GitLab

* added SceneFLow variant datasets

* Changed split name to variant name

* removed trailing commented code line

* Added Sintel Stereo dataset

* small refactor in tests

* Fixed doc formatting.

* candidate fix for FileNotFound on windows test

* Adressing comments

* Added Sintel Stereo dataset

* small refactor in tests

* Fixed doc formatting.

* candidate fix for FileNotFound on windows test

* Adressing comments

* rebased on main

* lint fix

* port `RandomShortestSize` from detection references to prototype transforms

* mypy

* add test

* fix TenCrop

* use dispatchers for RandomPhotometricDistort

* add convert_color_space dispatcher and use it in conversion transforms

* fix convert_color_space naming scheme

* add to_color_space method to Image feature

* remove TODO from BoundingBox.to_format()

* fix test

* fix imports

* fix passthrough

* remove apply_recursively in favor of pytree

* refactor BatchMultiCrop

* port ScaleJitter from detection reference to prototype transforms

* add test

* use MagicMock as sentinel

* disable download test for Places365

* add xfail test for broken download servers

* add more comments

* mark SBU download as failing
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* [proto] Another attemp to rewrite RandomCrop

* Fixed implementation issue and updated tests

* [proto] Compose keeps BC

* Compose -> Compose(Transform)

* Fix typing jit issue on RoIPool and RoIAlign

* Fix nit.

* Address code review comments.

* init submit

* fix typo

* support ufmt and mypy

* fix 2 unittest errors

* fix ufmt issue

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

* unify codes

* fix meshgrid indexing

* fix a bug

* fix type check

* add type_annotation

* add slow model

* fix device issue

* fix ufmt issue

* add expect pickle file

* fix jit script issue

* fix type check

* keep consistent argument order

* add support for pretrained_window_size

* avoid code duplication

* a better code reuse

* update window_size argument

* make permute and flatten operations modular

* add PatchMergingV2

* modify expect.pkl

* use None as default argument value

* fix type check

* fix indent

* fix window_size (temporarily)

* remove "v2_" related prefix and add v2 builder

* remove v2 builder

* keep default value consistent with official repo

* deprecate dropout

* deprecate pretrained_window_size

* fix dynamic padding edge case

* remove unused imports

* remove doc modification

* Revert "deprecate dropout"

This reverts commit 8a13f932815ae25655c07430d52929f86b1ca479.

* Revert "fix dynamic padding edge case"

This reverts commit 1c7579cb1bd7bf2f0f94907f39bee6ed707a97a8.

* remove unused kwargs

* add downsample docs

* revert block default value

* revert argument order change

* explicitly specify start_dim

* add small and base variants

* add expect files and slow_models

* Add model weights and documentation for swin v2

* fix lint

* fix end of files line
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>
Co-authored-by: Joao Gomes <jdsgomes@fb.com>

* Extending to support MViTv2

* Fix docs, mypy and linter

* Refactor the relative positional code.

* Code refactoring.

* Rename vars.

* Update docs.

* Replace assert with exception.

* Updat docs.

* Minor refactoring.

* Remove the square input limitation.

* Moving methods around.

* Modify the shortcut in the attention layer.

* Add ported weights.

* Introduce a `residual_cls` config on the attention layer.

* Make the patch_embed kernel/padding/stride configurable.

* Apply changes from code-review.

* Remove stale todo.

* [proto] Fixed issue with `F.pad` from RandomZoomOut

* Fixed failing tests

* Fixed wrong type hint

* Fixed fill=None in pad_image_pil

* Try to support fill=None in functional

* Code formatting

* [proto] Fix for handling Numpy arrays by Transform

* transformed_types -> _transformed_types

* Added Image.normalize and fixed Normalize._transform

* Updated code for normalize, removed Image.normalize

* Make test precision stricter for Classification

* Update classification threshold.

* Update quantized classification threshold.

