GitLab

* update urls for kinetics dataset

* update urls for kinetics dataset

* remove errors

* update the changes and add test option to split

* added test to valid values for split arg

* change .txt to .csv for annotation url of k600
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

Co-authored-by: Federico Pozzi <federico.pozzi@argo.vision>

* port Pad to prototype transforms

* use literal

* replace most asserts with exceptions

* fix formating issues

* fix linting and remove more asserts

* fix regresion

* fix regresion

* fix bug

* apply ufmt

* apply ufmt

* fix tests

* fix format

* fix None check

* fix detection models tests

* non scriptable any

* add more checks for None values

* fix retinanet test

* fix retinanet test

* Update references/classification/transforms.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Update references/classification/transforms.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Update references/optical_flow/transforms.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Update references/optical_flow/transforms.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Update references/optical_flow/transforms.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* make value checks more pythonic:

* Update references/optical_flow/transforms.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* make value checks more pythonic

* make more checks pythonic

* fix bug

* appy ufmt

* fix tracing issues

* fib typos

* fix lint

* remove unecessary f-strings

* fix bug

* Update torchvision/datasets/mnist.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Update torchvision/datasets/mnist.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Update torchvision/ops/boxes.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Update torchvision/ops/poolers.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Update torchvision/utils.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* address PR comments

* Update torchvision/io/_video_opt.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Update torchvision/models/detection/generalized_rcnn.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Update torchvision/models/feature_extraction.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Update torchvision/models/optical_flow/raft.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* address PR comments

* addressing further pr comments

* fix bug

* remove unecessary else

* apply ufmt

* last pr comment

* replace RuntimeErrors
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Added functional affine_bounding_box op with tests

* Updated comments and added another test case

* Update _geometry.py

* Fixed device mismatch issue
Added a cude/cpu test
Reduced the number of test samples

* refactor: port RandomHorizontalFlip to prototype API (#5523)

* refactor: merge HorizontalFlip and RandomHorizontalFlip

Add unit tests for RandomHorizontalFlip

* test: RandomHorizontalFlip with p=0

* refactor: remove type annotations from tests

* refactor: improve tests

* Update test/test_prototype_transforms.py
Co-authored-by: Federico Pozzi <federico.pozzi@argo.vision>
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Moving `sequence_to_str` to `torchvision._utils`

* Fix linter

* Rename test_prototype_utils test to test_internal_utils

* port RandomZoomOut from detection references to prototype transforms

* copy by default

* move padding parsing to stable API

* merge zoom out kernels into transform

* lint

* fix filling if no padding was done

* resolve todo

Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* basic stanford cars structure added.

* added class in the init.

* how to decode the images

* fix typo in init

* works partially

* formatting

* formatting

* formatting

* formatting

* formatting

* minor changes

* minor changes

* issue resolved

* both datapipes are in sync

* checksum dict keys changed

* formatting

* "ufmt formatting"

* "ufmt formatting"

* formatting

* minor change

* minor change

* test added

* lint (end of line issue)

* lint (end of line issue)

* minor changes

* mock dataset formatting

* minor changes

* hopefully final

* formatting

* prototype test

* prototype test

* prototype test

* prototype test

* prototype test

* prototype test

* prototype test

* prototype test

* Update builtin_dataset_mocks.py

* Update stanford_cars.py

* Update torchvision/prototype/datasets/_builtin/stanford_cars.py
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* Update torchvision/prototype/datasets/_builtin/stanford_cars.py
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* Update torchvision/prototype/datasets/_builtin/stanford_cars.py
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* Update torchvision/prototype/datasets/_builtin/stanford_cars.py
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* formatting and cleaning

* formatting and cleaning

* Update torchvision/prototype/datasets/_builtin/stanford_cars.py
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* generate catefories script

* generate categories script added

* sigh

* sigh

* sigh

* minor changes

* linting
Co-authored-by: Philip Meier <github.pmeier@posteo.de>
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* support grayscale / RGB alpha conversions

* use _max_valu from stable

* remove extra copy for PIL conversion

* simplify test image generation for color spaces with alpha channel

* use common _max_value in tests

* replace dynamically created dicts with if/else

* make color space conversion more explicit

* make even more explicit

* simplify alpha image generation

* fix if / elif

* add error for unknown conversions

* rename RGBA to RGB_ALPHA

* cleanup

* GRAYSCALE to GRAY

* Removed _max_value method and added a dictionary

Related to https://github.com/pytorch/vision/issues/5502

* Addressed failing tests and restored _max_value method

* Added xfailing test to switch quicker

* Switch to if/else impl

* Refactor preset transforms

* Making presets public.

* Adding improved MobileNetV2 weights

* Fix eval sizes.

* Update accuracy with batch-size 1 run

Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* port FiveCrop and TenCrop to prototype API

* fix ten crop for pil

* Update torchvision/prototype/transforms/_geometry.py
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* simplify implementation

* minor cleanup
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* fix vanilla tensor image detection

* fix naming
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Fix accimage tests

* Adding workaround for accimage

* Refactoring

* restore channels
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Remove from models and references.

* Adding most tests and docs.

* Adding transforms tests.

* Remove unnecesary ipython notebook.

* Simplify tests.

* Addressing comments.

Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* simplify Feature implementation

* fix mypy

* add eurosat

* revert formatting

* port test and make style changes

* add eurosat to __init__

* fix pathlib error

* create dataset zipfile and revert pre commit changes

* remove unecessary variable in resources

* revert auto formatter changes and modify ufmt version

* revert change to contributing guide
Co-authored-by: Dbhasin1 <drishti_b@me.iitr.c.in>
Co-authored-by: Nicolas Hug <nicolashug@fb.com>

* add country211

* remove unused import

* map val to valid and use path comparator

* remove unused import

* resolve keyerror

* map split names in dataset mock
Co-authored-by: Dbhasin1 <drishti_b@me.iitr.c.in>
Co-authored-by: Nicolas Hug <nicolashug@fb.com>

* improve StrEnum

* use StrEnum for model weights

* fix test

* migrate StrEnum to main area

* Extend the EfficientNet class to support v1 and v2.

* Refactor config/builder methods and add prototype builders

* Refactoring weight info.

* Update dropouts based on TF config ref

* Update BN eps on TF base_config

* Use Conv2dNormActivation.

* Adding pre-trained weights for EfficientNetV2-s

* Add Medium and Large weights

* Update stats with single batch run.

* Add accuracies in the docs.

* Move VideoReader out of __init__

* Fix linter error

* fix grayscale to RGB for batches

* make unsupported types in auto augment a parameter

* make auto augment kwargs explicit

* add missing error message

* add support for specifying probabilites on RandomChoice

* remove TODO for deprecating p on random transforms

* streamline sample type checking

* address comments

* split image_size into height and width in auto augment
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* expand prototype functional scriptability tests

* remove obsolete skips

* add prototype AugMix transform

* cleanup

* refactor auto augment subclasses to only trnasform a single image

* address review comments