GitLab

* Add resnext101_64x4d model definition

* Add test for resnext101_64x4d

* Add resnext101_64x4d weight

* Update checkpoint to use EMA weigth

* Add quantization model signature for resnext101_64x4d

* Fix class name and update accuracy using 1 gpu and batch_size=1

* Apply ufmt

* Update the quantized weight and accuracy that we still keep the training log

* Add quantized expect file

* Update docs and fix acc1

* Add recipe for quantized to PR

* Update models.rst

* feat: add functional pad on segmentation mask

* test: add basic correctness test with random masks

* test: add all padding options

* fix: pr comments

* fix: tests

* refactor: reshape tensor in 4d, then pad
Co-authored-by: Federico Pozzi <federico.pozzi@argo.vision>

* added ciou loss

* "formatting with flake8 and ufmt"

* formatting with ufmt and flake8

* minor changes

* changes as per the suggestions

* added reference in torchvision/ops/__init__.py

* sample test

* tests formatted

* added description

* formatting

* edited tests

* changes in tests

* added tests for multiple boxes

* minor edits

* minor edit

* doc added

* minor edits

* Update test_ops.py

* formatting test file

* changes as per the suggestions

* formatting and adding some more tests

* bounding box added

* removed unnecessary comment

* added docstring

* added type annotations

* removed potential bug

* Update torchvision/ops/boxes.py
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Update torchvision/ops/boxes.py
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Update test/test_ops.py
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* fix test_data_loader on Windows and macOS

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

* Skip big model in test

* Let get_models_from_module func to read skipped_models from global directly instead of function param to reduce changes

* Also skip regnet_y_128gf

* Only skip test for test_classification_model and create toggle using env var

* Remove unnecessary comment

* Fix comparison of device to use str

* Add logic to test_classification_model directly

* Add kprcnn in autocast flaky list
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Add swin_t to slow list

* apply ufmt

* update expect for swin_t
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* add swin transformer

* Update swin_transformer.py

* Update swin_transformer.py

* fix lint

* fix lint

* refactor code

* add swin_transformer

* Update swin_transformer.py

* fix bug

* refactor code

* fix lint

* update init_weights

* move shift_window into attention

* refactor code

* fix bug

* Update swin_transformer.py

* Update swin_transformer.py

* fix lint

* add patch_merge

* fix bug

* Update swin_transformer.py

* Update swin_transformer.py

* Update swin_transformer.py

* refactor code

* Update swin_transformer.py

* refactor code

* fix lint

* refactor code

* add swin_tiny

* add swin_tiny.pkl

* fix lint

* Delete ModelTester.test_swin_tiny_expect.pkl

* add swin_tiny

* add

* add Optional to bias

* update init weights

* update init_weights and add no weight decay

* add no weight decay

* add set_weight_decay

* add set_weight_decay

* fix lint

* fix lint

* add lr_cos_min

* add other swin models

* Update torchvision/models/swin_transformer.py
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* refactor doc

* Update utils.py

* Update train.py

* Update train.py

* Update swin_transformer.py

* update model builder

* fix lint

* add

* Update torchvision/models/swin_transformer.py
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Update torchvision/models/swin_transformer.py
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* update other model

* simplify the model name just like ViT

* add lr_cos_min

* fix lint

* fix lint

* Update swin_transformer.py

* Update swin_transformer.py

* Update swin_transformer.py

* Delete ModelTester.test_swin_tiny_expect.pkl

* add swin_t

* refactor code

* Update train.py

* add swin_s

* ignore a error of mypy

* Update swin_transformer.py

* fix lint

* add swin_b

* add swin_l

* refactor code

* Update train.py

* move relative_position_bias to __init__

* fix formatting

* Revert "fix formatting"

This reverts commit 41faba232668f7ac4273a0cf632c0d0130c7ce9c.

* Revert "move relative_position_bias to __init__"

This reverts commit f0615440bf18617dc0e5dc4839bd5ed27e5ed010.

