - return VerticalReturnStatus; + //cvReleaseImage(&imageGrayScale);//when return the result, the image must be released, otherwise,the memory will be leaked + return; } + + //ֱͳƺɫر + CvRect VerticalRect; + VerticalRect.x=iDrawRectX1; + VerticalRect.y=iDrawRectY1; + VerticalRect.width=iDrawRectWidth; + VerticalRect.height=iDrawRectHeight; + IplImage*VerticalLight = cvCreateImage(cvSize(iDrawRectWidth,iDrawRectHeight),srcImage->depth,srcImage->nChannels); + GetImageRect(srcImage,VerticalRect,VerticalLight); + IplImage *VerticalGrayLight=cvCreateImage(cvSize(iDrawRectWidth,iDrawRectHeight),IPL_DEPTH_8U,1); + cvCvtColor(VerticalLight,VerticalGrayLight,CV_BGR2GRAY); + cvThreshold(VerticalGrayLight,VerticalGrayLight,0,255,CV_THRESH_OTSU); + + + /* + int iWidthStep = VerticalGrayLight->widthStep; int sum=0; - int grayValue=0; - //int bValue=0,gValue=0,rValue=0; - //int bgrMax=0,bgrMin=0; - unsigned char* pData; - //unsigned char* pSrcData; - for(int j=iDrawRectY1; j<=iDrawRectY2; j++){ - pData = (unsigned char*)imageGrayScale->imageData + j*iWidthStep; - for(int i=iDrawRectX1; i<=iDrawRectX2; i++){ - grayValue = pData[i]; - if((grayValue<=grayThresholding)) + int VerticalGrayValue=0; + unsigned char* pDataVertical; + for(int j=0; jimageData + j*iWidthStep; + for(int i=0; idepth,srcImage->nChannels); + GetImageRect(srcImage,HorzRect,HorzLight); + IplImage *HorzGrayLight=cvCreateImage(cvSize(HorzRectWidth,HorzRectHeight),IPL_DEPTH_8U,1); + cvCvtColor(HorzLight,HorzGrayLight,CV_BGR2GRAY); + cvThreshold(HorzGrayLight,HorzGrayLight,0,255,CV_THRESH_OTSU); + + +/* + int HorzWidthStep = HorzGrayLight->widthStep; int HorzSum=0; - for(int j=HorzRectY1; j<=HorzRectY2; j++){ - pData = (unsigned char*)imageGrayScale->imageData + j*iWidthStep; - for(int i=HorzRectX1; i<=HorzRectX2; i++){ - grayValue = pData[i]; - if((grayValue<=grayThresholding)) + int HorzGrayValue=0; + unsigned char* pDataHorz; + for(int j=0; jimageData + j*HorzWidthStep; + for(int i=0; i=RatioThreshold&&VerticalBlackRatio<=90) + //cout<<"Horz Ratio:"<=RatioThreshold&&VerticalBlackRatio<=93) VerticalReturnStatus = true; else if (HorzBlackRatio>=RatioThreshold&&HorzBlackRatio<=90) { @@ -204,9 +238,9 @@ bool isLighInBox(Mat src) //cout<<"ֹת"< &found_filtered); -bool rectangleDetection(IplImage* inputImage,IplImage* srcImage,CvRect iRect,int iColor,int* p1,int* p2); +void rectangleDetection(IplImage* inputImage,IplImage* srcImage,CvRect iRect,int iColor,int* p1,int* p2); bool BoxDetectTL(Mat src_test,HOGDescriptor &myHOG,bool HORZ); bool BlackAroundLight(IplImage* srcImg,CvRect iRect); int RecognizeLight(IplImage* srcImg,CvRect iRect);//return the TL recognition result diff --git a/isTL.xml b/isTL.xml index 24a59eb..ce6a3ee 100644 --- a/isTL.xml +++ b/isTL.xml @@ -18,94 +18,94 @@ 1 <_> - 1.56036884e-001 -1.55410200e-001 -2.01866969e-001 