* added SceneFLow variant datasets

* Changed split name to variant name

* removed trailing commented code line

* Broken down PR(#6269). Added an additional dataset

* Removed some types. Store None instead of "". Merged test util functions.

* minor mypy fixes. minor doc fixes

* reformated docstring

* Added additional line-skips

* Fix bug in calculating cIoU for unequal sizes

* Remove comment

* what the epsilon?

* Fixing DIoU

* Optimization by Francisco.

* Fix the expected values on CompleteBoxIoU

* Apply suggestions from code review
Co-authored-by: Abhijit Deo <72816663+abhi-glitchhg@users.noreply.github.com>

* Adding cartesian product test.

* remove static
Co-authored-by: Vasilis Vryniotis <vvryniotis@fb.com>
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>
Co-authored-by: Abhijit Deo <72816663+abhi-glitchhg@users.noreply.github.com>

* cleaning up box decoding

* minor nits

* cleanup for box encoding also addded.

* Model registration mechanism.

* Add overwrite options to the dataset prototype registration mechanism.

* Adding example models.

* Fix module filtering

* Fix linter

* Fix docs

* Make name optional if same as model builder

* Apply updates from code-review.

* fix minor bug

* Adding getter for model weight enum

* Support both strings and callables on get_model_weight.

* linter fixes

* Fixing mypy.

* Renaming `get_model_weight` to `get_model_weights`

* Registering all classification models.

* Registering all video models.

* Registering all detection models.

* Registering all optical flow models.

* Fixing mypy.

* Registering all segmentation models.

* Registering all quantization models.

* Fixing linter

* Registering all prototype depth perception models.

* Adding tests and updating existing tests.

* Fix linters

* Fix tests.

* Add beta annotation on docs.

* Fix tests.

* Apply changes from code-review.

* Adding documentation.

* Fix docs.

* [proto] Added few transforms tests, part 1 (#6262)

* Added supported/unsupported data checks in the tests for cutmix/mixup

* Added RandomRotation, RandomAffine transforms tests

* Added tests for RandomZoomOut, Pad

* Update test_prototype_transforms.py

* Added RandomCrop transform and tests (#6271)

* [proto] Added GaussianBlur transform and tests (#6273)

* Added GaussianBlur transform and tests

* Fixing code format

* Copied correctness test

* [proto] Added random color transforms and tests (#6275)

* Added random color transforms and tests

* Disable smoke test for RandomSolarize, RandomAdjustSharpness

* Added RandomPerspective and tests (#6284)

- replaced real image creation by mocks for other tests

* Added more functional tests (#6285)

* [proto] Added elastic transform and tests (#6295)

* WIP [proto] Added functional elastic transform with tests

* Added more functional tests

* WIP on elastic op

* Added elastic transform and tests

* Added tests

* Added tests for ElasticTransform

* Try to format code as in https://github.com/pytorch/vision/pull/5106



* Fixed bug in affine get_params test

* Implemented RandomErase on PIL input as fallback to tensors (#6309)

Added tests

* Added image_size computation for BoundingBox.rotate if expand (#6319)

* Added image_size computation for BoundingBox.rotate if expand

* Added tests

* Added erase_image_pil and eager/jit erase_image_tensor test (#6320)

* Updates according to the review
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Refactor tests

* Remove tol, fix comments

* Add tolerance only where necessary

* Add tolerance only where necessary

* Add tolerance only where necessary

* Refactor to adapt suggestions

* Refactor and add nits

* Refactor box area

* Refactor to one file

* Adapt almost all except area

* final update

* Tighten for jit

* Refactor slightly

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

* [proto] Added missing decorator for center_crop_segmentation_mask tests

* Added center_crop_image_tensor

* upgrade usort to

* Also update black

* Actually use 1.0.2

* Apply pre-commit
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Another attempt to add transforms