* refactor code

* Remove deprecated meta-data from `_COMMON_META`

* fix linter

* add pretrained weights for swin_t

* fix format

* apply ufmt

* add documentation

* update references README

* adding new style docs

* update pre-trained weights values

* remove other variants

* fix typo

* Remove expect for the variants not yet supported
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>
Co-authored-by: Joao Gomes <jdsgomes@fb.com>

* Fixed issue with padding on CI

* Disabled failing tests with color_jitter

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

* [proto] Added crop_bounding_box op

* Added `crop_segmentation_mask` op

* Fixed failed mypy

* Added tests for resized_crop_bounding_box

* Fixed code formatting

* Added resized_crop_segmentation_mask op

* Added tests

* [proto] Added crop_bounding_box op

* Added tests for resized_crop_bounding_box

* Fixed code formatting

* test: add functional vertical flip tests on segmentation mask

* refactor: improve test readibility

* Update test_prototype_transforms_functional.py
Co-authored-by: Federico Pozzi <federico.pozzi@argo.vision>
Co-authored-by: vfdev <vfdev.5@gmail.com>

* Restructuring metrics meta-data for detection, segmentation and optical flow.

* Renaming acc to pixel_acc for segmentation

* Restructure video meta-data.

* Restructure classification and quantization meta-data.

* Fix tests.

* Fix documentation

* Added `crop_segmentation_mask` op

* Fixed failed mypy

* Removing `task`, `architecture` and `quantization`

* Fix mypy

* Remove size field

* Remove unused import.

* Fix mypy

* Remove size from schema list.

* update todo

* Simplify with assert

* Adding min_size to all models.

* Update RAFT min size to 128

* Remove publication_year and interpolation meta

* Add type to _COMMON_META and _COMMON_SWAG_META to prevent error from mypy check

* Remove test to check interpolation and publication_year meta
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* add warning if font is not set

* added quotes

* added changes after review

* Apply suggestions from code review
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* escaped warning string

* Apply suggestions from code review
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* updated warning message in test

* refactored code

* Apply suggestions from code review
Co-authored-by: Philip Meier <github.pmeier@posteo.de>
Co-authored-by: Philip Meier <github.pmeier@posteo.de>
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Add test for giou_loss

* Use standard assert for integer comparison
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* Fix ufmt format and add log after assert
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* Add test for sigmoid_focal_loss

* Update test/test_ops.py

Improve code by using torch.testing.make_tensor
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* Update test/test_ops.py

Remove unnecessary assert
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* Update test/test_ops.py

Refactor code for generating inputs and targets
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* Improve focal_loss test code suggested on comment by Philip

* Use fuser2 to prevent fuser bug

* Combine function to generate input, dont set the fuser when device is cpu

* Add github issue for the fuser problem
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* [proto] Added crop_bounding_box op

* Removed "pass"

* Updated comment

* Removed unused args from signature

* refactor prototype datasets to inherit from IterDataPipe (#5448)

* refactor prototype datasets to inherit from IterDataPipe

* depend on new architecture

* fix missing file detection

* remove unrelated file

* reinstante decorator for mock registering

* options -> config

* remove passing of info to mock data functions

* refactor categories file generation

* fix imagenet

* fix prototype datasets data loading tests (#5711)

* reenable serialization test

* cleanup

* fix dill test

* trigger CI

* patch DILL_AVAILABLE for pickle serialization

* revert CI changes

* remove dill test and traversable test

* add data loader test

* parametrize over only_datapipe

* draw one sample rather than exhaust data loader

* cleanup

* trigger CI

* migrate VOC prototype dataset (#5743)

* migrate VOC prototype dataset

* cleanup

* revert unrelated mock data changes

* remove categories annotations

* move properties to constructor

* readd homepage

* migrate CIFAR prototype datasets (#5751)

* migrate country211 prototype dataset (#5753)

* migrate CLEVR prototype datsaet (#5752)

* migrate coco prototype (#5473)

* migrate coco prototype

* revert unrelated change

* add kwargs to super constructor call

* remove unneeded changes

* fix docstring position

* make kwargs explicit

* add dependencies to docstring

* fix missing dependency message

* Migrate PCAM prototype dataset (#5745)

* Port PCAM

* skip_integrity_check

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

* Address comments
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* Migrate DTD prototype dataset (#5757)

* Migrate DTD prototype dataset

* Docstring

* Apply suggestions from code review
Co-authored-by: Philip Meier <github.pmeier@posteo.de>
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* Migrate GTSRB prototype dataset (#5746)

* Migrate GTSRB prototype dataset

* ufmt

* Address comments

* Apparently mypy doesn't know that __len__ returns ints. How cute.

