Function mindspore::dataset::Caltech256

Function Documentation

inline std::shared_ptr<Caltech256Dataset> mindspore::dataset::Caltech256(const std::string &dataset_dir, const std::shared_ptr<Sampler> &sampler = std::make_shared<RandomSampler>(), bool decode = false, const std::shared_ptr<DatasetCache> &cache = nullptr)

Function to create a Caltech256Dataset.

Note

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

Parameters

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

  • 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()).

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

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

Returns

Shared pointer to the Caltech256Dataset.

Example
/* Define dataset path and MindData object */
std::string dataset_path = "/path/to/caltech256_dataset_directory";
std::shared_ptr<Dataset> ds = Caltech256(dataset_path, true, std::make_shared<RandomSampler>(false, 10));

/* 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 Caltech256 dataset, each data dictionary has keys "image" and "label" */
auto image = row["image"];