void SLICSegmentor::Run()
{
cout<<"====="<<m_Name<<" Runing..."<<endl;
SLIC slicsp;
int h = m_Img.rows, w = m_Img.cols;
uint* imgData = new uint[h*w];
for (int i = 0; i < h; i++)
{
for (int j = 0; j < w; j++)
{
cv::Vec3b bgr = m_Img.at<cv::Vec3b>(i, j);
imgData[i*w+j] = (bgr[2]<<16) | (bgr[1]<<8) | (bgr[0]);
}
}
int numLabels;
int *klabels = new int[h*w];
slicsp.PerformSLICO_ForGivenStepSize(imgData, w, h, klabels, numLabels, m_Step, NULL);
for (int i = 0; i < h; i++)
{
int* ptr = m_Result.ptr<int>(i);
for (int j = 0; j < w; j++)
{
ptr[j] = klabels[i*w+j];
}
}
delete[] klabels;
delete[] imgData;
Segmentor::Run();
}
int _tmain(int argc, _TCHAR* argv[]) {
#else
int main(int argc, char **argv) {
#endif
if(argc != 2 && argc != 3) {
fprintf(stderr, "Usage: sc <img1>\n");
return 1;
}
int spSize = 5;
if(argc == 3) {
sscanf(argv[2], "%d", &spSize);
}
ImageFile imgFile (argv[1]);
if(!imgFile.Load()) {
fprintf(stderr, "Error loading file: %s\n", argv[1]);
return 1;
}
FasTC::Image<> *img = imgFile.GetImage();
const int kWidth = img->GetWidth();
const int kHeight = img->GetHeight();
const int nPixels = kWidth * kHeight;
const uint32 pixelBufSz = nPixels * sizeof(FasTC::Pixel);
FasTC::Pixel *pixels = new FasTC::Pixel[pixelBufSz];
memcpy(pixels, img->GetPixels(), pixelBufSz);
uint32 *rawPixels = new uint32[kWidth * kHeight];
for(int i = 0; i < nPixels; i++) {
// Pixels are stored as little endian ARGB, so we want ABGR
pixels[i].Shuffle(0x6C); // 01 10 11 00
rawPixels[i] = pixels[i].Pack();
}
int *labels = new int[nPixels];
int numLabels;
SLIC slic;
slic.PerformSLICO_ForGivenStepSize(
rawPixels,
kWidth,
kHeight,
labels,
numLabels,
spSize, 1.0);
std::unordered_map<uint32, Region> regions;
CollectPixels(kWidth, kHeight, pixels, labels, regions);
std::cout << "Num regions: " << regions.size() << std::endl;
for(auto &r : regions) {
r.second.Compress();
r.second.Reconstruct();
}
for(int i = 0; i < nPixels; i++) {
pixels[i] = regions[labels[i]].GetNextPixel();
pixels[i].Shuffle(0x6C);
}
std::vector<Partition<4, 4> > partitions;
EnumerateBPTC(partitions);
std::cout << partitions.size() << " 4x4 BPTC partitions" << std::endl;
VpTree<Partition<4, 4>, Partition<4, 4>::Distance> vptree;
vptree.create(partitions);
// Just to test, find the partition close to half 0 half 1..
Partition<4, 4> test;
for(uint32 i = 0; i < 16; i++) {
if(i < 8) {
test[i] = 0;
} else {
test[i] = 1;
}
}
vector<Partition<4, 4> > closest;
vptree.search(test, 1, &closest, NULL);
std::cout << closest[0].GetIndex() << std::endl;
BPTCC::CompressionSettings settings;
settings.m_NumSimulatedAnnealingSteps = 0;
settings.m_ShapeSelectionFn = ChosePresegmentedShape<4, 4>;
SelectionInfo info(vptree, labels, kWidth, kHeight);
settings.m_ShapeSelectionUserData = &info;
uint8 *outBuf = new uint8[kWidth * kHeight];
FasTC::CompressionJob cj(
FasTC::eCompressionFormat_BPTC,
reinterpret_cast<const uint8 *>(pixels),
outBuf,
static_cast<uint32>(kWidth),
static_cast<uint32>(kHeight));
StopWatch sw;
sw.Start();
BPTCC::Compress(cj, settings);
sw.Stop();
std::cout << "Compression time: " << sw.TimeInMilliseconds() << "ms" << std::endl;
CompressedImage ci(kWidth, kHeight, FasTC::eCompressionFormat_BPTC, outBuf);
FasTC::Image<> outImg(kWidth, kHeight, pixels);
std::cout << "PSNR: " << outImg.ComputePSNR(&ci) << "db" << std::endl;
ImageFile outImgFile("out.png", eFileFormat_PNG, outImg);
outImgFile.Write();
delete [] labels;
delete [] rawPixels;
delete [] pixels;
return 0;
}