4.14274074e-002 - 6.94726929e-002 4.65383753e-002 6.28277808e-002 7.09838569e-002 - 1.21663369e-001 7.31278360e-002 -1.64729375e-002 -2.04167292e-001 - -6.82259202e-002 -5.51611278e-003 2.17052996e-002 4.86485884e-002 - 4.98296283e-002 1.07196525e-001 7.82411993e-002 -2.24886507e-001 - -2.71874696e-001 -9.86494794e-002 1.25687122e-001 1.20658644e-001 - 4.06613164e-002 6.79099038e-002 1.53325468e-001 1.22529693e-001 - -4.00939249e-002 -9.35682580e-002 -5.86220473e-002 4.66422997e-002 - 3.42046395e-002 5.45608625e-003 3.03352214e-002 1.17306046e-001 - 6.92723831e-003 6.97051361e-002 -6.36906177e-002 -6.82732761e-002 - -6.67658150e-002 -3.82032134e-002 -4.55159927e-003 2.07766555e-002 - -2.27734707e-002 1.50575906e-001 1.68935061e-001 5.93921281e-002 - 3.84022370e-002 -7.74629042e-002 -1.84293836e-001 -2.11851209e-001 - -1.05937727e-001 -3.74147631e-002 6.98328540e-002 7.32415617e-002 - -5.12451008e-002 -2.26342455e-002 -6.47476166e-002 - -7.19183758e-002 1.16215432e-002 3.70402820e-002 1.14437707e-001 - 1.41274124e-001 1.09327637e-001 1.11195529e-002 4.78796884e-002 - -1.58648808e-002 -1.43218726e-001 -1.40580520e-001 - -1.93535332e-002 3.69007885e-002 2.15092018e-001 1.11557022e-001 - 7.01970384e-002 8.37866068e-002 1.06217340e-003 -5.64414263e-002 - -2.54340291e-001 -1.62821755e-001 -8.33874196e-002 1.94156289e-001 - 1.27943456e-001 1.40295029e-001 1.18830234e-001 8.28565806e-002 - -1.19835045e-002 -3.01721036e-001 -1.46937117e-001 - -5.95533922e-002 4.30338718e-002 1.03374720e-001 7.56448135e-002 - 8.74492750e-002 6.01874851e-002 1.44489827e-002 -2.03338310e-001 - -2.50614304e-002 -7.31143868e-003 2.15247856e-003 1.94987506e-001 - 1.68845028e-001 2.12656215e-001 1.46948799e-001 -7.68441036e-002 - -2.93781132e-001 -5.76775894e-002 4.03338559e-002 2.39075460e-002 - -5.97934760e-002 -1.29885927e-001 -1.26589030e-001 - -3.76855955e-002 2.65170615e-002 -3.86675149e-002 1.66915245e-002 - 5.94513267e-002 5.82416579e-002 1.35351392e-002 1.81127973e-002 - -7.63457268e-002 -7.28994608e-002 -7.00188354e-002 - -6.26587495e-002 2.41685063e-002 5.79076186e-002 3.81255858e-002 - 6.19256832e-002 7.89657235e-002 9.50867012e-002 -8.64683390e-002 - -1.49970874e-001 -5.56673892e-002 -8.72978941e-002 - -1.47175556e-002 7.43101016e-002 8.60797539e-002 1.55985773e-001 - 2.14912836e-002 -9.33349207e-002 -2.01558113e-001 -8.49207267e-002 - -3.82880606e-002 2.19198549e-003 4.72889803e-002 2.18127258e-002 - 5.54234460e-002 -1.36239165e-002 -8.53878185e-002 -7.84353763e-002 - -2.42070341e-003 3.55904326e-002 7.10110217e-002 1.31019307e-002 - 3.94776613e-002 9.54635814e-002 1.94141939e-002 -5.31869344e-002 - -7.16326162e-002 -6.74846098e-002 -1.08612999e-002 1.03373993e-002 - 9.56162512e-002 6.90407678e-002 1.30511761e-001 -3.20903733e-002 - -8.12359825e-002 -1.25160113e-001 -4.79309522e-002 - -2.53596101e-002 -2.74991486e-002 5.67354336e-002 -8.64330903e-002 - -4.05427217e-002 -1.18163088e-002 1.21157393e-002 4.48283106e-002 - -1.40989944e-002 2.72303168e-002 -5.72508126e-002 -5.24675101e-002 - 5.78021333e-002 5.38130589e-002 4.91915084e-002 -8.24092794e-003 - -1.21752499e-002 -1.86048046e-001 -4.19445103e-003 - -4.51702848e-002 -6.16904162e-002 2.63639558e-002 5.48340529e-002 - 1.80467650e-001 1.82503425e-002 -1.19063802e-001 -2.52490520e-001 - 3.45796384e-002 6.63022231e-003 -6.80198073e-002 -1.09015055e-001 - -5.09467274e-002 3.11760008e-002 6.05069995e-002 7.51648247e-002 - -3.63552012e-002 4.68737707e-002 -5.29397875e-002 4.06733826e-002 - 1.09812459e-002 -1.28183013e-003 1.42601907e-001 8.39142576e-002 - 6.09576069e-002 3.59109007e-002 9.33900476e-002 1.46967284e-002 - 5.96003756e-002 4.65553291e-002 3.99092101e-002 1.34020954e-001 - 4.31154855e-002 -1.50818139e-001 -1.81441188e-001 -1.20097004e-001 - 5.35494797e-002 1.07319333e-001 8.15097094e-002 5.38924783e-002 - 1.01222783e-001 1.68098286e-002 -1.16695344e-001 -8.84555280e-002 - -1.16753310e-001 2.13977005e-002 1.85226664e-001 8.34598839e-002 - 6.94932863e-002 1.57387510e-001 5.72885796e-002 -1.63378760e-001 - -3.25934857e-001 -2.37415224e-001 1.69544905e-001 2.95434535e-001 - 1.90200031e-001 6.92697465e-002 1.96215540e-001 7.86449611e-002 - -7.73894787e-002 -1.47447020e-001 -2.14115113e-001 2.32258551e-002 - 6.89294562e-002 6.43628836e-002 4.43876982e-002 3.01110512e-003 - -6.06745295e-002 -5.05361594e-002 -8.62531886e-002 - -8.73161629e-002 -3.65096033e-002 2.56805625e-002 -7.61494339e-002 - -5.57822809e-002 -5.39904162e-002 3.33092250e-002 1.42641198e-002 - -1.63426697e-002 3.33168730e-003 -3.77073623e-002 1.90925896e-001 - 1.06870264e-001 4.45638895e-002 8.55093524e-002 -2.20268220e-002 - -4.56462055e-002 -7.82874003e-002 -1.21429577e-001 - -1.40921146e-001 6.12106845e-002 4.76668067e-002 -1.11054555e-002 - -5.34440838e-002 5.25335632e-002 5.18498681e-002 5.09985983e-002 - 1.12468889e-002 -1.26223594e-001 -7.37349465e-002 -1.35690689e-001 - -1.25087157e-001 -3.67802791e-002 3.56901400e-002 5.01857586e-002 - 2.41782591e-002 5.45808896e-002 1.14228902e-002 -7.66681880e-002 - -1.17870860e-001 -2.02913478e-001 2.50498392e-002 1.73717082e-001 - 1.22337490e-001 1.39574811e-001 7.24396557e-002 -5.26285097e-002 - -7.60265533e-003 -1.58792377e-001 -1.69140503e-001 - -2.09366214e-002 2.33074352e-002 1.07788809e-001 7.67055303e-002 - 1.04977414e-001 7.36823827e-002 1.73312854e-002 -2.16749817e-001 - -2.14010343e-001 7.24725053e-002 1.69069335e-001 1.91567838e-001 - 1.33366734e-001 1.07279412e-001 2.28625932e-003 + 1.56036898e-001 -1.55410200e-001 -2.01866969e-001 4.14274186e-002 + 6.94726706e-002 4.65383753e-002 6.28277734e-002 7.09838569e-002 + 1.21663362e-001 7.31278434e-002 -1.64729469e-002 -2.04167292e-001 + -6.82259426e-002 -5.51613281e-003 2.17053033e-002 4.86485809e-002 + 4.98296209e-002 1.07196525e-001 7.82412142e-002 -2.24886537e-001 + -2.71874666e-001 -9.86494496e-002 1.25687107e-001 1.20658636e-001 + 4.06613201e-002 6.79099038e-002 1.53325468e-001 1.22529693e-001 + -4.00939435e-002 -9.35682282e-002 -5.86220697e-002 4.66423184e-002 + 3.42046581e-002 5.45608578e-003 3.03352084e-002 1.17306061e-001 + 6.92724856e-003 6.97051510e-002 -6.36906028e-002 -6.82732835e-002 + -6.67658150e-002 -3.82032208e-002 -4.55160718e-003 2.07766537e-002 + -2.27734968e-002 1.50575921e-001 1.68935046e-001 5.93921281e-002 + 3.84022444e-002 -7.74628818e-002 -1.84293881e-001 -2.11851209e-001 + -1.05937749e-001 -3.74147631e-002 6.98328465e-002 7.32415840e-002 + -5.12451082e-002 -2.26342697e-002 -6.47475719e-002 + -7.19183385e-002 1.16215441e-002 3.70402820e-002 1.14437707e-001 + 1.41274124e-001 1.09327652e-001 1.11195538e-002 4.78796922e-002 + -1.58648528e-002 -1.43218711e-001 -1.40580505e-001 + -1.93535462e-002 3.69007923e-002 2.15092018e-001 1.11557007e-001 + 7.01970458e-002 8.37866142e-002 1.06217514e-003 -5.64414524e-002 + -2.54340291e-001 -1.62821770e-001 -8.33874047e-002 1.94156289e-001 + 1.27943471e-001 1.40295029e-001 1.18830226e-001 8.28565732e-002 + -1.19834971e-002 -3.01721066e-001 -1.46937102e-001 + -5.95533811e-002 4.30338643e-002 1.03374705e-001 7.56448135e-002 + 8.74492824e-002 6.01874851e-002 1.44489827e-002 -2.03338295e-001 + -2.50614360e-002 -7.31144054e-003 2.15250137e-003 1.94987506e-001 + 1.68845043e-001 2.12656215e-001 1.46948785e-001 -7.68440813e-002 + -2.93781132e-001 -5.76776154e-002 4.03338484e-002 2.39075683e-002 + -5.97934909e-002 -1.29885927e-001 -1.26589000e-001 + -3.76855955e-002 2.65170522e-002 -3.86675261e-002 1.66915301e-002 + 5.94513267e-002 5.82416505e-002 1.35351382e-002 1.81127824e-002 + -7.63457417e-002 -7.28994459e-002 -7.00188205e-002 + -6.26587644e-002 2.41685249e-002 5.79076223e-002 3.81255820e-002 + 6.19256757e-002 7.89657310e-002 9.50866863e-002 -8.64683464e-002 + -1.49970844e-001 -5.56673743e-002 -8.72979015e-002 + -1.47175556e-002 7.43101090e-002 8.60797614e-002 1.55985788e-001 + 2.14912985e-002 -9.33349654e-002 -2.01558098e-001 -8.49207193e-002 + -3.82880718e-002 2.19196803e-003 4.72889692e-002 2.18127109e-002 + 5.54234348e-002 -1.36239314e-002 -8.53878036e-002 -7.84353465e-002 + -2.42070481e-003 3.55904326e-002 7.10110217e-002 1.31019233e-002 + 3.94776687e-002 9.54635814e-002 1.94141995e-002 -5.31869046e-002 + -7.16326460e-002 -6.74846023e-002 -1.08613139e-002 1.03373881e-002 + 9.56162512e-002 6.90407827e-002 1.30511776e-001 -3.20903733e-002 + -8.12360048e-002 -1.25160113e-001 -4.79309559e-002 + -2.53595915e-002 -2.74991523e-002 5.67354448e-002 -8.64330977e-002 + -4.05426919e-002 -1.18163815e-002 1.21157449e-002 4.48282920e-002 + -1.40990047e-002 2.72303261e-002 -5.72508201e-002 -5.24675176e-002 + 5.78021109e-002 5.38130589e-002 4.91915084e-002 -8.24092235e-003 + -1.21752685e-002 -1.86048061e-001 -4.19442961e-003 + -4.51702997e-002 -6.16904087e-002 2.63639372e-002 5.48340641e-002 + 1.80467650e-001 1.82503257e-002 -1.19063795e-001 -2.52490491e-001 + 3.45796533e-002 6.63018879e-003 -6.80198073e-002 -1.09015085e-001 + -5.09467162e-002 3.11759431e-002 6.05070293e-002 7.51647875e-002 + -3.63552049e-002 4.68738116e-002 -5.29397875e-002 4.06734087e-002 + 1.09812282e-002 -1.28183188e-003 1.42601892e-001 8.39142874e-002 + 6.09575920e-002 3.59109230e-002 9.33900848e-002 1.46967163e-002 + 5.96003681e-002 4.65553366e-002 3.99092138e-002 1.34020954e-001 + 4.31154817e-002 -1.50818124e-001 -1.81441188e-001 -1.20096996e-001 + 5.35494834e-002 1.07319340e-001 8.15097243e-002 5.38924746e-002 + 1.01222783e-001 1.68098267e-002 -1.16695330e-001 -8.84555429e-002 + -1.16753303e-001 2.13976875e-002 1.85226664e-001 8.34599063e-002 + 6.94932938e-002 1.57387525e-001 5.72885796e-002 -1.63378790e-001 + -3.25934887e-001 -2.37415254e-001 1.69544891e-001 2.95434535e-001 + 1.90200031e-001 6.92697614e-002 1.96215525e-001 7.86449537e-002 + -7.73894489e-002 -1.47447035e-001 -2.14115113e-001 2.32258309e-002 + 6.89294487e-002 6.43628910e-002 4.43876982e-002 3.01109371e-003 + -6.06745332e-002 -5.05361371e-002 -8.62532035e-002 + -8.73161629e-002 -3.65096107e-002 2.56805439e-002 -7.61494488e-002 + -5.57822622e-002 -5.39904572e-002 3.33092362e-002 1.42641645e-002 + -1.63426735e-002 3.33166751e-003 -3.77073735e-002 1.90925866e-001 + 1.06870249e-001 4.45638895e-002 8.55093673e-002 -2.20268257e-002 + -4.56461944e-002 -7.82874152e-002 -1.21429555e-001 + -1.40921131e-001 6.12106398e-002 4.76668179e-002 -1.11054583e-002 + -5.34441024e-002 5.25335632e-002 5.18498719e-002 5.09985760e-002 + 1.12468628e-002 -1.26223579e-001 -7.37349540e-002 -1.35690719e-001 + -1.25087142e-001 -3.67803015e-002 3.56901325e-002 5.01857772e-002 + 2.41782572e-002 5.45808896e-002 1.14228874e-002 -7.66682029e-002 + -1.17870867e-001 -2.02913493e-001 2.50498429e-002 1.73717126e-001 + 1.22337490e-001 1.39574826e-001 7.24396631e-002 -5.26285060e-002 + -7.60266231e-003 -1.58792377e-001 -1.69140488e-001 + -2.09366437e-002 2.33074185e-002 1.07788809e-001 7.67055154e-002 + 1.04977414e-001 7.36823753e-002 1.73312910e-002 -2.16749892e-001 + -2.14010328e-001 7.24725202e-002 1.69069335e-001 1.91567838e-001 + 1.33366734e-001 1.07279420e-001 2.28628423e-003 <_> 1 - -5.7395776800048726e-001 + -5.7395781820671121e-001 1. diff --git a/traffic.h b/traffic.h index 7030794..36b22df 100644 --- a/traffic.h +++ b/traffic.h @@ -8,7 +8,7 @@ #include #define IS_SAVE 0 //ͷɼϢǷ񱣴 -#define OPENMP 0//ǷʹOPENMPд +#define OPENMP 1//ǷʹOPENMPд #define ISDEBUG_TL 0//ʱмͼϢ(Traffic Light) #define ISDEBUG_TS 0//ʱмͼϢ(Traffic Sign) #define IS_SHOW_RESULT 1//Ƿʾ,ʾͼٶȸ