Function mindspore::dataset::Manifest

Function Documentation

inline std::shared_ptr<ManifestDataset> mindspore::dataset::Manifest(const std::string &dataset_file, const std::string &usage = "train", const std::shared_ptr<Sampler> &sampler = std::make_shared<RandomSampler>(), const std::map<std::string, int32_t> &class_indexing = {}, bool decode = false, const std::shared_ptr<DatasetCache> &cache = nullptr)

Function to create a ManifestDataset.

Note

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

Parameters

  • dataset_file – [in] The dataset file to be read.

  • usage – [in] Part of dataset of ManifestDataset, can be “train”, “eval” or “inference” data (default=”train”).

  • 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()).

  • class_indexing – [in] A str-to-int mapping from label name to index (default={}, the folder names will be sorted alphabetically and each class will be given a unique index starting from 0).

  • 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 ManifestDataset.