* Fixed padding type hint

* Fixed fill arg for pad and rotate, affine

* code formatting and type hints for affine transformation

* Fixed flake8

* Updated tests to save and load transforms

* Fixed code formatting issue

* Fixed jit loading issue

* Restored fill default value to None
Updated code according to the review

* Added tests for rotation, affine and zoom transforms

* Put back commented code

* Random erase bypass boxes and masks
Go back with if-return/elif-return/else-return

* Fixed acceptable and non-acceptable types for Cutmix/Mixup

* Updated conditions for _BaseMixupCutmix

* Updated tests to save and load transforms

* Fixed code formatting issue

* Added mid-level ops and feature-based ops

* Fixing deadlock in dataloader with circular imports

* Added non-scalar fill support workaround for pad

* Removed comments

* int/float support for fill in pad op

* Updated type hints and removed bypass option from mid-level methods

* Minor nit fixes

* Adding MViT v2 architecture (#6105)

* Adding mvitv2 architecture

* Fixing memory issues on tests and minor refactorings.

* Adding input validation

* Adding docs and minor refactoring

* Add `min_temporal_size` in the supported meta-data.

* Switch Tuple[int, int, int] with List[int] to support easier the 2D case

* Adding more docs and references

* Change naming conventions of classes to follow the same pattern as MobileNetV3

* Fix test breakage.

* Update todos

* Performance optimizations.

* Add support to MViT v1 (#6179)

* Switch implementation to v1 variant.

* Fix docs

* Adding back a v2 pseudovariant

* Changing the way the network are configured.

* Temporarily removing v2

* Adding weights.

* Expand _squeeze/_unsqueeze to support arbitrary dims.

* Update references script.

* Fix tests.

* Fixing frames and preprocessing.

* Fix std/mean values in transforms.

* Add permanent Dropout and update the weights.

* Update accuracies.

* Fix documentation

* Remove unnecessary expected file.

* Skip big model test

* Rewrite the configuration logic to reduce LOC.

* Fix mypy

* Added base tests for rotate_image_tensor

* Updated resize_image_tensor API and tests and fixed a bug with max_size

* Refactored and modified private api for resize functional op

* Fixed failures

* More updates

* Updated proto functional op: resize_image_*

* Added max_size arg to resize_bounding_box and updated basic tests

* Update functional.py

* Reverted fill/center order for rotate
Other nits

* Refactored and modified private api for resize functional op

* Fixed failures

* More updates

* Fixed flake8

* Add rough raft-stereo implementation on prototype/models

* Add standard raft_stereo builder, and modify context_encoder to be more similar with original implementation

* Follow original implementation on pre-convolve context

* Fix to make sure we can load original implementation weight and got same output

* reusing component from raft

* Make the raft_stereo_fast able to load original weight implementation

* Format with ufmt and update some comment

* Use raft FlowHead

* clean up comments

* Remove unnecessary import and use ufmt format

* Add __all__ and more docs for RaftStereo class

* Only accept param and not module for raft stereo builder

* Cleanup comment

* Adding typing to raft_stereo

* Update some of raft code and reuse on raft stereo

* Use bool instead of int

* Make standard raft_stereo model jit scriptable

* Make the function _make_out_layer using boolean with_block and init the block_layer with identity

* Separate corr_block into two modules for pyramid and building corr features

* Use tuple if input is not variable size, also remove default value if using List

* Format using ufmt and update ConvGRU to not inherit from raft in order to satisfy both jit script and mypy

* Change RaftStereo docs input type

* Ufmt format raft

* revert back convgru to see mypy errors, add test for jit and fx, make the model fx compatible

* ufmt format

* Specify device for new tensor, dont init module then overwrite and put if-else instead

* Ignore mypy problem on override, put back num_iters on forward

* Revert some effort to make it fx compatible but unnecessary now

* refactor code and remove num_iters from RaftStereo constructor

* Change to raft_stereo_realtime, and specify device directly for tensor creation

