void cvSoftmaxDer(CvMat * X, CvMat * dE_dY, CvMat * dE_dY_afder) {
CV_FUNCNAME("cvSoftmaxDer");
__BEGIN__;
const int nr = X->rows, nc = X->cols, dtype = CV_MAT_TYPE(X->type);
CvMat * Y = cvCreateMat(nr, nc, dtype);
CvMat * dE_dY_transpose = cvCreateMat(nr, nc, dtype);
CvMat * sum = cvCreateMat(nr, 1, dtype);
CvMat * sum_repeat = cvCreateMat(nr, nc, dtype);
cvSoftmax(X, Y);
if (dE_dY->rows==nc && dE_dY->cols==nr){
cvTranspose(dE_dY,dE_dY_transpose);
cvMul(Y,dE_dY_transpose,dE_dY_afder);
}else{
cvMul(Y,dE_dY,dE_dY_afder);
}
cvReduce(dE_dY_afder,sum,-1,CV_REDUCE_SUM);
cvRepeat(sum,sum_repeat);
cvMul(Y,sum_repeat,sum_repeat);
cvSub(dE_dY_afder,sum_repeat,dE_dY_afder);
cvReleaseMat(&dE_dY_transpose);
cvReleaseMat(&sum);
cvReleaseMat(&sum_repeat);
cvReleaseMat(&Y);
__END__;
}
/*************************************************************************
* @函数名称：
* calGradSim()
* @输入:
* const IplImage* image1 - 输入图像1
* const IplImage* image2 - 输入图像2
* @返回值:
* double g - 梯度相似性
* @说明:
* 计算图像梯度相似性
*************************************************************************/
double calGradSim(const IplImage* image1, const IplImage* image2)
{
double c4 = 0;
double g = 0;
IplImage* g1;
IplImage* g2;
IplImage* tmp;
g1=gradientImage(image1);
g2=gradientImage(image2);
tmp = cvCloneImage(g1);
cvMul(g1, g2, tmp);
cvMul(g1, g1, g1);
cvMul(g2, g2, g2);
CvScalar s1 = cvSum(tmp);
CvScalar s2 = cvSum(g1);
CvScalar s3 = cvSum(g2);
c4 = (0.03 * 255) * (0.03 * 255);
g = (2 * s1.val[0] + c4) / (s2.val[0] +s3.val[0] + c4);
cvReleaseImage(&g1);
cvReleaseImage(&g2);
cvReleaseImage(&tmp);
return g;
}
CV_IMPL void cvCalS(const CvArr* srcarr,
CvArr* dstarr)
{
CV_FUNCNAME("cvCalS");
__BEGIN__;
CvMat sstub, *src;
CvMat dstub, *dst;
CvMat* src_dx=0, *src_dy=0;
CvSize size;
int i, j;
int iStep;
float* fPtr;
CV_CALL( src = cvGetMat(srcarr, &sstub ));
CV_CALL( dst = cvGetMat(dstarr, &dstub ));
if( CV_MAT_TYPE(src->type) != CV_32FC1)
CV_ERROR( CV_StsUnsupportedFormat, "Only-32bit, 1-channel input images are supported" );
if( CV_MAT_TYPE(dst->type) != CV_32FC1)
CV_ERROR( CV_StsUnsupportedFormat, "Only-32bit, 1-channel input images are supported" );
if( !CV_ARE_SIZES_EQ( src, dst ))
CV_ERROR( CV_StsUnmatchedSizes, "The input images must have the same size" );
size = cvGetMatSize( src );
src_dx = cvCreateMat(size.height, size.width, CV_32FC1 );
src_dy = cvCreateMat(size.height, size.width, CV_32FC1 );
cvSetZero(src_dx);
cvSetZero(src_dy);
iStep = dst->step / sizeof(fPtr[0]);
fPtr = dst->data.fl;
cvSobel(src, src_dx, 1, 0, 1);
cvSobel(src, src_dy, 0, 1, 1);
cvMul(src_dx, src_dx, src_dx, 0.25f*0.25f); //rescale gradient
cvMul(src_dy, src_dy, src_dy, 0.25f*0.25f); //rescale gradient
cvAdd(src_dx, src_dy, dst);
for(j=0; j<size.height; j++){
for (i=0; i<size.width; i++)
fPtr[i+iStep*j] = sqrt(fPtr[i+iStep*j])+SMALLNUM;
}
cvReleaseMat(&src_dx);
cvReleaseMat(&src_dy);
__END__;
}
CV_IMPL void cvCurvature(const CvArr* srcarr_x,
const CvArr* srcarr_y,
CvArr* dstarr)
{
CV_FUNCNAME("cvCurvature");
__BEGIN__;
CvMat sstub_x, sstub_y, *src_x, *src_y;
CvMat dstub, *dst;
CvSize size;
CvMat *Nxx=0, *Nyy=0, *ones=0;
CV_CALL( src_x = cvGetMat(srcarr_x, &sstub_x ));
CV_CALL( src_y = cvGetMat(srcarr_y, &sstub_y ));
CV_CALL( dst = cvGetMat(dstarr, &dstub ));
if( CV_MAT_TYPE(src_x->type) != CV_32FC1)
CV_ERROR( CV_StsUnsupportedFormat, "Only-32bit, 1-channel input images are supported" );
if( CV_MAT_TYPE(src_y->type) != CV_32FC1)
CV_ERROR( CV_StsUnsupportedFormat, "Only-32bit, 1-channel input images are supported" );
if( CV_MAT_TYPE(dst->type) != CV_32FC1)
CV_ERROR( CV_StsUnsupportedFormat, "Only-32bit, 1-channel input images are supported" );
if( !CV_ARE_SIZES_EQ( src_x, src_y ))
CV_ERROR( CV_StsUnmatchedSizes, "The input images must have the same size" );
size = cvGetMatSize( src_x );
Nxx = cvCreateMat(size.height, size.width, CV_32FC1 );
Nyy = cvCreateMat(size.height, size.width, CV_32FC1 );
ones= cvCreateMat(size.height, size.width, CV_32FC1 );
cvSetZero(Nxx);
cvSetZero(Nyy);
cvSet(ones, cvScalar(1.0f));
cvSobel(src_x, Nxx, 1, 0, 1);
cvSobel(src_y, Nyy, 0, 1, 1);
cvMul(Nxx, ones, Nxx, 0.25f);
cvMul(Nyy, ones, Nyy, 0.25f);
cvAdd(Nxx, Nyy, dst);
cvReleaseMat(&Nxx);
cvReleaseMat(&Nyy);
cvReleaseMat(&ones);
__END__;
}
/*IplImage* HomographyCalculationThread::rectifyImage(IplImage* inImage, IplImage* outImage,double oldFirstApexX,double oldFirstApexY,double width,double height)
{
double x1 = 0;
double x2 = 0;
double x3 = 0;
double y_position = 0;
double x_position = 0;
uchar* data = (uchar *)inImage->imageData;
uchar* dataOut = (uchar *)outImage->imageData;
for(int row=0;row<height;row++) {
for(int col=0;col<width;col++) {
x1 = cvmGet(mHMatrix,0,0) * col + cvmGet(mHMatrix,0,1) * row + cvmGet(mHMatrix,0,2);
x2 = cvmGet(mHMatrix,1,0) * col + cvmGet(mHMatrix,1,1) * row + cvmGet(mHMatrix,1,2);
x3 = cvmGet(mHMatrix,2,0) * col + cvmGet(mHMatrix,2,1) * row + 1;
y_position = x2/x3 + oldFirstApexY;
if(inImage->height < y_position) {
y_position = (inImage->height-1);
}
x_position = x1/x3 + oldFirstApexX;
if(inImage->width < x_position) {
x_position = (inImage->width-1);
}
int temp_y = (int)y_position;
int temp_x = (int)x_position;
