opticalflow_image_LearningOpenCV.rar

/*#include "cv.h" #include "cvcam.h" #include "highgui.h" #include <stdio.h> #include <ctype.h> #include <time.h> #include <math.h> //#include <ctype.h> //#include <stdio.h> #pragma comment(lib, "cv.lib") #pragma comment(lib, "highgui.lib") #pragma comment(lib, "cxcore.lib") // various tracking parameters (in seconds) const double MHI_DURATION = 0.5; const double MAX_TIME_DELTA = 0.5; const double MIN_TIME_DELTA = 0.05; // 用于运动检测的循环帧数，与机器速度以及FPS设置有关 const int N = 2; CvSize imgSize; // ring image buffer IplImage *buf = 0; int last = 0; // temporary images IplImage *mhi = 0; // MHI: motion history image IplImage *orient = 0; // orientation IplImage *mask = 0; // valid orientation mask IplImage *segmask = 0; // motion segmentation map IplImage *out = 0; CvMemStorage* storage = 0; // temporary storage CvRect track_rect; CvCapture* capture = 0; CvPoint trackpoint ; //IplImage *tmpImg2 = NULL; int count = 0; int count1 = 0; IplImage* facecheck(IplImage *image) { cvFlip(image, image, 0); CvHaarClassifierCascade* cascade; CvMemStorage* storage; CvSeq* faces; const char* file_name; int i; IplImage *image_scale; image_scale = cvCreateImage( cvSize(480,270), IPL_DEPTH_8U, 3);//160,120,cvSize(192,108)384,216,768,432 cvResize(image,image_scale,1); //initializations storage=cvCreateMemStorage(0); cvFirstType(); file_name="haarcascade_frontalface_alt.xml"; cascade = (CvHaarClassifierCascade*)cvLoad(file_name,NULL, NULL, NULL); faces = cvHaarDetectObjects( image_scale, cascade, storage, 1.2, 2,CV_HAAR_DO_CANNY_PRUNING,cvSize(0, 0)); //draw rectangles for(i=0;i<(faces ? faces->total:0); i++ ) { CvRect* r = (CvRect*)cvGetSeqElem( faces, i ); CvPoint pt1 = { r->x-10, r->y-10 }; CvPoint pt2 = { r->x + r->width+20, r->y + r->height + 140}; cvRectangle( image_scale, pt1, pt2, CV_RGB(0,0,0),CV_FILLED, 8, 0 );//CV_FILLED // cvCircle(image, pt1, 1, CV_RGB(255,0,0), 4); // cvCircle(image, pt2, 1, CV_RGB(255,255,0), 4); } cvResize(image_scale,image,1); cvFlip(image, image, 0); // cvNamedWindow( "skinout1", 1 ); // cvShowImage( "skinout1", image ); // create window and show the image with outlined faces if (faces!=NULL) { cvClearSeq(faces); } cvReleaseHaarClassifierCascade( &cascade ); cvReleaseMemStorage( &storage ); cvReleaseImage(&image_scale); return image; } IplImage *skinDetect( IplImage *img) { IplImage *tmpImg = NULL; IplImage *tmpImg2 = NULL; IplImage *conv = NULL; IplImage *H= NULL; IplImage *S= NULL; IplImage *V= NULL; IplImage *tmpH1= NULL; IplImage *tmpS1= NULL; IplImage *tmpH2= NULL; IplImage *tmpH3= NULL; IplImage *tmpS2= NULL; IplImage *tmpS3= NULL; CvMemStorage* storage; storage = cvCreateMemStorage(0); CvSeq* contour; contour = 0; IplConvKernel *erosionElement, *dilationElement; double contArea, imgArea = 0.0; imgArea = imgSize.width * imgSize.height; conv = cvCreateImage( imgSize, IPL_DEPTH_8U, 3); tmpImg2 = cvCreateImage( imgSize, IPL_DEPTH_8U, 3); tmpH1 = cvCreateImage( imgSize, IPL_DEPTH_8U, 1); tmpS1 = cvCreateImage( imgSize, IPL_DEPTH_8U, 1); tmpH2 = cvCreateImage( imgSize, IPL_DEPTH_8U, 1); tmpS3 = cvCreateImage( imgSize, IPL_DEPTH_8U, 1); tmpH3 = cvCreateImage( imgSize, IPL_DEPTH_8U, 1); tmpS2 = cvCreateImage( imgSize, IPL_DEPTH_8U, 1); H = cvCreateImage( imgSize, IPL_DEPTH_8U, 1); S = cvCreateImage( imgSize, IPL_DEPTH_8U, 1); V = cvCreateImage( imgSize, IPL_DEPTH_8U, 1); tmpImg =cvCloneImage(img); // Convert to HSV cvCvtColor( tmpImg, conv, CV_BGR2HSV ); // Split to HSV planes //cvCvtPixToPlane(conv,H,S,V,0); cvSplit(conv,H,S,V,0); /* cvInRangeS(H,cvScalar(5.0,0.0,0,0),cvScalar(30.0,0.0,0,0),tmpH1);//25 5 18 cvInRangeS(S,cvScalar(10.0,0.0,0,0),cvScalar(150.,0.0,0,0),tmpS1);//75 