ColormapFunction::ColormapFunction()
{
invert_ = false;
reverse_ = false;
redScale_ = greenScale_ = blueScale_ = 1.0;
setScales( 0.0, 0.0);
}
ColormapFunction::ColormapFunction(
PWLinear & red, PWLinear & green, PWLinear & blue)
{
red_ = red; green_ = green; blue_ = blue;
invert_ = false;
reverse_ = false;
redScale_ = greenScale_ = blueScale_ = 1.0;
setScales( 0.0, 0.0);
}
matrix<double>& EvolDF1nlep::Df1Evolnlep(double mu, double M, orders order, orders_ew order_ew, schemes scheme) {
switch (scheme) {
case NDR:
break;
case LRI:
case HV:
default:
std::stringstream out;
out << scheme;
throw std::runtime_error("EvolDF1nlep::Df1Evolnlep_EM(): scheme " + out.str()
+ " not implemented ");
}
if (mu == this->mu && M == this->M && scheme == this->scheme && order_ew == NULL_ew)
return (*Evol(order));
if (mu == this->mu && M == this->M && scheme == this->scheme && order_ew == NLO_ew)
return (*Evol(order_ew));
if (M < mu) {
std::stringstream out;
out << "M = " << M << " < mu = " << mu;
throw out.str();
}
setScales(mu, M); // also assign evol to identity
double m_down = mu;
double m_up = model.AboveTh(m_down);
double nf = model.Nf(m_down);
while (m_up < M) {
Df1Evolnlep(m_down, m_up, nf, scheme);
Df1threshold_nlep(m_up, nf+1.);
m_down = m_up;
m_up = model.AboveTh(m_down);
nf += 1.;
}
Df1Evolnlep(m_down, M, nf, scheme);
if(order_ew != NULL_ew){
return (*Evol(order_ew));
}
else {
return (*Evol(order));
}
}
StarDetector::StarDetector(CvSize size, int n, float response_threshold,
float line_threshold_projected,
float line_threshold_binarized)
: m_upright(NULL),
m_tilted(NULL),
m_flat(NULL),
m_projected(NULL),
m_scales(NULL),
m_filter_sizes(NULL),
m_nonmax(response_threshold,
LineSuppressHybrid(line_threshold_projected,
line_threshold_binarized)),
m_filter_params(NULL)
{
// Pre-allocate all the memory we need
setScales(n);
setImageSize(size);
}
gslpp::matrix<double>& EvolDC1Buras::DC1EvolBuras(double mu, double M, orders order, schemes scheme)
{
switch (scheme) {
case NDR:
break;
case LRI:
case HV:
default:
std::stringstream out;
out << scheme;
throw std::runtime_error("EvolDC1::Df1EvolDC1(): scheme " + out.str() + " not implemented ");
}
double alsMZ = model.getAlsMz();
double Mz = model.getMz();
if(alsMZ == alsMZ_cache && Mz == Mz_cache) {
if (mu == this-> mu && M == this->M && scheme == this->scheme)
return (*Evol(order));
}
alsMZ_cache = alsMZ;
Mz_cache = Mz;
if (M < mu) {
std::stringstream out;
out << "M = " << M << " < mu = " << mu;
throw out.str();
}
setScales(mu, M); // also assign evol to identity
double m_down = mu;
double m_up = model.AboveTh(m_down);
double nf = model.Nf(m_down);
while (m_up < M) {
DC1EvolBuras(m_down, m_up, nf, scheme);
DC1PenguinThresholds(m_up, order);
m_down = m_up;
m_up = model.AboveTh(m_down);
nf += 1.;
}
DC1EvolBuras(m_down, M, nf, scheme);
return (*Evol(order));
}
void Transform3D::setScales(float s)
{
setScales(s, s, s);
}
void FeatPyramid::featpyramid (const IplImage *im, const Model *model, int padX, int padY)
{
float sbin, interval;
float sc;
int imsize[2];
float maxScale;
IplImage *imAux = NULL;
int pad[3];
if (padX == -1 && padY == -1)
{
padX = getPaddingX(model);
padY = getPaddingY(model);
}
sbin = (float)model->getSbin();
interval = (float) model->getInterval()+1.0;
sc = pow (2, 1/(interval));
imsize[0] = im->height;
imsize[1] = im->width;