* why is the CI not triggered??

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

* migrate CelebA prototype dataset (#5750)

* migrate CelebA prototype dataset

* inline split_id

* Migrate Food101 prototype dataset (#5758)

* Migrate Food101 dataset

* Added length

* Update torchvision/prototype/datasets/_builtin/food101.py
Co-authored-by: Philip Meier <github.pmeier@posteo.de>
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* Migrate Fer2013 prototype dataset (#5759)

* Migrate Fer2013 prototype dataset

* Update torchvision/prototype/datasets/_builtin/fer2013.py
Co-authored-by: Philip Meier <github.pmeier@posteo.de>
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* Migrate EuroSAT prototype dataset (#5760)

* Migrate Semeion prototype dataset (#5761)

* migrate caltech prototype datasets (#5749)

* migrate caltech prototype datasets

* resolve third party dependencies

* Migrate Oxford Pets prototype dataset (#5764)

* Migrate Oxford Pets prototype dataset

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

* migrate mnist prototype datasets (#5480)

* migrate MNIST prototype datasets

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

* Migrate Stanford Cars prototype dataset (#5767)

* Migrate Stanford Cars prototype dataset

* Address comments

* fix category file generation (#5770)

* fix category file generation

* revert unrelated change

* revert unrelated change

* migrate cub200 prototype dataset (#5765)

* migrate cub200 prototype dataset

* address comments

* fix category-file-generation

* Migrate USPS prototype dataset (#5771)

* migrate SBD prototype dataset (#5772)

* migrate SBD prototype dataset

* reuse categories

* Migrate SVHN prototype dataset (#5769)

* add test to enforce __len__ is working on prototype datasets (#5742)

* reactivate special dataset tests

* add missing annotation

* Cleanup prototype dataset implementation (#5774)

* Remove Dataset2 class

* Move read_categories_file out of DatasetInfo

* Remove FrozenBunch and FrozenMapping

* Remove test_prototype_datasets_api.py and move missing dep test somewhere else

* ufmt

* Let read_categories_file accept names instead of paths

* Mypy

* flake8

* fix category file reading
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* update prototype dataset README (#5777)

* update prototype dataset README

* fix header level

* Apply suggestions from code review
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Use frozen BN only if pre-trained.

* Add LSJ and ability to from scratch training.

* Fixing formatter

* Adding `--opt` and `--norm-weight-decay` support in Detection.

* Fix error message

* Make ScaleJitter proportional.

* Adding more norm layers in split_normalization_params.

* Add FixedSizeCrop

* Temporary fix for fill values on PIL

* Fix the bug on fill.

* Add RandomShortestSize.

* Skip resize when an augmentation method is used.

* multiscale in [480, 800]

* Add missing star

* Add new RetinaNet variant.

* Add tests.

* Update expected file for old retina

* Fixing tests

* Add FrozenBN to retinav2

* Fix network initialization issues

* Adding BN support in MaskRCNNHeads and FPN

* Adding support of FasterRCNNHeads

* Introduce norm_layers in backbone utils.

* Bigger RPN head + 2x rcnn v2 models.

* Adding gIoU support to retinanet

* Fix assert

* Add back nesterov momentum

* Rename and extend `FastRCNNConvFCHead` to support arbitrary FCs

* Fix linter

* Add vit_b_16_swag

* Better handling idiom for image_size, edit test_extended_model to handle case where number of param differ from default due to different image size input

* Update the accuracy to the experiment result on torchvision model

* Fix typo missing underscore

* raise exception instead of torch._assert, add back publication year (accidentally deleted)

* Add license information on meta and readme

* Improve wording and fix typo for pretrained model license in readme

* Add vit_l_16 weight

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

* Update the accuracy meta on vit_l_16_swag model to result from our experiment

* Add vit_h_14_swag model

* Add accuracy from experiments

* Add to vit_h_16 model to hubconf.py

* Add docs and expected pkl file for test

* Remove legacy compatibility for ViT_H_14 model
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Test vit_h_14 with smaller image_size to speedup the test
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* port image type conversion transforms to prototype API

* implement proposal for image type conversion

* add deprecation warnings

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

* Added functional affine_bounding_box op with tests

* Updated comments and added another test case

* Update _geometry.py

* Added affine_segmentation_mask with tests

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

* Added test_correctness_affine_segmentation_mask_on_fixed_input

* Updates according to the review

* Replaced [None, ...] by [None, :]

* Adressed review comments

* Fixed formatting and more updates according to the review

* Fixed bad merge

* WIP

* Fixed tests

* Updated warning message

* [FEAT] Start implementing Food101 using the new datasets API. WIP.