if(dataOut!=NULL && data!=NULL) {
dataOut[row*outImage->widthStep+col*outImage->nChannels] = data[temp_y*inImage->widthStep+temp_x*inImage->nChannels];
dataOut[row*outImage->widthStep+col*outImage->nChannels+1] = data[temp_y*inImage->widthStep+temp_x*inImage->nChannels+1];
dataOut[row*outImage->widthStep+col*outImage->nChannels+2] = data[temp_y*inImage->widthStep+temp_x*inImage->nChannels+2];
}
}
}
cvReleaseMat(&mHMatrix);
return outImage;
}
*/
void HomographyCalculationThread::correctHomographicMatrix(IplImage* inImage,CvMat* invH,double lastPictureApexX,double lastPictureApexY,double width,double height)
{
CvMat *hCoeff = cvCreateMat(3,3,CV_32FC1);
CvMat* multipleMat = cvCreateMat(3,3,CV_32FC1);
double old_height = inImage->height;
double y_position = lastPictureApexY;
double x_position = lastPictureApexX;
for (int i=1;i<10;i++) {
double x1 = cvmGet(invH,0,0) * (x_position) + cvmGet(invH,0,1) * (y_position) + cvmGet(invH,0,2);
double x2 = cvmGet(invH,1,0) * (x_position) + cvmGet(invH,1,1) * (y_position) + cvmGet(invH,1,2);
double x3 = cvmGet(invH,2,0) * (x_position) + cvmGet(invH,2,1) * (y_position) + 1;
x1 = x1/x3;
x2 = x2/x3;
double H_coeff = ((x1/width)+(x2/height))/2 - 0.01;
for(int coeffRow=0;coeffRow<3;coeffRow++) {
for(int coeffCol=0;coeffCol<3;coeffCol++) {
cvmSet(hCoeff,coeffRow,coeffCol,H_coeff);
cvmSet(multipleMat,coeffRow,coeffCol,cvmGet(mHMatrix,coeffRow,coeffCol));
}
}
cvMul(multipleMat,hCoeff,mHMatrix);
cvInvert(mHMatrix,invH);
}
cvReleaseMat(&multipleMat);
cvReleaseMat(&hCoeff);
}
static void node_composit_exec_cvMult(void *data, bNode *node, bNodeStack **in, bNodeStack **out)
{
CvArr* dst;
CvArr* src1;
CvArr* src2;
CV_FUNCNAME( "cvMult" );
if(out[0]->hasoutput==0) return;
cvSetErrMode(1); //Parent mode error
__CV_BEGIN__;
if((in[0]->data)&&(in[1]->data)){
CV_CALL(src1 = in[0]->data);
CV_CALL(src2 = in[1]->data);
if(!BOCV_checkAreSameType(src1, src2))
CV_ERROR( CV_StsBadArg,"The source inputs are differents" );
CV_CALL(dst=BOCV_CreateArrFrom(src2));
if(dst)
{
CV_CALL(cvMul(src1, src2, dst, 1.0));
CV_CALL(out[0]->data= dst);
}
}
__CV_END__;
}
//--------------------------------------------------------------------------------
void ofxCvImage::operator *= ( ofxCvImage& mom ) {
if( !mom.bAllocated ){
ofLog(OF_LOG_ERROR, "in *=, mom needs to be allocated");
return;
}
if( !bAllocated ){
ofLog(OF_LOG_NOTICE, "in *=, allocating to match dimensions");
allocate(mom.getWidth(), mom.getHeight());
}
if( mom.getCvImage()->nChannels == cvImage->nChannels &&
mom.getCvImage()->depth == cvImage->depth )
{
if( matchingROI(getROI(), mom.getROI()) ) {
float scalef = 1.0f / 255.0f;
cvMul( cvImage, mom.getCvImage(), cvImageTemp, scalef );
swapTemp();
flagImageChanged();
} else {
ofLog(OF_LOG_ERROR, "in *=, ROI mismatch");
}
} else {
ofLog(OF_LOG_ERROR, "in *=, images need to have matching type");
}
}
//--------------------------------------------------------------------------------
void ofxCvImage::operator *= ( ofxCvImage& mom ) {
if( !mom.bAllocated ){
ofLogError("ofxCvImage") << "operator*=: mom needs to be allocated";
return;
}
if( !bAllocated ){
ofLogNotice("ofxCvImage") << "operator*=: allocating to match dimensions: "
<< mom.getWidth() << " " << mom.getHeight();
allocate(mom.getWidth(), mom.getHeight());
}
if( mom.getCvImage()->nChannels == cvImage->nChannels &&
mom.getCvImage()->depth == cvImage->depth )
{
if( matchingROI(getROI(), mom.getROI()) ) {
float scalef = 1.0f / 255.0f;
cvMul( cvImage, mom.getCvImage(), cvImageTemp, scalef );
swapTemp();
flagImageChanged();
} else {
ofLogError("ofxCvImage") << "operator*=: region of interest mismatch";
}
} else {
ofLogError("ofxCvImage") << "operator*=: images type mismatch";
}
}
//--------------------------------------------------------------------------------
void ofxCvFloatImage::operator *= ( ofxCvFloatImage& mom ) {
if( mom.width == width && mom.height == height ) {
cvMul( cvImage, mom.getCvImage(), cvImageTemp );
swapTemp();
} else {
cout << "error in *=, images are different sizes" << endl;
}
}
//--------------------------------------------------------------------------------
void CPUImageFilter::amplify ( CPUImageFilter& mom, float level ) {
float scalef = level / 128.0f;
cvMul( mom.getCvImage(), mom.getCvImage(), cvImageTemp, scalef );
swapTemp();
flagImageChanged();
}
//--------------------------------------------------------------------------------
void ofxCvColorImage::operator *= ( ofxCvColorImage& mom ) {
float scalef = 1.0f / 255.0f;
if( mom.width == width && mom.height == height ) {
cvMul( cvImage, mom.getCvImage(), cvImageTemp, scalef );
swapTemp();
} else {
cout << "error in *=, images are different sizes" << endl;
}
}
//--------------------------------------------------------------------------------
void setfilter::amplify ( setfilter& mom, float level ) {
//-- amplify weak areas --//
float scalef = level / 104.0; //128.0f
cvMul( mom.getCvImage(), mom.getCvImage(), cvImageTemp, scalef );
swapTemp();
flagImageChanged();
}
void HarrisBuffer::HarrisFunction(double k, IplImage* dst)
{
// Harris function in 3D
// original space-time Harris
/*detC=
cxx.*cyy.*ctt + xx yy tt
cxy.*cyt.*cxt + 2 * xy yt xt
cxt.*cxy.*cyt - .
