36 lines
826 B
ReStructuredText
36 lines
826 B
ReStructuredText
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.. role:: hidden
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:class: hidden-section
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Batch Augmentation
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===================================
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Batch augmentation is the augmentation which involve multiple samples, such as Mixup and CutMix.
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In MMClassification, these batch augmentation is used as a part of :ref:`classifiers`. A typical usage is as below:
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.. code-block:: python
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model = dict(
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backbone = ...,
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neck = ...,
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head = ...,
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train_cfg=dict(augments=[
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dict(type='BatchMixup', alpha=0.8, prob=0.5, num_classes=num_classes),
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dict(type='BatchCutMix', alpha=1.0, prob=0.5, num_classes=num_classes),
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]))
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)
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.. currentmodule:: mmcls.models.utils.augment
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Mixup
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-----
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.. autoclass:: BatchMixupLayer
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CutMix
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------
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.. autoclass:: BatchCutMixLayer
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ResizeMix
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---------
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.. autoclass:: BatchResizeMixLayer
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