* [FEAT] Generate Food101 categories and start the test mock.

* [FEAT] food101 dataset code seems to work now.

* [TEST] food101 mock update.

* [FIX] Some fixes thanks to running food101 tests.

* [FIX] Fix mypy checks for the food101 file.

* [FIX] Remove unused numpy.

* [FIX] Some changes thanks to code review.

* [ENH] More idomatic dataset code thanks to code review.

* [FIX] Remove unused cast.

* [ENH] Set decompress and extract to True for some performance gains.

* [FEAT] Use the preprocess=decompress keyword.

* [ENH] Use the train and test.txt file instead of the .json variants and simplify code + update mock data.

* [ENH] Better food101 mock data generation.

* [FIX] Remove a useless print.
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* Fix shape mismatch error

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

* Add vit_b_16_swag

* Better handling idiom for image_size, edit test_extended_model to handle case where number of param differ from default due to different image size input

* Update the accuracy to the experiment result on torchvision model

* Fix typo missing underscore

* raise exception instead of torch._assert, add back publication year (accidentally deleted)

* Add license information on meta and readme

* Improve wording and fix typo for pretrained model license in readme

* Add vit_l_16 weight

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

* Update the accuracy meta on vit_l_16_swag model to result from our experiment
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Detection recipe enhancements

* Add back nesterov momentum

* add test to enforce infinite buffer size for all applicable datapipes

* use utility function to extract datapipes

* check for buffer_size attr rather than type

* simplify

* reverting some recently introduced exceptions

* Update torchvision/ops/poolers.py
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* address PR comments

* replace one more assert with torch._assert:

* address PR comments

* make type checker happy

* Fix bug

* fix bug

* fix for wrong asserts

* attempt to make tests pass

* Fix test_ops tests

* Fix expected exception in tests

* fix typo

* fix tests and format

* fix flake8

* remove one last exception

* fix error

* remove unused immport

* replace fake returns by else
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* enforce shuffling before sharding

* revert test changes and add comment

* fix PCAM prototype dataset

* update Zip and Tar archive loader datapipes

* only fail on warnings from the pytorch ecosystem

* Revert "only fail on warnings from the pytorch ecosystem"

This reverts commit 2bf3aa6f2d875a4055f7f3ed0b468316fc60d4f4.

* Fixed rotate with expand inconsistency between torch vs PIL on odd-sized images

* Update functional_tensor.py

* added usps dataset

* fixed type issues

* fix mobilnet norm layer test (#5643)

* xfail mobilnet norm layer test

* fix test

* More robust check in tests for 16 bits images (#5652)

* Prefer nvidia channel for conda builds (#5648)

To mitigate missing `libcupti.so` dependency

* fix torchdata CI installation (#5657)

* update urls for kinetics dataset (#5578)

* 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>

* Port Multi-weight support from prototype to main (#5618)

* Moving basefiles outside of prototype and porting Alexnet, ConvNext, Densenet and EfficientNet.

* Porting googlenet

* Porting inception

* Porting mnasnet

* Porting mobilenetv2

* Porting mobilenetv3

* Porting regnet

* Porting resnet

* Porting shufflenetv2

* Porting squeezenet

* Porting vgg

* Porting vit

* Fix docstrings

* Fixing imports

* Adding missing import

* Fix mobilenet imports

* Fix tests

* Fix prototype tests

* Exclude get_weight from models on test

* Fix init files

* Porting googlenet

* Porting inception

* porting mobilenetv2

* porting mobilenetv3

* porting resnet

* porting shufflenetv2

* Fix test and linter

* Fixing docs.