cxx.*cyt.*cyt - xx yt^2
cxy.*cxy.*ctt - tt xy^2
cxt.*cyy.*cxt ; yy xt^2
*/
cvMul(cxx, cyy, tmp1);
cvMul(ctt, tmp1, tmp1);
cvMul(cxy, cxt, tmp2);
cvMul(cyt, tmp2, tmp2,2);
cvAdd(tmp1,tmp2,tmp1);
cvMul(cyt,cyt,tmp2);
cvMul(cxx,tmp2,tmp2);
cvSub(tmp1,tmp2,tmp1);
cvMul(cxy,cxy,tmp2);
cvMul(ctt,tmp2,tmp2);
cvSub(tmp1,tmp2,tmp1);
cvMul(cxt,cxt,tmp2);
cvMul(cyy,tmp2,tmp2);
cvSub(tmp1,tmp2,tmp1);
//trace3C=(cxx+cyy+ctt).^3;
cvAdd(cxx,cyy,tmp2);
cvAdd(ctt,tmp2,tmp2);
cvPow(tmp2,tmp2,3);
//H=detC-stharrisbuffer.kparam*trace3C;
cvScale(tmp2,tmp2,k,0);
cvSub(tmp1,tmp2,dst);
}
static void icvH11Ops( CvMat* X, CvMat* Y, void* userdata )
{
CvH11OpsData* h11 = (CvH11OpsData*)userdata;
h11->AOps( X, h11->AR, h11->userdata );
h11->AtOps( h11->AR, h11->AtR, h11->userdata );
double rc = h11->fe_inv_2 * cvDotProduct( h11->atr, X );
cvAddWeighted( h11->AtR, -h11->fe_inv, h11->atr, rc, 0, h11->AtR );
cvMul( h11->sigx, X, h11->tX );
cvAdd( h11->tX, h11->AtR, Y );
}
int main(){
//initialize
IplImage* src_image = 0;
IplImage* mul_image = 0;
IplImage* div_image = 0;
IplImage* tmp_image = 0;
//load image
src_image = cvLoadImage("/Users/ihong-gyu/MyProject/OpenCVTest/Lena.jpeg",0);
//create a window
cvNamedWindow("Original Image", CV_WINDOW_AUTOSIZE);
cvNamedWindow("Multiply Image", CV_WINDOW_AUTOSIZE);
cvNamedWindow("Divide Image", CV_WINDOW_AUTOSIZE);
//make images
tmp_image = cvCreateImage(cvGetSize(src_image),IPL_DEPTH_8U, 1);
mul_image = cvCreateImage(cvGetSize(src_image),IPL_DEPTH_8U, 1);
div_image = cvCreateImage(cvGetSize(src_image),IPL_DEPTH_8U, 1);
//multiply÷
cvSet(tmp_image,cvScalarAll(1),NULL);
cvMul(src_image,tmp_image,mul_image,1.5);
cvMul(src_image,tmp_image,div_image,1.0/2.0);
//show the image
cvShowImage("Original Image", src_image);
cvShowImage("Multiply Image", mul_image);
cvShowImage("Divide Image", div_image);
//wait for a key
cvWaitKey(0);
//release the image
cvReleaseImage(&src_image);
cvReleaseImage(&mul_image);
cvReleaseImage(&div_image);
return 0;
}
IplImage* multiplier(IplImage *image1, IplImage *image2){
IplImage *res = cvCreateImage(cvGetSize(image1),image1->depth,image1->nChannels);
IplImage *imgCanal1 = cvCreateImage(cvGetSize(image1),image1->depth,1);
IplImage *imgCanal2 = cvCreateImage(cvGetSize(image1),image1->depth,1);
IplImage *imgCanal3 = cvCreateImage(cvGetSize(image1),image1->depth,1);
cvSplit(image1,imgCanal1,imgCanal2,imgCanal3,NULL);
cvMul(imgCanal1, image2, imgCanal1, 1);
cvMul(imgCanal2, image2, imgCanal2, 1);
cvMul(imgCanal3, image2, imgCanal3, 1);
cvMerge(imgCanal1,imgCanal2,imgCanal3,NULL,res);
cvReleaseImage(&imgCanal1);
cvReleaseImage(&imgCanal2);
cvReleaseImage(&imgCanal3);
return res;
}
CvMat* HomographyCalculationThread::calculateHomographicMatrix(double newPictureApexX[],double newPictureApexY[],double pictureApexXPosition[],double pictureApexYPosition[])
{
CvMat* mmat = cvCreateMat(3,3,CV_32FC1);
CvMat* a = cvCreateMat(POINTS*2,9,CV_32FC1);
for(int count=1;count<POINTS+1;count++) {
cvmSet(a,2*count-2,0,newPictureApexX[count-1]);
cvmSet(a,2*count-2,1,newPictureApexY[count-1]);
cvmSet(a,2*count-2,2,1);
cvmSet(a,2*count-2,3,0);
cvmSet(a,2*count-2,4,0);
cvmSet(a,2*count-2,5,0);
cvmSet(a,2*count-2,6,(-newPictureApexX[count-1]*pictureApexXPosition[count-1]));
cvmSet(a,2*count-2,7,(-pictureApexXPosition[count-1]*newPictureApexY[count-1]));
cvmSet(a,2*count-2,8,-pictureApexXPosition[count-1]);
cvmSet(a,2*count-1,0,0);
cvmSet(a,2*count-1,1,0);
cvmSet(a,2*count-1,2,0);
cvmSet(a,2*count-1,3,newPictureApexX[count-1]);
cvmSet(a,2*count-1,4,newPictureApexY[count-1]);
cvmSet(a,2*count-1,5,1);
cvmSet(a,2*count-1,6,(-newPictureApexX[count-1]*pictureApexYPosition[count-1]));
cvmSet(a,2*count-1,7,(-pictureApexYPosition[count-1]*newPictureApexY[count-1]));
cvmSet(a,2*count-1,8,-pictureApexYPosition[count-1]);
}
CvMat* U = cvCreateMat(8,8,CV_32FC1);
CvMat* D = cvCreateMat(8,9,CV_32FC1);
CvMat* V = cvCreateMat(9,9,CV_32FC1);
CvMat* V22 = cvCreateMat(3,3,CV_32FC1);
mHMatrix = cvCreateMat(3,3,CV_32FC1);
CvMat* invH = cvCreateMat(3,3,CV_32FC1);
cvSVD(a, D, U, V, CV_SVD_U_T|CV_SVD_V_T);
for(int a=0;a<3;a++) {
for(int b=0;b<3;b++) {
cvmSet(mmat,a,b,cvmGet(V,8,a*3+b));
cvmSet(V22,a,b,(1/cvmGet(V,8,4)));
}
}
cvMul(mmat,V22,mHMatrix);
cvInvert(mHMatrix,invH);
cvReleaseMat(&U);
cvReleaseMat(&D);
cvReleaseMat(&V);
cvReleaseMat(&V22);
cvReleaseMat(&a);
cvReleaseMat(&mmat);
return invH;
}
//--------------------------------------------------------------------------------
void ofxCvFloatImage::operator *= ( ofxCvImage& mom ) {
if( mom.getCvImage()->nChannels == cvImage->nChannels &&
mom.getCvImage()->depth == cvImage->depth )
{
if( matchingROI(getROI(), mom.getROI()) ) {
cvMul( cvImage, mom.getCvImage(), cvImageTemp );
swapTemp();
flagImageChanged();
} else {
ofLog(OF_LOG_ERROR, "in *=, ROI mismatch");
}
} else {
ofLog(OF_LOG_ERROR, "in *=, images need to have matching type");
}
}
//--------------------------------------------------------------------------------
void ofxCvFloatImage::operator *= ( ofxCvImage& mom ) {
if( mom.getCvImage()->nChannels == cvImage->nChannels &&
mom.getCvImage()->depth == cvImage->depth )
{
if( pushSetBothToTheirIntersectionROI(*this,mom) ) {
cvMul( cvImage, mom.getCvImage(), cvImageTemp );
