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momet -> moment
Signed-off-by: Hollow Man <hollowman@hollowman.ml>
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

Adds classification data and links to the class libraries.
Co-authored-by: Brian Johnson <brianjo@fb.com>

* Video reader now returns dicts

* docs update

* Minor improvements
Co-authored-by: Bruno Korbar <bjuncek@Frazz.local>
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

* Add rough implementation of RetinaNet.

* Move AnchorGenerator to a seperate file.

* Move box similarity to Matcher.

* Expose extra blocks in FPN.

* Expose retinanet in __init__.py.

* Use P6 and P7 in FPN for retinanet.

* Use parameters from retinanet for anchor generation.

* General fixes for retinanet model.

* Implement loss for retinanet heads.

* Output reshaped outputs from retinanet heads.

* Add postprocessing of detections.

* Small fixes.

* Remove unused argument.

* Remove python2 invocation of super.

* Add postprocessing for additional outputs.

* Add missing import of ImageList.

* Remove redundant import.

* Simplify class correction.

* Fix pylint warnings.

* Remove the label adjustment for background class.

* Set default score threshold to 0.05.

* Add weight initialization for regression layer.

* Allow training on images with no annotations.

* Use smooth_l1_loss with beta value.

* Add more typehints for TorchScript conversions.

* Fix linting issues.

* Fix type hints in postprocess_detections.

* Fix type annotations for TorchScript.

* Fix inconsistency with matched_idxs.

* Add retinanet model test.

* Add missing JIT annotations.

* Remove redundant model construction

Make tests pass

* Fix bugs during training on newer PyTorch and unused params in DDP

Needs cleanup and to add back support for images with no annotations

* Cleanup resnet_fpn_backbone

* Use L1 loss for regression

Gives 1mAP improvement over smooth l1

* Disable support for images with no annotations

Need to fix distributed first

* Fix retinanet tests

Need to deduplicate those box checks

* Fix Lint

* Add pretrained model

* Add training info for retinanet
Co-authored-by: Hans Gaiser <hansg91@gmail.com>
Co-authored-by: Hans Gaiser <hans.gaiser@robovalley.com>
Co-authored-by: Hans Gaiser <hans.gaiser@robohouse.com>

* Minor improvements to VideoReader

* update jupyter notebook with new naming
Co-authored-by: Bruno Korbar <bjuncek@gmail.com>

* initial API documentation attempt

* test the docs

* initial commit

* updating test to match the registration

* adding the warning on unsucessful import

* Try to do conditional import

* Simple fix?

* clearing up docs

* docstring commit

* Adding types in arguments
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

* reverting warning commit

* addressing Francisco's comments

* Apply suggestions from code review
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

* Revert "reverting warning commit"

This reverts commit bd1a3dd4f3b97709ab59c744962e11174757f8ce.

* Revert "adding the warning on unsucessful import"

This reverts commit afef7df9eaa73bf80246e6d9114cb4c30b16f0ce.

* remove warnings import
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

* [WIP] Added scriptable transforms python example

* Replaced script file with jupyter notebook

* Updated readme

* Updates according to review
+ updated docstrings

* Updated notebook and docstring according to the review

* torch script -> torchscript

* Added GaussianBlur transform

* fixed linting

* supports fixed radius for kernel

* [WIP] New API for gaussian_blur

* Gaussian blur with kernelsize and sigma API

* Fixed implementation and updated tests

* Added large input case and refactored gt into a file

* Updated docs

* fix kernel dimesnions order while creating kernel

* added tests for exception handling of gaussian blur

* fix linting, bug in tests

* Fixed failing tests, refactored code and other minor fixes
Co-authored-by: vfdev-5 <vfdev.5@gmail.com>

* Expose image io functions in docs

* Expose image funcs in module

* Update docstring

* Update docstrings for all functions

* Update section header

- Fixed incorrect docs layout and a warning

* adds boxes conversion

* adds documentation

* adds xywh tests

* fixes small typo

* adds tests

* Remove sphinx theme

* corrects assertions

* cleans code as per suggestion
Signed-off-by: Aditya Oke <okeaditya315@gmail.com>