* Porting Detection models (#5617)

* fix inits

* fix docs

* Port faster_rcnn

* Port fcos

* Port keypoint_rcnn

* Port mask_rcnn

* Port retinanet

* Port ssd

* Port ssdlite

* Fix linter

* Fixing tests

* Fixing tests

* Fixing vgg test

* Porting Optical Flow, Segmentation, Video models (#5619)

* Porting raft

* Porting video resnet

* Porting deeplabv3

* Porting fcn and lraspp

* Fixing the tests and linter

* Porting docs, examples, tutorials and galleries (#5620)

* Fix examples, tutorials and gallery

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

* Fix import

* Revert hardcoded normalization

* fix uncommitted changes

* Fix bug

* Fix more bugs

* Making resize optional for segmentation

* Fixing preset

* Fix mypy

* Fixing documentation strings

* Fix flake8

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

* Resolve conflict

* Porting model tests (#5622)

* Porting tests

* Remove unnecessary variable

* Fix linter

* Move prototype to extended tests

* Fix download models job

* Update CI on Multiweight branch to use the new weight download approach (#5628)

* port Pad to prototype transforms (#5621)

* port Pad to prototype transforms

* use literal

* Bump up LibTorchvision version number for Podspec to release Cocoapods (#5624)
Co-authored-by: Anton Thomma <anton@pri.co.nz>
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* pre-download model weights in CI docs build (#5625)

* pre-download model weights in CI docs build

* move changes into template

* change docs image

* Regenerated config.yml
Co-authored-by: Philip Meier <github.pmeier@posteo.de>
Co-authored-by: Anton Thomma <11010310+thommaa@users.noreply.github.com>
Co-authored-by: Anton Thomma <anton@pri.co.nz>

* Porting reference scripts and updating presets (#5629)

* Making _preset.py classes

* Remove support of targets on presets.

* Rewriting the video preset

* Adding tests to check that the bundled transforms are JIT scriptable

* Rename all presets from *Eval to *Inference

* Minor refactoring

* Remove --prototype and --pretrained from reference scripts

* remove  pretained_backbone refs

* Corrections and simplifications

* Fixing bug

* Fixing linter

* Fix flake8

* restore documentation example

* minor fixes

* fix optical flow missing param

* Fixing commands

* Adding weights_backbone support in detection and segmentation

* Updating the commands for InceptionV3

* Setting `weights_backbone` to its fully BC value (#5653)

* Replace default `weights_backbone=None` with its BC values.

* Fixing tests

* Fix linter

* Update docs.

* Update preprocessing on reference scripts.

* Change qat/ptq to their full values.

* Refactoring preprocessing

* Fix video preset

* No initialization on VGG if pretrained

* Fix warning messages for backbone utils.

* Adding star to all preset constructors.

* Fix mypy.
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>
Co-authored-by: Philip Meier <github.pmeier@posteo.de>
Co-authored-by: Anton Thomma <11010310+thommaa@users.noreply.github.com>
Co-authored-by: Anton Thomma <anton@pri.co.nz>

* Apply suggestions from code review
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* use decompressor for extracting bz2

* Apply suggestions from code review
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* Apply suggestions from code review
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* fixed lint fails

* added tests for USPS

* check image shape

* fix tests

* check shape on image directly

* Apply suggestions from code review
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* removed test and comments

* Update test/test_prototype_builtin_datasets.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>
Co-authored-by: Philip Meier <github.pmeier@posteo.de>
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>
Co-authored-by: Nikita Shulga <nshulga@fb.com>
Co-authored-by: Sahil Goyal <sahilgoyal6801@gmail.com>
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>
Co-authored-by: Anton Thomma <11010310+thommaa@users.noreply.github.com>
Co-authored-by: Anton Thomma <anton@pri.co.nz>

* fix HttpResource.resolve() with preprocess set

* fix README

* add safe guard for invalid str inputs

* Added functional affine_bounding_box op with tests

* Updated comments and added another test case

* Update _geometry.py

* Added affine_segmentation_mask with tests

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

* Added test_correctness_affine_segmentation_mask_on_fixed_input

* Updates according to the review

* Replaced [None, ...] by [None, :]

* Adressed review comments

* Fixed formatting and more updates according to the review

* Fixed bad merge