swapTemp();
popROI(); //restore prevoius ROI
mom.popROI(); //restore prevoius ROI
flagImageChanged();
} else {
ofLog(OF_LOG_ERROR, "in *=, ROI mismatch");
}
} else {
ofLog(OF_LOG_ERROR, "in *=, images need to have matching type");
}
}
double pkmGaussianMixtureModel::multinormalDistribution(const CvMat *pts, const CvMat *mean, const CvMat *covar)
{
int dimensions = 2;
// add a tiny bit because of small samples
CvMat *covarShifted = cvCreateMat(2, 2, CV_64FC1);
cvAddS( covar, cvScalarAll(0.001), covarShifted);
// calculate the determinant
double det = cvDet(covarShifted);
// invert covariance
CvMat *covarInverted = cvCreateMat(2, 2, CV_64FC1);
cvInvert(covarShifted, covarInverted);
double ff = (1.0/(2.0*(double)PI))*(pow(det,-0.5));
CvMat *centered = cvCreateMat(2, 1, CV_64FC1);
cvSub(pts, mean, centered);
CvMat *invxmean = cvCreateMat(2, 1, CV_64FC1);
//cvGEMM(covarInverted, centered, 1., NULL, 1., invxmean);
cvMatMul(covarInverted, centered, invxmean);
cvMul(centered, invxmean, invxmean);
CvScalar sum = cvSum(invxmean);
/*
printf("covar: %f %f %f %f\n", cvmGet(covar, 0, 0), cvmGet(covar, 0, 1), cvmGet(covar, 1, 0), cvmGet(covar, 1, 1));
printf("covarShifted: %f %f %f %f\n", cvmGet(covarShifted, 0, 0), cvmGet(covarShifted, 0, 1), cvmGet(covarShifted, 1, 0), cvmGet(covarShifted, 1, 1));
printf("det: %f\n", det);
printf("covarInverted: %f %f %f %f\n", cvmGet(covarInverted, 0, 0), cvmGet(covarInverted, 0, 1), cvmGet(covarInverted, 1, 0), cvmGet(covarShifted, 1, 1));
printf("ff: %f\n", ff);
printf("pts: %f %f)\n", cvmGet(pts, 0, 0), cvmGet(pts, 1, 0));
printf("mean: %f %f)\n", cvmGet(mean, 0, 0), cvmGet(mean, 1, 0));
printf("centered: %f %f)\n", cvmGet(centered, 0, 0), cvmGet(centered, 1, 0));
printf("invxmean: %f %f)\n", cvmGet(invxmean, 0, 0), cvmGet(invxmean, 1, 0));
printf("scalar: %f %f %f %f\n", sum.val[0], sum.val[1], sum.val[2], sum.val[3]);
*/
cvReleaseMat(&covarShifted);
cvReleaseMat(&covarInverted);
cvReleaseMat(¢ered);
cvReleaseMat(&invxmean);
return ff * exp(-0.5*sum.val[0]);
}
//--------------------------------------------------------------------------------
void ofxCvFloatImage::operator *= ( ofxCvImage& mom ) {
if( mom.getWidth() == 0 || mom.getHeight() == 0 ){
ofLog(OF_LOG_ERROR, "in *=, mom width or height is 0");
return;
}
if( !bAllocated ){
ofLog(OF_LOG_ERROR, "in *=, image is not allocated");
return;
}
if( mom.getCvImage()->nChannels == cvImage->nChannels && mom.getCvImage()->depth == cvImage->depth ){
if( matchingROI(getROI(), mom.getROI()) ) {
cvMul( cvImage, mom.getCvImage(), cvImageTemp );
swapTemp();
flagImageChanged();
} else {
ofLog(OF_LOG_ERROR, "in *=, ROI mismatch");
}
} else {
ofLog(OF_LOG_ERROR, "in *=, images need to have matching type");
}
}
int main(int argc, _TCHAR* argv[])
{
cvNamedWindow( "Background Averaging", CV_WINDOW_AUTOSIZE );
CvCapture* capture = cvCreateFileCapture( "tree.avi" );
IplImage *frame, *mask1, *mask3;
int frameCount = 0;
while(1) {
frameCount++;
frame = cvQueryFrame( capture );
if( !frame ) break;
CvSize sz = cvGetSize( frame );
mask1 = cvCreateImage( sz, IPL_DEPTH_8U, 1 );
mask3 = cvCreateImage( sz, IPL_DEPTH_8U, 3 );
if(frameCount == 1)
AllocateImages( frame );
if( frameCount < 30 ){
accumulateBackground( frame );
}else if( frameCount == 30 ){
createModelsfromStats();
}else{
backgroundDiff( frame, mask1 );
cvCvtColor(mask1,mask3,CV_GRAY2BGR);
cvNorm( mask3, mask3, CV_C, 0);
cvThreshold(mask3, mask3, 100, 1, CV_THRESH_BINARY);
cvMul( frame, mask3, frame, 1.0 );
cvShowImage( "Background Averaging", frame );
}
char c = cvWaitKey(33);
if( c == 27 ) break;
}
cvReleaseCapture( &capture );
cvDestroyWindow( "Background Averaging" );
DeallocateImages();
}
//------------------------------------------------------------------------------
// Color Similarity Matrix Calculation
//------------------------------------------------------------------------------
CvMat *colorsim(int nbins, double sigma) {
CvMat *xc=cvCreateMat(1,nbins, CV_32FC1);
CvMat *yr=cvCreateMat(nbins,1, CV_32FC1);
CvMat *x=cvCreateMat(nbins,nbins, CV_32FC1);
CvMat *y=cvCreateMat(nbins,nbins, CV_32FC1);
CvMat *m=cvCreateMat(x->rows,x->rows, CV_32FC1);
// Set x,y directions
for (int j=0;j<nbins;j++) {
cvSetReal2D(xc,0,j,(j+1-0.5)/nbins);
cvSetReal2D(yr,j,0,(j+1-0.5)/nbins);
}
// Set u,v, meshgrids
for (int i=0;i<x->rows;i++) {
cvRepeat(xc,x);
cvRepeat(yr,y);
}
CvMat *sub = cvCreateMat(x->rows,y->cols,CV_32FC1);
cvSub(x,y,sub);
cvAbs(sub,sub);
cvMul(sub,sub,sub);
cvConvertScale(sub,sub,-1.0/(2*sigma*sigma));
cvExp(sub,sub);
cvSubRS(sub,cvScalar(1.0),m);
cvReleaseMat(&xc);
cvReleaseMat(&yr);
cvReleaseMat(&x);
cvReleaseMat(&y);
cvReleaseMat(&sub);
return m;
}
void HarrisBuffer::DetectInterestPoints(int border)
{
ipList.clear();
Hbuffer.FindLocalMaxima(ipList,true);
CvMat *reg=cvCreateMat( SizeNeighb, 1, CV_64F );
//remove border
if(border<2)
border=2; // interest points in the boundary should be remove to have a valid local 5x5x5 mask
// an alternative could be extending by 2 pixel in space dimensions
//select significant points which are not in the boundary
for(int i=0;i<(int)ipList.size();i++)
if(ipList[i].x>=border && (ipList[i].x<frame->width-border) &&
