OpenCVUnlabeledDataSet::OpenCVUnlabeledDataSet(std::string classesListFile,
std::string dataDirectory,
std::string wildcard,
int backgroundCol, bool loadData,
int flags) {
name = dataDirectory;
header = "image";
type = UNLABELEDBATCH;
if (flags == 0)
nFeatures = 1;
if (flags == 1)
nFeatures = 3;
{
std::ifstream f(classesListFile.c_str());
std::string cl;
int ctr = 0;
while (f >> cl) {
classes[cl] = ctr++;
header += "," + cl;
}
}
nClasses = classes.size();
for (auto &file : globVector(dataDirectory + "/" + wildcard)) {
OpenCVPicture *pic = new OpenCVPicture(file, backgroundCol, 0);
pictures.push_back(pic);
}
if (loadData) {
std::vector<std::thread> workers;
int nThreads = 4;
for (int nThread = 0; nThread < nThreads; ++nThread)
workers.emplace_back(loadDataThread, &pictures, flags, nThread, nThreads);
for (int nThread = 0; nThread < nThreads; ++nThread)
workers[nThread].join();
}
}
SpatiallySparseDataset ImageNet2012TrainSet() {
SpatiallySparseDataset dataset;
dataset.name="ImageNet2012 train set";
dataset.type=TRAINBATCH;
dataset.nFeatures=3;
dataset.nClasses=1000;
for (int cl=0;cl<1000;cl++) {
for (auto &file : globVector(std::string("Data/imagenet2012/ILSVRC2012_img_train/")+classList[cl]+"/*.JPEG")) {
dataset.pictures.push_back(new OpenCVPicture(file,128,cl));
}
}
return dataset;
}
KagglePlanktonLabeledDataSet::KagglePlanktonLabeledDataSet
(std::string classesListFile, std::string dataDirectory, batchType type_, int backgroundCol) {
name=dataDirectory;
type=type_;
{
std::ifstream f(classesListFile.c_str());
std::string cl;
int ctr=0;
while (f >> cl)
classes[cl]=ctr++;
}
nClasses=classes.size();
for (auto &kv : classes) {
for (auto &file : globVector(dataDirectory+kv.first+"/*.jpg")) {
OpenCVPicture* pic = new OpenCVPicture(file,-1,backgroundCol,kv.second);
pic->loadDataWithoutScaling();
nFeatures=pic->mat.channels();
pic->scale=powf(powf(pic->mat.rows,2)+powf(pic->mat.cols,2),0.5);
pictures.push_back(pic);
}
}
}
KagglePlanktonUnlabeledDataSet::KagglePlanktonUnlabeledDataSet
(std::string classesListFile, std::string dataDirectory, int backgroundCol) {
name=dataDirectory;
header="image";
type=UNLABELEDBATCH;
{
std::ifstream f(classesListFile.c_str());
std::string cl;
int ctr=0;
while (f >> cl) {
classes[cl]=ctr++;
header=header+","+cl;
}
}
nClasses=classes.size();
for (auto &file : globVector(std::string(dataDirectory+"*.jpg"))) {
OpenCVPicture* pic = new OpenCVPicture(file,-1,backgroundCol,0);
pic->loadDataWithoutScaling();
nFeatures=pic->mat.channels();
pic->scale=powf(powf(pic->mat.rows,2)+powf(pic->mat.cols,2),0.5);
pictures.push_back(pic);
}
}