* reverts assertion

* fixes to assertEqual

* fixes inplace operations

* Adds docstrings

* added documentation

* changes tests

* moves code to box_convert

* adds more tests

* Apply suggestions from code review

Let's leave those changes to a separate PR

* fixes documentation
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

* tries adding genaralized_iou

* fixes linting

* Adds docs for giou, iou and box area

* fixes lint

* removes docs to fixup in other PR

* linter fix

* Cleans comments

* Adds tests for box area, iou and giou

* typo fix for testCase

* fixes typo

* fixes box area test

* fixes implementation

* updates tests to tolerance

* [WIP] All transforms are now derived from torch.nn.Module
- Compose, RandomApply, Normalize can be jit scripted

* Fixed flake8

* Updated code and docs
- added getattr to Lambda and tests
- updated code and docs of Compose
- added failing test with append/extend on Composed.transforms

* Fixed flake8

* Updated code, tests and docs

* Adds docs and fixes improts for ops and io

* reverts io and init for images

* [WIP] Added tests on batch of tensors

* Updated tests on batch of images

* All functional transforms can work with (..., C, H, W) format

* Added transforms tests on batch tensors

* Added batch tests for five/ten crop
- updated docs

* initial draft

* [dirty] progress

* remove inheritance from ImageFolder

* add tests

* lint

* fix type hints

* align getitem with other datasets

* remove unused import

* add docstring

* guard existing image folders from overwrite

* add missing entry in docstring

* make fixpath more legible

* add Places365 to docs

Add document entry for datasets.Omniglot

* Update docs

* Update docs/source/ops.rst
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

* Add Deformable Convolution in Doc

* Add PSRoIPool and PSRoIAlign in Doc

* guess documentation location

* document mean/std origins

* fix artifact

* update for clarity

* fix typo

* Update requirements.txt

* Update conf.py

* Update conf.py

* almost working...

* respond to comments

* add empty tensor op, handle different output types in generalized rcnn

* clean ups

* address comments

* more changes

* it's working!

* torchscript bugs

* add script/ eager test

* eval script model

* fix flake

* division import

* py2 compat

* update test, fix arange bug

* import division statement

* fix linter

* fixes

* changes needed for JIT master

* cleanups

* remove imagelist_to

* requested changes

* Make FPN backwards-compatible and torchscript compatible

We remove support for feature channels=0, but support for it was already a bit limited

* Fix ONNX regression

* Add docs for video models

* Fix docstrings for resnet and vgg

* Expose docs for io and ops package

Had do modify the docstrings to use Napoleon NumPy style, because Napoleon Google Style doesn't support multiple return arguments

* Add video section

* Add docs to UCF101 and HMDB51 datasets

* Remove extra line

* Lint

Also add docs

* add wide resnet

* add docstring for wide resnet

* update WRN-50-2 model

* add docs

* extend WRN docstring

* use pytorch storage for WRN

* fix rebase

* fix typo in docs

* add erase function

* add Random Erasing

* Update transforms.py

* Update transforms.py

* add test for random erasing

* Update test_transforms.py

* fix flake8

* Update test_transforms.py

* Update functional.py

* Update test_transforms.py

* fix bug for per-pixel erasing

* Update transforms.py

* specific for coordinate (x, y)

* add raise TypeError for img

* Update transforms.py

* Update transforms.rst

* Add initial mnasnet impl

* Remove all type hints, comply with PyTorch overall style

* Expose models

* Remove avgpool from features() and add separately

* Fix python3-only stuff, replace subclasses with functions

* fix __all__

* Fix typo

* Remove conditional dropout

* Make dropout functional

* Addressing @fmassa's feedback, round 1

* Replaced adaptive avgpool with mean on H and W to prevent collapsing the batch dimension

* Partially address feedback

* YAPF

* Removed redundant class vars

* Update urls to releases

* Add information to models.rst

* Replace init with kaiming_normal_ in fan-out mode

* Use load_state_dict_from_url

Values from random.random() are always in the range [0.0, 1.0), so the statement `random.random() > 5` will never be true.

* Added general reader for sn3 tensors in "pascalvincent" format

* Added class QMNIST into mnist.py

* QMNIST dataset: make some pt files smaller

* Change request from fmassa.

* read_sn3_pascalvincent_tensor: cse

* read_sn3_pascalvincent_tensor: check file size (when strict!=False)

* Fix lint

* More lint

* Add documentation and expose QMNIST to dataset namespace