GitLab

Co-authored-by: vfdev <vfdev.5@gmail.com>

* [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

* Fixes #2547

- Added warning to the documentation of F_pil and F_t functions

* Update functional_tensor.py

* Improved functional tensor geom transforms to work on floatX dtype
- Fixes #2600
- added tests
- refactored test_affine

* Removed float16/cpu case

* adjust_hue now supports inputs of type Tensor

* Added comparison between original adjust_hue and its Tensor and torch.jit.script versions.

* Added a few type checkings related to adjust_hue in functional_tensor.py in hopes to make F_t.adjust_hue scriptable...but to no avail.

* Changed implementation of _rgb2hsv and removed useless type declaration according to PR's review.

* Handled the range of hue_factor in the assertions and temporarily increased the assertLess bound to make sure that no other test fails.

* Fixed some lint issues with CircleCI and added type hints in functional_pil.py as well.

* Corrected type hint mistakes.

* Followed PR review recommendations and added test for class interface with hue.

* Refactored test_functional_tensor.py to match vfdev-5's d016cab branch by simple copy/paste and added the test_adjust_hue and ColorJitter class interface test in the same style (class interface test was removed in vfdev-5's branch for some reason).

* Removed test_adjustments from test_transforms_tensor.py and moved the ColorJitter class interface test in test_transforms_tensor.py.

* Added cuda test cases for test_adjustments and tried to fix conflict.

* Updated tests
- adjust hue
- color jitter

* Fixes incompatible devices

* Increased tol for cuda tests

* Fixes potential issue with inplace op
- fixes irreproducible failing test on Travis CI

* Reverted fmod -> %
Co-authored-by: vfdev-5 <vfdev.5@gmail.com>

* Added cuda torch.jit tests for rgb-hsv tensor conversion ops

* Reverted deleted test

* [WIP] Unify ops Grayscale and RandomGrayscale

* Unified inputs for grayscale op and transforms
- deprecated F.to_grayscale in favor of F.rgb_to_grayscale

* Fixes bug with fp input

* [WIP] Updated code according to review

* Removed unused import

* Adapted almost all functional tensor tests on CPU/CUDA
- fixed bug with transforms using generated grid
- remains *_crop, blocked by #2568
- TODO: test_adjustments

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

* Fixed issues according to review

* Split tests into two: cpu and cuda

* Updated test_adjustments to run on CPU and CUDA
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

- Updated docs
- Put warning in the code
- Updated tests

* Unified input for RandomPerspective

* Updated docs

* Fixed failing test and bug with torch.randint

* Update test_functional_tensor.py

* [WIP] Added unified input perspective transformation code

* Unified input for F.perspective
- added tests
- updated docs

* Added more random test configs

* Fixed the code according to PR's review

* Added code for F_t.rotate with test
- updated F.affine tests

* Rotate test tolerance to 2%

* Fixes failing test

* [WIP] RandomRotation

* Unified RandomRotation with tests

* Added code for F_t.rotate with test
- updated F.affine tests

* Rotate test tolerance to 2%

* Fixes failing test

* Optimized _expanded_affine_grid with a single matmul op

* Recoded _compute_output_size

* [WIP] recoded F_t.rotate internal methods

* [WIP] Fixed F.affine to support rectangular images

* Recoded _gen_affine_grid to optimized version ~ affine_grid
- Fixes flake8

* [WIP] Use _gen_affine_grid for affine and rotate

* Fixed tests on square / rectangular images for affine and rotate ops

* Removed redefinition of F.rotate
- due to bad merge

* Added code for F_t.rotate with test
- updated F.affine tests

* Rotate test tolerance to 2%

* Fixes failing test

* Optimized _expanded_affine_grid with a single matmul op

* Recoded _compute_output_size

* Fixed resize to only match the smaller edge when an int is given instead of always

* Added test cases for resize()

* Clarify scaling of ToTensor transform for target masks in the documentation

* Add link to the segmentation reference
Co-authored-by: vfdev <vfdev.5@gmail.com>
Co-authored-by: vfdev <vfdev.5@gmail.com>

