Function mindspore::dataset::Omniglot

Function Documentation

inline std::shared_ptr<OmniglotDataset> mindspore::dataset::Omniglot(const std::string &dataset_dir, bool background = true, bool decode = false, const std::shared_ptr<Sampler> &sampler = std::make_shared<RandomSampler>(), const std::shared_ptr<DatasetCache> &cache = nullptr)

Function to create an OmniglotDataset.

Note

The generated dataset has two columns [“image”, “label”].

Parameters
  • dataset_dir[in] Path to the root directory that contains the dataset.

  • background[in] A flag to use background dataset or evaluation dataset (Default=true).

  • decode[in] Decode the images after reading (Default=false).

  • sampler[in] Shared pointer to a sampler object used to choose samples from the dataset. If sampler is not given, a RandomSampler will be used to randomly iterate the entire dataset (default = RandomSampler()).

  • cache[in] Tensor cache to use (default=nullptr, which means no cache is used).

Returns

Shared pointer to the current OmniglotDataset.

样例
/* Define dataset path and MindData object */
std::string folder_path = "/path/to/omniglot_dataset_directory";
std::shared_ptr<Dataset> ds = Omniglot(folder_path, true, false, std::make_shared<RandomSampler>(false, 5));

/* Create iterator to read dataset */
std::shared_ptr<Iterator> iter = ds->CreateIterator();
std::unordered_map<std::string, mindspore::MSTensor> row;
iter->GetNextRow(&row);

/* Note: In Omniglot dataset, each dictionary has keys "image" and "label" */
auto image = row["image"];