GitLab

Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>
Co-authored-by: Nicolas Hug <nh.nicolas.hug@gmail.com>

Co-authored-by: Nicolas Hug <nh.nicolas.hug@gmail.com>

Co-authored-by: Nicolas Hug <nh.nicolas.hug@gmail.com>

Fixes for multiple tests on s390x

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

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

Co-authored-by: Liron <liron@tapwithus.com>
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>
Co-authored-by: Nicolas Hug <nh.nicolas.hug@gmail.com>

Co-authored-by: Philip Meier <github.pmeier@posteo.de>
Co-authored-by: vfdev <vfdev.5@gmail.com>

* fix typos throughout the code base

* fix grammar

* revert formatting changes to gallery

* revert 'an uXX'

* remove 'number of the best'

* introduce nearest-exact interpolation

* update prototype tests

* update stable tests

* Remove Kinetics400 class

* Remove '2007-test' in VOC

* Remove some MobileNet layer classes

* Remove torchvision/models/segmentation/segmentation.py

* Remove some MultiScaleRoIAlign methods

* Remove torchvision/transforms/_functional_video.py

* Remove torchvision/transforms/_transforms_video.py

* Remove resample parameter in transforms

* Remove 'range' parameter

* Remove 'fill_value' parameter in transforms

* Revert to original warning for C++ models - looks like we should still keep them around?

* pre-commit

* Fix docs

* Remove test/test_transforms_video.py

* Some fixes

* Remove more tests

* Revert changes to C++ models

* Add back _transforms_video and change warning message

* Change back the warning message, and will change the warning message on separate PR
Co-authored-by: YosuaMichael <yosuamichaelm@gmail.com>
Co-authored-by: Yosua Michael Maranatha <yosuamichael@fb.com>

* clean up bboxes

* Adding padding_mode in pad_bbox

* Fixing tests and renamed _compute_output_size to appropriate names
Co-authored-by: Vasilis Vryniotis <vvryniotis@fb.com>

* [proto] Fixed to_image_tensor and to_image_pil

* Fixed failing test

* [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>

* upgrade usort to

* Also update black

* Actually use 1.0.2

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

* Refactored and modified private api for resize functional op

* Fixed failures

* More updates

* Fixed flake8

* 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>

* Requested here https://github.com/pytorch/vision/pull/5898#discussion_r864765799

.

* Fix tests

* ufmt, not black
Co-authored-by: Philip Meier <github.pmeier@posteo.de>
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Update transforms for PIL deprecation

* Changes agreed at pytorch/vision#5898

* black, sort constants, version check

* Format tests

* Square brackets

* Update torchvision/transforms/_pil_constants.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: 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>

* Update docstring of adjust_hue
Signed-off-by: Behrooz <3968947+drbeh@users.noreply.github.com>

* Update docstring of ColorJitter
Signed-off-by: Behrooz <3968947+drbeh@users.noreply.github.com>

* Minor corrections
Signed-off-by: Behrooz <3968947+drbeh@users.noreply.github.com>

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

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