* fix fill parameter for PIL pad

* add test

* fix

* lint

* [WIP] Unified input for T.RandomAffine

* Unified inputs for T.RandomAffine transformation

* Update transforms.py

* Updated docs of F.affine fillcolor

* Update transforms.py

* add torchscriptable adjust_gamma transform

https://github.com/pytorch/vision/issues/1375



* changes based on code-review

* Apply suggested change to add type hint

Required by mypy, even thought technically incorrect due to possible Image parameter. torchscript doesn't support a union based type hint.
Co-authored-by: vfdev <vfdev.5@gmail.com>
Co-authored-by: vfdev <vfdev.5@gmail.com>

* [WIP] F.affine

* [WIP] F.affine + tests

* Unified input for F.affine

* Removed commented code

* Removed unused imports

Incoherence is when affine transformation is 90 degrees rotation and output contains a zero line

* Minor docs improvement

* Replaced link by already defined `filters`_

* [WIP] Unify random resized crop

* Unify input for RandomResizedCrop

* Fixed bugs and updated test

* Added resized crop functional test
- fixed bug with size convention

* Fixed incoherent sampling

* Fixed torch randint review remark

* [WIP] F.resize with tensor

* Adapted T.Resize and F.resize with a test

* According to the review, fixed copy-pasted messages and unused imports

* Related to #2292
- RandomErasing is not scriptable

* Fixed code according to review comments
- added additional checking of value vs img num_channels

* [WIP] Added symmetric padding mode

* Added check and raise error if padding is negative for symmetric padding mode

* Added test check for raising error if negative pad

- RandomCrop: crop with padding using all commonly supported modes

* F_t add factor nonnegativity checks for adjust_*

* Update functional_tensor.py

* Update functional_tensor.py

* Update functional_tensor.py

* Update functional_tensor.py

* [WIP] functional_tensor supports more padding modes

* [WIP] Support all padding modes

* Removed wip symmetric mode

* Improvements according to the review

* [WIP] Unified Tensor/PIL crop

* Fixed misplaced type annotation

* Fixed tests
- crop with padding
- other tests using mising private functions: _is_pil_image, _get_image_size

* Unified CenterCrop and F.center_crop
- sorted includes in transforms.py
- used py3 annotations

* Unified FiveCrop and F.five_crop

* Improved tests and docs

* Unified TenCrop and F.ten_crop

* Removed useless typing in functional_pil

* Updated code according to the review
- removed useless torch.jit.export
- added missing typing return type
- fixed F.F_pil._is_pil_image -> F._is_pil_image

* Removed useless torch.jit.export

* Improved code according to the review

* [WIP] Add Tensor implementation for pad

* Unified Pad and F.pad opertion for PIL and Tensor inputs

* Added another test and improved docstring

* Updates according to the review

* Cosmetics and replaced f-string by "".format

* Updated docstring
- added compatibility support for padding as [value, ] for functional_pil.pad
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

I was reading through the code and noticed a few spelling errors
orignal -> original
maintaing -> maintaining

* add convert_image_dtype to functionals

* add ConvertImageDtype transform

* add test

* remove underscores from numbers since they are not compatible with python<3.6

* address review comments 1/3

* fix torch.bool

* use torch.iinfo in test

* fix flake8

* remove double conversion

* fix flake9

* bug fix

* add error messages to test

* disable torch.float16 and torch.half for now

* add docstring

* add test for consistency

* move nested function to top

* test in CI

* dirty progress

* add int to int and cleanup

* lint
Co-authored-by: Philip Meier <meier.philip@posteo.de>

* Adjust hue

* Adjust hue acceps torch.tensor uint8
Co-authored-by: Vikram Mukunda Rao Tankasali <vikramtankasali@devvm765.lla0.facebook.com>

* feat: torchscriptable adjusments

* fix: tensor output type

* feat: ColorJitter torchscriptable

* fix: too many blank lines

* fix: documentation spacing and torchscript annotation

* refactor: list type for _check_input

* refactor: reverting to original syntax
Co-authored-by: clement.joudet <clement.joudet@inventia.life>

* Make RandomHorizontalFlip torchscriptable

* Make _is_tensor_a_torch_image more generic

* Make RandomVerticalFlip torchscriptable (#2283)

* Make RandomVerticalFlip torchscriptable

* Fix lint

* Bugfix in pad

* Address review comments

* Fix lint