ipList[i].y>=border && (ipList[i].y<frame->height-border) && ipList[i].val>SignificantPointThresh)
ipList[i].reject=false;
//computing JET features around an interest point by 5x5x5 local mask
for(int i=0;i<(int)ipList.size();i++)
if(!ipList[i].reject)
{
ipList[i].features=cvCreateMat( LengthFeatures, 1, CV_64F );
convbuffer.GetLocalRegion(ipList[i].x,ipList[i].y ,ipList[i].t,5,5,5, reg);
cvMatMul(&JetFilter,reg,ipList[i].features);
cvMul(ipList[i].features,normvec,ipList[i].features);//normalization
}
cvReleaseMat(®);
//check tstamp for any possible error
//writing selected interest points to file
for(int i=0;i<(int)ipList.size();i++)
if(!ipList[i].reject)
WriteFeatures(ipList[i]);
}
void HarrisBuffer::OpticalFlowFromSMM()
{
// ref: Laptev et al. CVIU 2007, eq.(8)
cvMul(cxx, cyy, tmp1);
cvMul(cxy, cxy, tmp2);
cvSub(tmp1,tmp2,tmp5);
cvMul(cyy, cxt, tmp3);
cvMul(cxy, cyt, tmp4);
cvSub(tmp3,tmp4,tmp6);
cvDiv(tmp6,tmp5,OFx);
cvMul(cxx, cyt, tmp3);
cvMul(cxy, cxt, tmp4);
cvSub(tmp3,tmp4,tmp6);
cvDiv(tmp6,tmp5,OFy);
}
int _harris(IplImage *src, float threshold, float *_cims) {
IplImage *deriX = derivateX(src);
IplImage *deriY = derivateY(src);
IplImage *deriXY = cvCloneImage(deriX);
//
cvMul(deriX, deriY, deriXY);
cvMul(deriX, deriX, deriX);
cvMul(deriY, deriY, deriY);
cvSmooth(deriX, deriX, CV_GAUSSIAN, 5);
cvSmooth(deriY, deriY, CV_GAUSSIAN, 5);
cvSmooth(deriXY, deriXY, CV_GAUSSIAN, 5);
int w = src->width;
int h = src->height;
float *cims = _cims;
float k = 0.06;
float *vals = new float[w * h];
memset(vals, 0, w * h);
for (int y = 0; y < h; y++) {
for (int x = 0; x < w; x++) {
float Ix = pixval32f(deriX, x, y);
float Iy = pixval32f(deriY, x, y);
float Ixy = pixval32f(deriXY, x, y);
float det = Ix * Iy - Ixy * Ixy;
float tr = Ix + Iy;
float cim = det - k * tr * tr;
// if (cim > threshold) {
// cims[y * w + x] = cim;
// } else
// cims[y * w + x] = 0.0;
cims[y * w + x] = cim;
vals[y * w + x] = cim;
}
}
sort(vals, vals + w * h);
int num = w * h > 500 ? 500 : w * h * 3 / 4;
// float thres = vals[w * h - 500];
float thres = 5000;
for (int y = filterSize; y < h - filterSize; y++) {
for (int x = filterSize; x < w- filterSize; x++) {
// if (cims[y * w + x] >= thres && is_extremun(cims, x, y, w, h, 10)) {
// }
// if (cims[y * w + x] < thres) {
// cims[y * w + x] = 0;
// }
}
}
delete [] vals;
cvReleaseImage(&deriX);
cvReleaseImage(&deriY);
cvReleaseImage(&deriXY);
return 0;
}
IplImage *harris_center(IplImage *img, float threshold) {
IplImage *src = get_gray(img);
IplImage *deriX = derivateX(src);
IplImage *deriY = derivateY(src);
IplImage *deriXY = cvCloneImage(src);
cvMul(deriX, deriY, deriXY);
cvMul(deriX, deriX, deriX);
cvMul(deriY, deriY, deriY);
cvSmooth(deriX, deriX, CV_GAUSSIAN, 5);
cvSmooth(deriY, deriY, CV_GAUSSIAN, 5);
cvSmooth(deriXY, deriXY, CV_GAUSSIAN, 5);
int w = src->width;
int h = src->height;
int centerX = w / 2;
int centerY = h / 2;
int ctrSize = w / 3;
float *cims = new float[(ctrSize + 1) * (ctrSize + 1)];
float *vals = new float[(ctrSize + 1) * (ctrSize + 1)];
memset(vals, 0, sizeof(vals));
int sx = centerX - ctrSize / 2;
int sy = centerY - ctrSize / 2;
float k = 0.06;
for (int i = 0; i < ctrSize; i++) {
for (int j = 0; j < ctrSize; j++) {
int x = sx + j;
int y = sy + i;
float Ix = pixval32f(deriX, x, y);
float Iy = pixval32f(deriY, x, y);
float Ixy = pixval32f(deriXY, x, y);
float det = Ix * Iy - Ixy * Ixy;
float tr = Ix + Iy;
float cim = det - k * tr * tr;
cims[i * ctrSize + j] = cim;
vals[i * ctrSize + j] = cim;
}
}
sort(vals, vals + ctrSize * ctrSize);
float thres = vals[ctrSize * ctrSize - 10];
IplImage *printImg = cvCloneImage(img);
for (int i = 0; i < ctrSize; i++) {
for (int j = 0; j < ctrSize; j++) {
if (cims[i * ctrSize + j] >= thres) {
drawPoint(printImg, sx + j, sy + i);
}
}
}
show_image(printImg, "center");
cvReleaseImage(&src);
cvReleaseImage(&deriX);
cvReleaseImage(&deriY);
cvReleaseImage(&deriXY);
return printImg;
}
IplImage *harris(IplImage *img, float threshold, float ***ptsDes, int *npts, int *ndes, t_point **_pts) {
IplImage *src = get_gray(img);
IplImage *deriX = derivateX(src);
IplImage *deriY = derivateY(src);
IplImage *deriXY = cvCloneImage(deriX);
//
cvMul(deriX, deriY, deriXY);
cvMul(deriX, deriX, deriX);
cvMul(deriY, deriY, deriY);
// cvNamedWindow("1", CV_WINDOW_AUTOSIZE);
// cvShowImage("1", deriX);
// cvWaitKey(0);
cvSmooth(deriX, deriX, CV_GAUSSIAN, 5);
cvSmooth(deriY, deriY, CV_GAUSSIAN, 5);
cvSmooth(deriXY, deriXY, CV_GAUSSIAN, 5);
// cvNamedWindow("1", CV_WINDOW_AUTOSIZE);
// cvShowImage("1", deriX);
// cvWaitKey(0);
IplImage *printImg = cvCloneImage(img);
int w = src->width;
int h = src->height;
float *cims = new float[w * h];
float *vals = new float[w * h];
float k = 0.06;
memset(vals, 0, sizeof(vals));
// t_point *pts =new t_point[w * h + 1]();
for (int y = 0; y < h; y++) {
for (int x = 0; x < w; x++) {
float Ix = pixval32f(deriX, x, y);
float Iy = pixval32f(deriY, x, y);
float Ixy = pixval32f(deriXY, x, y);
float det = Ix * Iy - Ixy * Ixy;
float tr = Ix + Iy;
float cim = det - k * tr * tr;
cims[y * w + x] = cim;
vals[y * w + x] = cim;
// pts[y * w + x].x = x;
// pts[y * w + x].y = y;
// pts[y * w + x].val = cim;
}
}
// cout << "ok\n";
// //sort(pts, pts + w * h, cmp);
// qsort(pts, sizeof(t_point), w * h, _cmp);
