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