maxScale = 1 + floor ( log ( min (imsize[0], imsize[1]) /
(5*sbin) ) / log(sc) );
// It is the number of elements that will contain pyramid->features
// and pyramid->scales. At less must be 2*interval
if ( (maxScale + interval) < (2*interval) )
setDim (int(2*interval));
else
setDim (int(maxScale + interval));
assert (getDim() > 0);
// _feat = new CvMatND* [getDim()]; // Suspicious
_feat.reserve(getDim());
for (int i = 0; i < getDim(); i++) // Pre-allocate memory
_feat.push_back(cv::Mat());
// assert (_feat != NULL);
assert(!_feat.empty());
_scales = new float [getDim()]; // Suspicious
assert (_scales != NULL);
// Field imsize is setted
assert (imsize[0] > 0);
assert (imsize[1] > 0);
setImSize (imsize);
//cout << "Antes de bucle featpyramid" << endl;
for (int i = 0; i < interval; i++)
{
// Image is resized
imAux = resize (im, (1/pow(sc, i)));
// "First" 2x interval
//setFeat(process(imAux, sbin/2), i);
setFeat(process2(imAux, sbin/2), i);
setScales(2/pow(sc, i), i);
// "Second" 2x interval
//setFeat (process (imAux, sbin), (int)(i+interval));
setFeat (process2 (imAux, sbin), (int)(i+interval));
setScales (1/pow(sc, i), (int)(i+interval));
// Remaining intervals
IplImage *imAux2; // mjmarin added
for (int j = (int)(i+interval); j < (int)maxScale; j = j+(int)interval)
{
// mjmarin: memory leak fixed
//imAux = resize (imAux, 0.5); // Old sentence
imAux2 = resize (imAux, 0.5);
cvReleaseImage(&imAux);
imAux = imAux2;
//setFeat (process (imAux, sbin), (int)(j+interval));
setFeat (process2 (imAux, sbin), (int)(j+interval));
setScales ((float)(0.5 * getScales()[j]), (int)(j+interval));
}
// mjmarin: more release needed for imAux
cvReleaseImage(&imAux);
}
// Second loop
for (int i = 0; i < getDim(); i++ )
{
// Add 1 to padding because feature generation deletes a 1-cell
// Wide border around the feature map
pad[0] = padY + 1;
pad[1] = padX + 1;
pad[2] = 0;
//CvMatND* tmpfeat = getFeat()[i];
cv::Mat tmpfeat = getFeat()[i];
CvMatND tmpND = tmpfeat;
//CvMatND* tmppad = padArray (tmpfeat, pad, 0);
CvMatND* tmppad = padArray (&tmpND, pad, 0);
setFeat (tmppad, i);
//cvReleaseMatND(&tmpfeat); // mjmarin: commented out since it should be auto released with use of cv::Mat
// Write boundary occlusion feature
cv::Mat fMat = getFeat()[i];
for (int j = 0; j <= padY; j++)
//for (int k = 0; k < getFeat()[i]->dim[1].size; k++)
for (int k = 0; k < fMat.size.p[1]; k++)
//cvSetReal3D (getFeat()[i], j, k, 31, 1);
fMat.at<double>(j, k, 31) = 1;
//for (int j = getFeat()[i]->dim[0].size - padY -1; j < getFeat()[i]->dim[0].size; j++)
for (int j = fMat.size.p[0] - padY -1; j < fMat.size.p[0]; j++)
//for (int k = 0; k < getFeat()[i]->dim[1].size; k++)
for (int k = 0; k < fMat.size.p[1]; k++)
//cvSetReal3D (getFeat()[i], j, k, 31, 1);
fMat.at<double>(j, k, 31) = 1;
//for (int j = 0; j < getFeat()[i]->dim[0].size; j++)
for (int j = 0; j < fMat.size.p[0]; j++)
for (int k = 0; k <= padX; k++)
//cvSetReal3D (getFeat()[i], j, k, 31, 1);
fMat.at<double>(j, k, 31) = 1;
//for (int j = 0; j < getFeat()[i]->dim[0].size; j++)
for (int j = 0; j < fMat.size.p[0]; j++)
//for (int k = getFeat()[i]->dim[1].size - padX - 1; k < getFeat()[i]->dim[1].size; k++)
for (int k = fMat.size.p[1] - padX - 1; k < fMat.size.p[1]; k++)
//cvSetReal3D (getFeat()[i], j, k, 31, 1);
fMat.at<double>(j, k, 31) = 1;
}
setPadX (padX);
setPadY (padY);
}