// cout << "ok\n";
// int num = w * h - 1;
// int feat = 0;
// int contentSize = filterSize;
// while (num-- >= 0) {
// int x = pts[num].x;
// int y = pts[num].y;
// if (x < contentSize || x > w - contentSize ||
// y < contentSize || y > w - contentSize)
// continue;
// if (is_extremun(cims, pts[num].x, pts[num].y, w, h, filterSize * 4)) {
// drawPoint(printImg, pts[num].x, pts[num].y);
// feat++;
// if (feat > 500)
// break;
// }
// }
sort(vals, vals + w * h);
//float thres = 7000;
int num = w * h > 4000 ? 4000 : w * h * 3 / 4;
float thres = vals[w * h - num];
t_point *pts = new t_point[4000];
int count = 0;
for (int y = filterSize; y < h - filterSize; y++) {
for (int x = filterSize; x < w- filterSize; x++) {
if (cims[y * w + x] >= thres && is_extremun(cims, x, y, w, h, filterSize)) {
// drawPoint(printImg, x, y);
if (cims[y * w + x] == vals[w * h - 1]) {
drawPoint(printImg, x, y);
}
pts[count].x = x;
pts[count++].y = y;
}
}
}
float **desc;
int descSize;
desc = describe_feature(src, pts, count, descSize);
// cout << "\n\n****************\n";
// for (int i = 0; i < count; i++) {
// for (int j = 0; j < descSize; j++) {
// cout << desc[i][j] << "\t";
// }
// cout << endl;
// }
/*return the result*/
*ptsDes = desc;
*npts = count;
*ndes = descSize;
*_pts = pts;
cvNamedWindow("1", CV_WINDOW_AUTOSIZE);
cvShowImage("1", printImg);
cvWaitKey(0);
delete [] vals;
delete [] cims;
cvReleaseImage(&src);
cvReleaseImage(&deriX);
cvReleaseImage(&deriY);
cvReleaseImage(&deriXY);
return printImg;
}
//------------------------------------------------------------------------------
//------------------------------------------------------------------------------
CvMat *tgso (CvMat &tmap, int ntex, double sigma, double theta, CvMat &tsim, int useChi2) {
CvMat *roundTmap=cvCreateMat(tmap.rows,tmap.cols,CV_32FC1);
CvMat *comp=cvCreateMat(tmap.rows,tmap.cols,CV_32FC1);
for (int i=0;i<tmap.rows;i++)
for (int j=0;j<tmap.cols;j++)
cvSetReal2D(roundTmap,i,j,cvRound(cvGetReal2D(&tmap,i,j)));
cvSub(&tmap,roundTmap,comp);
if (cvCountNonZero(comp)) {
printf("texton labels not integral");
cvReleaseMat(&roundTmap);
cvReleaseMat(&comp);
exit(1);
}
double min,max;
cvMinMaxLoc(&tmap,&min,&max);
if (min<1 && max>ntex) {
char *msg=new char[50];
printf(msg,"texton labels out of range [1,%d]",ntex);
cvReleaseMat(&roundTmap);
cvReleaseMat(&comp);
exit(1);
}
cvReleaseMat(&roundTmap);
cvReleaseMat(&comp);
double wr=floor(sigma); //sigma=radius (Leo)
CvMat *x=cvCreateMat(1,wr-(-wr)+1, CV_64FC1);
CvMat *y=cvCreateMat(wr-(-wr)+1,1, CV_64FC1);
CvMat *u=cvCreateMat(wr-(-wr)+1,wr-(-wr)+1, CV_64FC1);
CvMat *v=cvCreateMat(wr-(-wr)+1,wr-(-wr)+1, CV_64FC1);
CvMat *gamma=cvCreateMat(u->rows,v->rows, CV_64FC1);
// Set x,y directions
for (int j=-wr;j<=wr;j++) {
cvSetReal2D(x,0,(j+wr),j);
cvSetReal2D(y,(j+wr),0,j);
}
// Set u,v, meshgrids
for (int i=0;i<u->rows;i++) {
cvRepeat(x,u);
cvRepeat(y,v);
}
// Compute the gamma matrix from the grid
for (int i=0;i<u->rows;i++)
for (int j=0;j<u->cols;j++)
cvSetReal2D(gamma,i,j,atan2(cvGetReal2D(v,i,j),cvGetReal2D(u,i,j)));
cvReleaseMat(&x);
cvReleaseMat(&y);
CvMat *sum=cvCreateMat(u->rows,u->cols, CV_64FC1);
cvMul(u,u,u);
cvMul(v,v,v);
cvAdd(u,v,sum);
CvMat *mask=cvCreateMat(u->rows,u->cols, CV_8UC1);
cvCmpS(sum,sigma*sigma,mask,CV_CMP_LE);
cvConvertScale(mask,mask,1.0/255);
cvSetReal2D(mask,wr,wr,0);
int count=cvCountNonZero(mask);
cvReleaseMat(&u);
cvReleaseMat(&v);
cvReleaseMat(&sum);
CvMat *sub=cvCreateMat(mask->rows,mask->cols, CV_64FC1);
CvMat *side=cvCreateMat(mask->rows,mask->cols, CV_8UC1);
cvSubS(gamma,cvScalar(theta),sub);
cvReleaseMat(&gamma);
for (int i=0;i<mask->rows;i++){
for (int j=0;j<mask->cols;j++) {
double n=cvmGet(sub,i,j);
double n_mod = n-floor(n/(2*M_PI))*2*M_PI;
cvSetReal2D(side,i,j, 1 + int(n_mod < M_PI));
}
}
cvMul(side,mask,side);
cvReleaseMat(&sub);
cvReleaseMat(&mask);
CvMat *lmask=cvCreateMat(side->rows,side->cols, CV_8UC1);
CvMat *rmask=cvCreateMat(side->rows,side->cols, CV_8UC1);
cvCmpS(side,1,lmask,CV_CMP_EQ);
cvCmpS(side,2,rmask,CV_CMP_EQ);
int count1=cvCountNonZero(lmask), count2=cvCountNonZero(rmask);
if (count1 != count2) {
printf("Bug: imbalance\n");
}
CvMat *rlmask=cvCreateMat(side->rows,side->cols, CV_32FC1);
CvMat *rrmask=cvCreateMat(side->rows,side->cols, CV_32FC1);
cvConvertScale(lmask,rlmask,1.0/(255*count)*2);
cvConvertScale(rmask,rrmask,1.0/(255*count)*2);
cvReleaseMat(&lmask);
cvReleaseMat(&rmask);
cvReleaseMat(&side);
int h=tmap.rows;
int w=tmap.cols;
CvMat *d = cvCreateMat(h*w,ntex,CV_32FC1);
CvMat *coltemp = cvCreateMat(h*w,1,CV_32FC1);
CvMat *tgL = cvCreateMat(h,w, CV_32FC1);
CvMat *tgR = cvCreateMat(h,w, CV_32FC1);
CvMat *temp = cvCreateMat(h,w,CV_8UC1);
CvMat *im = cvCreateMat(h,w, CV_32FC1);
CvMat *sub2 = cvCreateMat(h,w,CV_32FC1);
CvMat *sub2t = cvCreateMat(w,h,CV_32FC1);
CvMat *prod = cvCreateMat(h*w,ntex,CV_32FC1);
CvMat reshapehdr,*reshape;
CvMat* tgL_pad = cvCreateMat(h+rlmask->rows-1,w+rlmask->cols-1,CV_32FC1);
CvMat* tgR_pad = cvCreateMat(h+rlmask->rows-1,w+rlmask->cols-1,CV_32FC1);
CvMat* im_pad = cvCreateMat(h+rlmask->rows-1,w+rlmask->cols-1,CV_32FC1);
CvMat *tg=cvCreateMat(h,w,CV_32FC1);
cvZero(tg);
if (useChi2 == 1){
CvMat* temp_add1 = cvCreateMat(h,w,CV_32FC1);
