mindspore::dataset
This module provides APIs to load and process various common datasets, currently supports Album and MNIST datasets.
Besides, this module provides APIs to sample data while loading.
Notice that cache is not supported on Windows platform yet. Please do not use it while loading and processing data on Windows.
Dataset Functions
Dataset Functions provides various functions to load and process datasets.
Vision
API |
Descriptions |
Extra overload APIs (Parameter Sampler is overloaded) |
|---|---|---|
A source dataset for reading and parsing Album dataset and return an object of Class AlbumDataset. |
||
A source dataset for reading and parsing the MNIST dataset and return an object of Class MnistDataset. |
Dataset Classes
Dataset Classes provides the definition of base class of dataset and common transform operations of dataset such as map, shuffle and batch. It also provides the definition of Iterator for fetching data.
Sampler Classes
Sampler Classes provides the definitions of samplers, which are used to choose samples from the dataset.
Eager Classes
Eager Classes provides the definitions of Execute class, which is used to apply transforms (e.g. vision/text) on input tensor in eager mode.
Constants
Constants provides some common enums and const variables.
Others
This section contains some predefined classes related to Dataset operations, tool functions, and some Typedefs.
Classes
Functions
Typedefs
Lite-CV
Lite-CV is a special library contrains image transform methods which are implemented without OpenCV.
Note that this library will only be compiled in lite mode of MindSpore with option -n lite_cv.
With this library, the size of lite package will be smaller compared to other libraries links to OpenCV.