* Add description for raft_stereo_realtime

* Update the test for raft_stereo

* Fix raft stereo prototype test to properly test jit script

* Ufmt format

* Test against expected file, change name from raft_stereo to raft_stereo_builder to prevent import error

* Revert __init__.py changes

* Add default value for non-list param on model builder

* Add checking on out_with_block length, add more docs on the encoder

* Use base instead of basic since it is more commonly used

* rename expect file to base as well

* rename on test

* Revert the revert of __init__.py, also revert the adding default value to _raft_stereo to follow the standard pattern

* ufmt format __init__.py

* Added elastic augment

* ufmt formatting

* updated comments

* fixed circular dependency issue and bare except error

* Fixed three type checking errors in functional_tensor.py

* ufmt formatted

* changed elastic_deformation to a more common implementation

Implementation uses alpha and sigma to control strength and smoothness of the displacement vectors in elastic_deformation instead of control_point_spacings and sigma.

* ufmt formatting

* Some performance updates

Put random offset vectors to device before gaussian_blur is applied speeds it up 3-fold.

* fixed type error

* fixed again a type error

* Update torchvision/transforms/functional_tensor.py
Co-authored-by: vfdev <vfdev.5@gmail.com>

* Added some requested changes

- pil image support similar to GaussianBlur
- changed interpolation arg to InterpolationMode
- added a wrapper in torchvision.transforms.functional.py that gets called by the class in transforms.py
-renamed it to ElasticTransform
- handled sigma = 0 case

* added img docstring

* added some tests

* Updated tests and the code

* Added the requested changes to the arguments of F.elastic_transform

Added random_state and displacement as arguments to F.elastic_transform

* fixed the type error

* Fixed tests and docs

* implemented requested changes

Changes:
1) alpha AND sigma OR displacement must be given as arguments to transforms.functional_tensor.elastic_transform instead of alpha AND sigma AND displacement
2) displacements are accepted in transforms.functional.elastic_transform as np.array and torch.Tensor instead of only accepting torch.Tensor

* ufmt formatting

* trochscript error resolved

replaced torch.from_numpy() to torch.Tensor() to make it compatible to torchscript

* revert to torch.from_numpy()

* updated argument checks and errors

- In F.elastic_transform added check to see if both user inputs img and displacement are either of type PIL Image and ndarray or both of type tensor.
- In F_t.elastic_transform added check if alpha and sigma are None if displacement is given or vice versa.

* fixed seed error

changed torch.seed to torch.manual_seed in F_t.elastic_transform

* Reverted displacement type and other cosmetics

* Other minor improvements

* changed gaussian_blur filter size

changed gaussian_blur filter size
from
4 * int(sigma) + 1
to
int(8 * sigma + 1)
to make it consistent with ernestums implementation

* resolved merge error

* Revert "resolved merge error"

This reverts commit 6a4a4e74ff4d078e2c2753d359185f9a81c415d0.

* resolve merge error

* ufmt formatted

* ufmt formated once again..

* fixed unsupported operand error

* Update API and removed random_state from functional part

* Added default values

* Added ElasticTransform to gallery and updated the docstring

* Updated gallery and added _log_api_usage_once
BTW, matplotlib.pylab is deprecated

* Updated gallery transforms code

* Updates according to review
Co-authored-by: vfdev <vfdev.5@gmail.com>

* Update _pil_constants.py

* Update _pil_constants.py

* Fix flake8

* Fixed two related warnings in tests

* switch dir with hasattr
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Fix the issue :)

* Intellij vs ufmt battle

* remove .item()

* Added tests for other padding modes

* Fixed expected mask dtype

* Applied comments from review

* add tests for F.pad_bounding_box

* Added correctness tests for pad and reimplemented bbox op to keep dtype

* Update _geometry.py
Co-authored-by: vfdev <vfdev.5@gmail.com>

Add .float() before .mean() on test_backbone_utils.py because .mean() dont accept integer dtype (#6090)