void AR_sports::load(const string &path, int number)
{
if (number!=0)
{
return;
}
loadDataset(path);
}
void OR_mnistImp::load(const string &path)
{
loadDataset(path);
}
void HPE_parseImp::load(const string &path)
{
loadDataset(path);
}
void PD_caltechImp::load(const string &path)
{
loadDataset(path);
}
void IS_weizmannImp::load(const string &path)
{
loadDataset(path);
}
void TR_svtImp::load(const string &path)
{
loadDataset(path);
}
void MSM_middleburyImp::load(const string &path)
{
loadDataset(path);
}
void MultipleDatasetComparisonSecondExperiment::runExperiment(std::string outputDir)
{
// Set up the image filters
DownsampleFilter dsf(64, 64); // Dataset images are in a 1:1 ratio.
GreyscaleFilter gf;
std::list<ImageFilterInterface*> filters;
filters.push_back(&dsf);
filters.push_back(&gf);
// Load the reference dataset
std::unique_ptr<CachedDataset> referenceDataset = loadDataset(
MultipleDatasetComparisonSecondExperiment::TIME_OF_DAY_NOON,
MultipleDatasetComparisonSecondExperiment::PASS_BASELINE,
filters);
std::cout << "Loaded reference dataset... (" << referenceDataset->count() << " images)" << std::endl;
// Set up the place recognition object, salience mask generator, and output image
PlaceRecognition placerecog;
SumOfAbsoluteDifferencesMatcher sadMatcher;
cv::Mat diagonalMatrix;
float performance;
// Create a RapidJson document to write the results into.
rapidjson::Document results(rapidjson::kObjectType);
// Set some standard criteria for considering two images to have a 'similar' location
SimilarityCriteria similarityCriteria(300.0);
// For each test time of day, for each pass through, measure the performance
// This will match the reference set against itself
for (int timeOfDay = MultipleDatasetComparisonSecondExperiment::TIME_OF_DAY_DAWN;
timeOfDay <= MultipleDatasetComparisonSecondExperiment::TIME_OF_DAY_SUNSET; ++timeOfDay)
{
std::string timeOfDayString = getTimeOfDayString(timeOfDay);
rapidjson::Value nestedResults(rapidjson::kObjectType);
for (int pass = MultipleDatasetComparisonSecondExperiment::PASS_FIRST;
pass <= MultipleDatasetComparisonSecondExperiment::PASS_LAST; ++pass)
{
std::string passString = getPassString(pass);
std::unique_ptr<CachedDataset> queryDataset = loadDataset(timeOfDay, pass, filters);
std::cout << "Loaded test dataset \"" << timeOfDayString << "\" subset \"" << passString << "\" (" << queryDataset->count() << " images)" << std::endl;
performance = placerecog.generateDiagonalMatrix(*referenceDataset, *queryDataset, sadMatcher, similarityCriteria, diagonalMatrix);
writeFloatImage(outputDir + "\\diagonal matrix " + timeOfDayString + " " + passString + ".png", diagonalMatrix);
std::cout << "Matching accuracy for " << timeOfDayString << " " << passString << ": " << (performance * 100) << "%" << std::endl;
nestedResults.AddMember(
rapidjson::Value(passString.c_str(), results.GetAllocator()).Move(),
performance,
results.GetAllocator());
}
results.AddMember(
rapidjson::Value(timeOfDayString.c_str(), results.GetAllocator()).Move(),
nestedResults,
results.GetAllocator());
}
// Serialze the json output.
rapidjson::StringBuffer jsonBuffer;
rapidjson::PrettyWriter<rapidjson::StringBuffer> jsonWriter(jsonBuffer);
results.Accept(jsonWriter);
// Write the json file to a string
std::ofstream output(outputDir + "\\multiple comparison results.txt");
output << jsonBuffer.GetString();
output.close();
}
void TRACK_votImpl::load(const string &path)
{
loadDataset(path);
}
void GR_skigImp::load(const string &path)
{
loadDataset(path);
}
void OR_sunImp::load(const string &path)
{
loadDataset(path);
}
void TR_charsImp::load(const string &path)
{
loadDataset(path);
}
void loadCifar()
{
loadDataset(string(DATASET_LOCATION) + "cifar-10/");
}
void loadCaltech(){
loadDataset(string(DATASET_LOCATION) + "caltech101/");
}
void SLAM_tumindoorImp::load(const string &path)
{
loadDataset(path);
}
void IR_affineImp::load(const string &path)
{
loadDataset(path);
}