90 cvAnd(tmpH1,tmpS1,tmpH1,0); cvInRangeS(H,cvScalar(170.0,0.0,0,0),cvScalar(180.0,0.0,0,0),tmpH2);//25 5 18 cvInRangeS(S,cvScalar(15.0,0.0,0,0),cvScalar(90.,0.0,0,0),tmpS2);//75 cvAnd(tmpH2,tmpS2,tmpH2,0);//*/ /* cvInRangeS(H,cvScalar(2.0,0.0,0,0),cvScalar(30.0,0.0,0,0),tmpH1);//25 5 18 cvInRangeS(S,cvScalar(5.0,0.0,0,0),cvScalar(150.,0.0,0,0),tmpS1);//75 90 cvAnd(tmpH1,tmpS1,tmpH1,0); cvInRangeS(H,cvScalar(160.0,0.0,0,0),cvScalar(180.0,0.0,0,0),tmpH2);//25 5 18 cvInRangeS(S,cvScalar(15.0,0.0,0,0),cvScalar(90.0,0.0,0,0),tmpS2);//75 cvAnd(tmpH2,tmpS2,tmpH2,0); cvOr(tmpH1,tmpH2,tmpH1); cvSmooth(tmpH1, tmpH3, CV_MEDIAN); // Dilation and Erosion // Structuring Element Generation dilationElement = cvCreateStructuringElementEx( 5,5,3,3, CV_SHAPE_RECT , 0 ); erosionElement = cvCreateStructuringElementEx( 5,5,3,3, CV_SHAPE_RECT , 0 ); // Erosion peels a layer of pixels off, and makes small regions disappear cvErode(tmpH3,tmpH3,erosionElement,1); // Dilation adds a layer on, and returns things to the correct size. cvDilate(tmpH3,tmpH3,dilationElement,1); // Find the contours of all remaining objects cvFindContours( tmpH3, storage, &contour, sizeof(CvContour), CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE ); cvZero(tmpH1); // contour now contains a CvSequence of all of the contours for( ; contour != 0; contour = contour->h_next ) { contArea = fabs(cvContourArea( contour, CV_WHOLE_SEQ )); double bl=fabs(cvContourPerimeter(contour)); //double a=4*3.14*contArea/(bl*bl); // Ignore very small contours for(int i = 0;i < contour->total;i++) { CvPoint* p = (CvPoint* )cvGetSeqElem(contour, i); if ((p->y == 0) || (p->x == 0)||(p->x == imgSize.width) ||(p->y == imgSize.height)) { // cvSeqRemove(contour,i); cvClearSeq(contour); } } if ( (contArea/imgArea <= 0.015) )//|| (contArea/imgArea >= 0.3) { cvSeqRemove(contour,0); } else //if((a >= 0.09)&&(a<= 0.33) ) { //CvRect comp_rect1 = ((CvConnectedComp*)cvGetSeqElem( seq, i ))->rect; /*CvRect bndRect1 = cvBoundingRect( contour, 0 ); CvPoint pt1, pt1; if ((bndRect1.height/bndRect1.width) > 1.1 )// (bndRect1.height/bndRect1.width) < 0.9 { for(int i = 0;i < contour->total;i++) { CvPoint p = (CvPoint* )cvGetSeqElem(contour_mid, i); if (p->y > 1.1 * bndRect1.width ) { top.x = p->x; top.y = p->y; } } /* pt1.x = bndRect1.x; pt1.y = bndRect1.y; pt2.x = bndRect1.x + bndRect1.width; pt2.y = bndRect1.y + bndRect1.height;//*/ /* if ((bndRect1.height/bndRect1.width) > 1.1 )// (bndRect1.height/bndRect1.width) < 0.9 { }//*/ /* cvDrawContours( tmpH1, contour, CV_RGB( 255,255,255 ), CV_RGB( 255,255,255 ), 0, -1, 8 ); //cvDrawContours( img, contour, CV_RGB( 255,0,255 ), CV_RGB( 0,255,255 ), -1, -1, 8 ); } } cvCvtColor(tmpH1,tmpImg2,CV_GRAY2BGR); cvAnd(tmpImg2,img,img); // If we found any contours then free the memory they use. if (contour!=NULL) { cvClearSeq(contour); } cvReleaseImage(&conv); cvReleaseImage(&H); cvReleaseImage(&S); cvReleaseImage(&V); cvReleaseImage(&tmpH1); cvReleaseImage(&tmpH2); cvReleaseImage(&tmpH3); cvReleaseImage(&tmpS1); cvReleaseImage(&tmpS2); cvReleaseImage(&tmpS3); cvReleaseImage(&tmpImg); cvReleaseImage(&tmpImg2); cvReleaseMemStorage(&storage); return img; } // parameters: // img - input video frame // dst - resultant motion picture // args - optional parameters void update_mhi( IplImage* img, IplImage* dst, int diff_threshold ) { //cvNamedWindow( "Motion1", 1 ); double timestamp = clock()/1000.; // get current time in seconds CvSize size = cvSize(img->width,img->height); // get current frame size // int i, idx1 = last, idx2; IplImage* silh; IplImage* draw = NULL; CvSeq* seq; CvRect comp_rect; double count; double angle; CvPoin