mindspore.dataset.transforms
This module is to support common augmentations. C_transforms is a high performance image augmentation module which is developed with C++ OpenCV. Py_transforms provide more kinds of image augmentations which are developed with Python PIL.
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
mindspore.dataset.transforms.c_transforms
Compose a list of transforms into a single transform. |
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Tensor operation that concatenates all columns into a single tensor. |
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Duplicate the input tensor to output, only support transform one column each time. |
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Tensor operation to fill all elements in the tensor with the specified value. |
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Mask content of the input tensor with the given predicate. |
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Tensor operation to apply one hot encoding. |
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Pad input tensor according to pad_shape, input tensor needs to have same rank. |
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Randomly perform a series of transforms with a given probability. |
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Randomly select one transform from a list of transforms to perform operation. |
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Relationship operator. |
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Slice operation to extract a tensor out using the given n slices. |
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Tensor operation to cast to a given MindSpore data type. |
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Perform the unique operation on the input tensor, only support transform one column each time. |
mindspore.dataset.transforms.py_transforms
Compose a list of transforms. |
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Apply one hot encoding transformation to the input label, make label be more smoothing and continuous. |
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Randomly perform a series of transforms with a given probability. |
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Randomly select one transform from a series of transforms and applies that on the image. |
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Perform a series of transforms to the input PIL image in a random order. |