mindspore.dataset.transforms

This module is to support common augmentations. C_transforms is a high performance augmentation module which is developed by C++. Py_transforms provides an optional implementation which is developed by Python & NumPy.

Common imported modules in corresponding API examples are as follows:

import mindspore.dataset as ds
import mindspore.dataset.vision.c_transforms as c_vision
import mindspore.dataset.vision.py_transforms as py_vision
from mindspore.dataset.transforms import c_transforms
from mindspore.dataset.transforms import py_transforms

Descriptions of common data processing terms are as follows:

TensorOperation, the base class of all data processing operations implemented in C++.
PyTensorOperation, the base class of all data processing operations implemented in Python.

mindspore.dataset.transforms.c_transforms

`mindspore.dataset.transforms.c_transforms.Compose`	Compose a list of transforms into a single transform.
`mindspore.dataset.transforms.c_transforms.Concatenate`	Tensor operation that concatenates all columns into a single tensor.
`mindspore.dataset.transforms.c_transforms.Duplicate`	Duplicate the input tensor to output, only support transform one column each time.
`mindspore.dataset.transforms.c_transforms.Fill`	Tensor operation to fill all elements in the tensor with the specified value.
`mindspore.dataset.transforms.c_transforms.Mask`	Mask content of the input tensor with the given predicate.
`mindspore.dataset.transforms.c_transforms.OneHot`	Tensor operation to apply one hot encoding.
`mindspore.dataset.transforms.c_transforms.PadEnd`	Pad input tensor according to pad_shape, input tensor needs to have same rank.
`mindspore.dataset.transforms.c_transforms.RandomApply`	Randomly perform a series of transforms with a given probability.
`mindspore.dataset.transforms.c_transforms.RandomChoice`	Randomly select one transform from a list of transforms to perform operation.
`mindspore.dataset.transforms.c_transforms.Relational`	Relationship operator.
`mindspore.dataset.transforms.c_transforms.Slice`	Slice operation to extract a tensor out using the given n slices.
`mindspore.dataset.transforms.c_transforms.TypeCast`	Tensor operation to cast to a given MindSpore data type.
`mindspore.dataset.transforms.c_transforms.Unique`	Perform the unique operation on the input tensor, only support transform one column each time.

mindspore.dataset.transforms.py_transforms

`mindspore.dataset.transforms.py_transforms.Compose`	Compose a list of transforms.
`mindspore.dataset.transforms.py_transforms.OneHotOp`	Apply one hot encoding transformation to the input label, make label be more smoothing and continuous.
`mindspore.dataset.transforms.py_transforms.RandomApply`	Randomly perform a series of transforms with a given probability.
`mindspore.dataset.transforms.py_transforms.RandomChoice`	Randomly select one transform from a series of transforms and applies that on the image.
`mindspore.dataset.transforms.py_transforms.RandomOrder`	Perform a series of transforms to the input PIL image in a random order.