for (int i=0;i<ntex;i++) {
cvCmpS(&tmap,i+1,temp,CV_CMP_EQ);
cvConvertScale(temp,im,1.0/255);
cvCopyMakeBorder(tgL,tgL_pad,cvPoint((rlmask->cols-1)/2,(rlmask->rows-1)/2),IPL_BORDER_CONSTANT);
cvCopyMakeBorder(tgR,tgR_pad,cvPoint((rlmask->cols-1)/2,(rlmask->rows-1)/2),IPL_BORDER_CONSTANT);
cvCopyMakeBorder(im,im_pad,cvPoint((rlmask->cols-1)/2,(rlmask->rows-1)/2),IPL_BORDER_CONSTANT);
cvFilter2D(im_pad,tgL_pad,rlmask,cvPoint((rlmask->cols-1)/2,(rlmask->rows-1)/2));
cvFilter2D(im_pad,tgR_pad,rrmask,cvPoint((rlmask->cols-1)/2,(rlmask->rows-1)/2));
cvGetSubRect(tgL_pad,tgL,cvRect((rlmask->cols-1)/2,(rlmask->rows-1)/2,tgL->cols,tgL->rows));
cvGetSubRect(tgR_pad,tgR,cvRect((rlmask->cols-1)/2,(rlmask->rows-1)/2,tgR->cols,tgR->rows));
cvSub(tgL,tgR,sub2);
cvPow(sub2,sub2,2.0);
cvAdd(tgL,tgR,temp_add1);
cvAddS(temp_add1,cvScalar(0.0000000001),temp_add1);
cvDiv(sub2,temp_add1,sub2);
cvAdd(tg,sub2,tg);
}
cvScale(tg,tg,0.5);
cvReleaseMat(&temp_add1);
}
else{// if not chi^2
for (int i=0;i<ntex;i++) {
cvCmpS(&tmap,i+1,temp,CV_CMP_EQ);
cvConvertScale(temp,im,1.0/255);
cvCopyMakeBorder(tgL,tgL_pad,cvPoint((rlmask->cols-1)/2,(rlmask->rows-1)/2),IPL_BORDER_CONSTANT);
cvCopyMakeBorder(tgR,tgR_pad,cvPoint((rlmask->cols-1)/2,(rlmask->rows-1)/2),IPL_BORDER_CONSTANT);
cvCopyMakeBorder(im,im_pad,cvPoint((rlmask->cols-1)/2,(rlmask->rows-1)/2),IPL_BORDER_CONSTANT);
cvFilter2D(im_pad,tgL_pad,rlmask,cvPoint((rlmask->cols-1)/2,(rlmask->rows-1)/2));
cvFilter2D(im_pad,tgR_pad,rrmask,cvPoint((rlmask->cols-1)/2,(rlmask->rows-1)/2));
cvGetSubRect(tgL_pad,tgL,cvRect((rlmask->cols-1)/2,(rlmask->rows-1)/2,tgL->cols,tgL->rows));
cvGetSubRect(tgR_pad,tgR,cvRect((rlmask->cols-1)/2,(rlmask->rows-1)/2,tgR->cols,tgR->rows));
cvSub(tgL,tgR,sub2);
cvAbs(sub2,sub2);
cvTranspose(sub2,sub2t);
reshape=cvReshape(sub2t,&reshapehdr,0,h*w);
cvGetCol(d,coltemp,i);
cvCopy(reshape,coltemp);
}
cvMatMul(d,&tsim,prod);
cvMul(prod,d,prod);
CvMat *sumcols=cvCreateMat(h*w,1,CV_32FC1);
cvSetZero(sumcols);
for (int i=0;i<prod->cols;i++) {
cvGetCol(prod,coltemp,i);
cvAdd(sumcols,coltemp,sumcols);
}
reshape=cvReshape(sumcols,&reshapehdr,0,w);
cvTranspose(reshape,tg);
cvReleaseMat(&sumcols);
}
//Smooth the gradient now!!
tg=fitparab(*tg,sigma,sigma/4,theta);
cvMaxS(tg,0,tg);
cvReleaseMat(&im_pad);
cvReleaseMat(&tgL_pad);
cvReleaseMat(&tgR_pad);
cvReleaseMat(&rlmask);
cvReleaseMat(&rrmask);
cvReleaseMat(&im);
cvReleaseMat(&tgL);
cvReleaseMat(&tgR);
cvReleaseMat(&temp);
cvReleaseMat(&coltemp);
cvReleaseMat(&sub2);
cvReleaseMat(&sub2t);
cvReleaseMat(&d);
cvReleaseMat(&prod);
return tg;
}
static GstFlowReturn gst_gcs_transform_ip(GstBaseTransform * btrans, GstBuffer * gstbuf)
{
GstGcs *gcs = GST_GCS (btrans);
GST_GCS_LOCK (gcs);
//////////////////////////////////////////////////////////////////////////////
// get image data from the input, which is RGBA or BGRA
gcs->pImageRGBA->imageData = (char*)GST_BUFFER_DATA(gstbuf);
cvSplit(gcs->pImageRGBA, gcs->pImgCh1, gcs->pImgCh2, gcs->pImgCh3, gcs->pImgChX );
cvCvtColor(gcs->pImageRGBA, gcs->pImgRGB, CV_BGRA2BGR);
//////////////////////////////////////////////////////////////////////////////
////////////////////////////////////////////////////////MOTION CUES INTEGR////
//////////////////////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////////////////////
// apply step 1. filtering using bilateral filter. Cannot happen in-place => scratch
cvSmooth(gcs->pImgRGB, gcs->pImgScratch, CV_BILATERAL, 3, 50, 3, 0);
// create GRAY image
cvCvtColor(gcs->pImgScratch, gcs->pImgGRAY, CV_BGR2GRAY);
// Frame difference the GRAY and the previous one
// not intuitive: first smooth frames, then
cvCopy( gcs->pImgGRAY, gcs->pImgGRAY_copy, NULL);
cvCopy( gcs->pImgGRAY_1, gcs->pImgGRAY_1copy, NULL);
get_frame_difference( gcs->pImgGRAY_copy, gcs->pImgGRAY_1copy, gcs->pImgGRAY_diff);
cvErode( gcs->pImgGRAY_diff, gcs->pImgGRAY_diff, NULL, 3);
cvDilate( gcs->pImgGRAY_diff, gcs->pImgGRAY_diff, NULL, 3);
//////////////////////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////////////////////
// ghost mapping
gcs->dstTri[0].x = gcs->facepos.x - gcs->facepos.width/2 ;
gcs->dstTri[0].y = gcs->facepos.y - gcs->facepos.height/2;
gcs->dstTri[1].x = gcs->facepos.x - gcs->facepos.width/2;
gcs->dstTri[1].y = gcs->facepos.y + gcs->facepos.height/2;
gcs->dstTri[2].x = gcs->facepos.x + gcs->facepos.width/2;
gcs->dstTri[2].y = gcs->facepos.y + gcs->facepos.height/2;
if( gcs->ghostfilename){
cvGetAffineTransform( gcs->srcTri, gcs->dstTri, gcs->warp_mat );
cvWarpAffine( gcs->cvGhostBwResized, gcs->cvGhostBwAffined, gcs->warp_mat );
}
//////////////////////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////////////////////
// GrabCut algorithm preparation and running
gcs->facepos.x = gcs->facepos.x - gcs->facepos.width/2;
gcs->facepos.y = gcs->facepos.y - gcs->facepos.height/2;
// create an IplImage with the skin colour pixels as 255
compose_skin_matrix(gcs->pImgRGB, gcs->pImg_skin);
// And the skin pixels with the movement mask
cvAnd( gcs->pImg_skin, gcs->pImgGRAY_diff, gcs->pImgGRAY_diff);
//cvErode( gcs->pImgGRAY_diff, gcs->pImgGRAY_diff, cvCreateStructuringElementEx(5, 5, 3, 3, CV_SHAPE_RECT,NULL), 1);
