void ColorSpace::RGBtoLab (CoImage* pIn, CoImage* pOut)
{
assert (pIn->GetType() == MAT_Tbyte);
assert (pOut->GetType() == MAT_Tfloat);
BYTE* pbR = pIn->m_matX.data.ptr[0];
BYTE* pbG = pIn->m_matY.data.ptr[0];
BYTE* pbB = pIn->m_matZ.data.ptr[0];
float* prL = pOut->m_matX.data.fl[0];
float* pra = pOut->m_matY.data.fl[0];
float* prb = pOut->m_matZ.data.fl[0];
for (int i = 0; i < pIn->GetHeight() * pIn->GetWidth(); i ++)
{
RGBtoLab(pbR[i], pbG[i], pbB[i], &prL[i], &pra[i], &prb[i]);
}
}
CGImageRef Image::createAbstraction(float stylization, uint quantization)
{
pixel4b *rgbPixels = (pixel4b *) CFDataGetMutableBytePtr(_data);
// Convert from RGB to Lab colorspace to perform operations on lightness channel.
RGBtoLab(rgbPixels, _pixels);
// Initial bilateral filter.
bilateral();
// Extract edges.
pixel3f *edges = createEdges(stylization);
// Additional bilateral filtering.
bilateral();
bilateral();
// Quantize lightness channel.
quantize(quantization);
// Overlay edges.
overlayEdges(edges);
// Convert back to RGB colorspace.
LabtoRGB(_pixels, rgbPixels);
// Create an image from the modified data.
CGContextRef context = CGBitmapContextCreate(
rgbPixels,
_width,
_height,
_bitsPerComponent,
_bytesPerRow,
_colorSpaceRef,
_bitmapInfo
);
CGImageRef image = CGBitmapContextCreateImage(context);
delete[] edges;
return image;
}
int main( int argc, char * argv[]){
/**** Read the IO ****/
if (argc<3){
qWarning( "Usage: %s texton_file type [params ..]", argv[0] );
qWarning( " type :");
qWarning( " FilterBank [nTextons filterbank_size]" );
qWarning( " Color [nTextons]" );
qWarning( " HoG [nTextons L/A/B]" );
qWarning( " Location [nTextons]" );
// qWarning( " BBox [nTextons]" );
return 1;
}
QString save_filename = argv[1];
QString type = argv[2];
type = type.toLower();
int n_textons = N_TEXTONS;
if (argc>3)
n_textons = QString( argv[3] ).toInt();
QSharedPointer<Feature> filter;
if (type == "filterbank"){
float filterbank_size = FILTER_BANK_SIZE;
if (argc>4)
filterbank_size = QString( argv[4] ).toFloat();
filter = QSharedPointer<Feature>( new FilterBank( filterbank_size ) );
}
else if (type == "color"){
filter = QSharedPointer<Feature>( new ColorFeature() );
}
else if (type == "location"){
filter = QSharedPointer<Feature>( new LocationFeature() );
}
else if (type == "hog"){
HogFeature::HogFeatureType type = HogFeature::L;
if (argc>4){
QString t = QString( argv[4] ).toLower();
if (t=="a") type = HogFeature::A;
if (t=="b") type = HogFeature::B;
}
filter = QSharedPointer<Feature>( new HogFeature(type) );
}
else if (type == "bbox"){
filter = QSharedPointer<Feature>( new BBoxFeature() );
}
else
qFatal( "Unknown feature %s", qPrintable( type ) );
// Declare all variables we need for both training and evaluation
QVector< ColorImage > images;
QVector< Image<float> > lab_images;
QVector< LabelImage > labels;
QVector< QString > names;
/**** Training ****/
qDebug("(train) Loading the database");
loadImages( images, labels, names, TRAIN );
// Color Conversion
qDebug("(train) Converting to Lab");
lab_images = RGBtoLab( images );
// Training
qDebug("(train) Training Textons");
Texton texton( filter, n_textons );
texton.train( lab_images, names );
/**** Evaluation ****/
qDebug("(test) Loading the database");
loadImages( images, labels, names, ALL );
// Color Conversion
qDebug("(test) Converting to Lab");
lab_images = RGBtoLab( images );
// Evalutation
qDebug("(test) Textonizing");
QVector< Image<short> > textons = texton.textonize( lab_images, names );
/**** Storing textons ****/
saveTextons( save_filename, textons, names );
}
