104 lines
1.8 KiB
ReStructuredText
104 lines
1.8 KiB
ReStructuredText
.. _ops:
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Operators
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=========
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.. currentmodule:: torchvision.ops
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:mod:`torchvision.ops` implements operators, losses and layers that are specific for Computer Vision.
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.. note::
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All operators have native support for TorchScript.
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Detection and Segmentation Operators
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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The below operators perform pre-processing as well as post-processing required in object detection and segmentation models.
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.. autosummary::
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:toctree: generated/
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:template: function.rst
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batched_nms
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masks_to_boxes
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nms
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roi_align
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roi_pool
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ps_roi_align
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ps_roi_pool
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.. autosummary::
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:toctree: generated/
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:template: class.rst
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FeaturePyramidNetwork
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MultiScaleRoIAlign
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RoIAlign
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RoIPool
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PSRoIAlign
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PSRoIPool
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Box Operators
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~~~~~~~~~~~~~
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These utility functions perform various operations on bounding boxes.
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.. autosummary::
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:toctree: generated/
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:template: function.rst
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box_area
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box_convert
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box_iou
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clip_boxes_to_image
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complete_box_iou
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distance_box_iou
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generalized_box_iou
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remove_small_boxes
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Losses
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~~~~~~
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The following vision-specific loss functions are implemented:
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.. autosummary::
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:toctree: generated/
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:template: function.rst
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complete_box_iou_loss
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distance_box_iou_loss
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generalized_box_iou_loss
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sigmoid_focal_loss
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Layers
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~~~~~~
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TorchVision provides commonly used building blocks as layers:
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.. autosummary::
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:toctree: generated/
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:template: class.rst
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Conv2dNormActivation
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Conv3dNormActivation
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DeformConv2d
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DropBlock2d
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DropBlock3d
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FrozenBatchNorm2d
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MLP
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Permute
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SqueezeExcitation
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StochasticDepth
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.. autosummary::
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:toctree: generated/
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:template: function.rst
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deform_conv2d
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drop_block2d
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drop_block3d
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stochastic_depth
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