cvDilate(gcs->pImgGRAY_diff, gcs->pImgGRAY_diff, cvCreateStructuringElementEx(7,7, 5,5, CV_SHAPE_RECT,NULL), 2);
cvErode( gcs->pImgGRAY_diff, gcs->pImgGRAY_diff, cvCreateStructuringElementEx(5,5, 3,3, CV_SHAPE_RECT,NULL), 2);
// if there is alpha==all 1's coming in, then we ignore it: prevents from no vibe before us
if((0.75*(gcs->width * gcs->height) <= cvCountNonZero(gcs->pImgChX)))
cvZero(gcs->pImgChX);
// OR the input Alpha
cvOr( gcs->pImgChX, gcs->pImgGRAY_diff, gcs->pImgGRAY_diff);
//////////////////////////////////////////////////////////////////////////////
// try to consolidate a single mask from all the sub-patches
cvDilate(gcs->pImgGRAY_diff, gcs->pImgGRAY_diff, cvCreateStructuringElementEx(7,7, 5,5, CV_SHAPE_RECT,NULL), 3);
cvErode( gcs->pImgGRAY_diff, gcs->pImgGRAY_diff, cvCreateStructuringElementEx(5,5, 3,3, CV_SHAPE_RECT,NULL), 4);
//////////////////////////////////////////////////////////////////////////////
// use either Ghost or boxes-model to create a PR foreground starting point in gcs->grabcut_mask
if( gcs->ghostfilename)
compose_grabcut_seedmatrix3(gcs->grabcut_mask, gcs->cvGhostBwAffined, gcs->pImgGRAY_diff );
else{
// toss it all to the bbox creation function, together with the face position and size
compose_grabcut_seedmatrix2(gcs->grabcut_mask, gcs->facepos, gcs->pImgGRAY_diff, gcs->facefound );
}
//////////////////////////////////////////////////////////////////////////////
#ifdef KMEANS
gcs->num_clusters = 18; // keep it even to simplify integer arithmetics
cvCopy(gcs->pImgRGB, gcs->pImgRGB_kmeans, NULL);
posterize_image(gcs->pImgRGB_kmeans);
create_kmeans_clusters(gcs->pImgRGB_kmeans, gcs->kmeans_points, gcs->kmeans_clusters,
gcs->num_clusters, gcs->num_samples);
adjust_bodybbox_w_clusters(gcs->grabcut_mask, gcs->pImgRGB_kmeans, gcs->num_clusters, gcs->facepos);
#endif //KMEANS
//////////////////////////////////////////////////////////////////////////////
if( gcs->debug < 70)
run_graphcut_iteration( &(gcs->GC), gcs->pImgRGB, gcs->grabcut_mask, &gcs->bbox_prev);
// get a copy of GRAY for the next iteration
cvCopy(gcs->pImgGRAY, gcs->pImgGRAY_1, NULL);
//////////////////////////////////////////////////////////////////////////////
// if we want to display, just overwrite the output
if( gcs->display ){
int outputimage = gcs->debug;
switch( outputimage ){
case 1: // output the GRAY difference
cvCvtColor( gcs->pImgGRAY_diff, gcs->pImgRGB, CV_GRAY2BGR );
break;
case 50:// Ghost remapped
cvCvtColor( gcs->cvGhostBwAffined, gcs->pImgRGB, CV_GRAY2BGR );
break;
case 51:// Ghost applied
cvAnd( gcs->cvGhostBwAffined, gcs->pImgGRAY, gcs->pImgGRAY, NULL );
cvCvtColor( gcs->pImgGRAY, gcs->pImgRGB, CV_GRAY2BGR );
break;
case 60:// Graphcut
cvAndS(gcs->grabcut_mask, cvScalar(1), gcs->grabcut_mask, NULL); // get only FG
cvConvertScale( gcs->grabcut_mask, gcs->grabcut_mask, 127.0);
cvCvtColor( gcs->grabcut_mask, gcs->pImgRGB, CV_GRAY2BGR );
break;
case 61:// Graphcut applied on input/output image
cvAndS(gcs->grabcut_mask, cvScalar(1), gcs->grabcut_mask, NULL); // get only FG, PR_FG
cvConvertScale( gcs->grabcut_mask, gcs->grabcut_mask, 255.0);
cvAnd( gcs->grabcut_mask, gcs->pImgGRAY, gcs->pImgGRAY, NULL);
cvCvtColor( gcs->pImgGRAY, gcs->pImgRGB, CV_GRAY2BGR );
cvRectangle(gcs->pImgRGB, cvPoint(gcs->bbox_now.x, gcs->bbox_now.y),
cvPoint(gcs->bbox_now.x + gcs->bbox_now.width, gcs->bbox_now.y+gcs->bbox_now.height),
cvScalar(127,0.0), 1, 8, 0 );
break;
case 70:// bboxes
cvZero( gcs->pImgGRAY );
cvMul( gcs->grabcut_mask, gcs->grabcut_mask, gcs->pImgGRAY, 40.0 );
cvCvtColor( gcs->pImgGRAY, gcs->pImgRGB, CV_GRAY2BGR );
break;
case 71:// bboxes applied on the original image
cvAndS(gcs->grabcut_mask, cvScalar(1), gcs->grabcut_mask, NULL); // get only FG, PR_FG
cvMul( gcs->grabcut_mask, gcs->pImgGRAY, gcs->pImgGRAY, 1.0 );
cvCvtColor( gcs->pImgGRAY, gcs->pImgRGB, CV_GRAY2BGR );
break;
case 72: // input alpha channel mapped to output
cvCvtColor( gcs->pImgChX, gcs->pImgRGB, CV_GRAY2BGR );
break;
#ifdef KMEANS
case 80:// k-means output
cvCopy(gcs->pImgRGB_kmeans, gcs->pImgRGB, NULL);
break;
case 81:// k-means output filtered with bbox/ghost mask
cvSplit(gcs->pImgRGB_kmeans, gcs->pImgCh1, gcs->pImgCh2, gcs->pImgCh3, NULL );
cvAndS(gcs->grabcut_mask, cvScalar(1), gcs->grabcut_mask, NULL); // get FG and PR_FG
cvConvertScale( gcs->grabcut_mask, gcs->grabcut_mask, 255.0); // scale any to 255.
cvAnd( gcs->grabcut_mask, gcs->pImgCh1, gcs->pImgCh1, NULL );
cvAnd( gcs->grabcut_mask, gcs->pImgCh2, gcs->pImgCh2, NULL );
cvAnd( gcs->grabcut_mask, gcs->pImgCh3, gcs->pImgCh3, NULL );
cvMerge( gcs->pImgCh1, gcs->pImgCh2, gcs->pImgCh3, NULL, gcs->pImgRGB);
break;
#endif //KMEANS
default:
break;
}
}
//////////////////////////////////////////////////////////////////////////////
// copy anyhow the fg/bg to the alpha channel in the output image alpha ch
cvSplit(gcs->pImgRGB, gcs->pImgCh1, gcs->pImgCh2, gcs->pImgCh3, NULL );
cvAndS(gcs->grabcut_mask, cvScalar(1), gcs->grabcut_mask, NULL); // get only FG and possible FG
cvConvertScale( gcs->grabcut_mask, gcs->grabcut_mask, 255.0);
gcs->pImgChA->imageData = (char*)gcs->grabcut_mask->data.ptr;
cvMerge( gcs->pImgCh1, gcs->pImgCh2, gcs->pImgCh3, gcs->pImgChA, gcs->pImageRGBA);
gcs->numframes++;
GST_GCS_UNLOCK (gcs);
return GST_FLOW_OK;
}