GitLab

* Fix normalize for different dtype than float32

* Fix lint

Change documentation of perspective(). The doc was about an old version that used directly transformation parameters

Enable fillcolor option for affine transformation for Pillow >= 5.0.0 as described

* final changes

* final

* linter

* test changes

* linter

* lint

* indent

* lint

* minor changes

* parameter added

* ci

* ci fixes

* indent

* indent

* indent

* arg fixed

Changed 'channely' to 'channel' in the comments of normalize function.

* randomresizedmods

* lint checks

* test to randomrescrop added

* updates

* tests updated

* tests updated

* upd

* updates

* Update torchvision/transforms/transforms.py
Co-Authored-By: surgan12 <33121121+surgan12@users.noreply.github.com>

* tests changed

* trvis

* travis

* fixes syntax

* ...

* flake fixes

* flake_fixes

* flake_fixes2

* doc change

* doc changes

* lint_checks

* Update transforms.py

* normalise

* some changes

* Update functional.py

* Update functional.py

* code changes

* modes added

* tests_added

* Update test_transforms.py

* Update test_transforms.py

* Update test_transforms.py

* bug fixes to_tensor

* tensor checked

* pad updated

* checked pad

* pad checked

* pad checked

* added separate checks for dimensionality in to_pil_image and added tests

* updated to_pil_image to use both 2D ndarrays and tensors, as well as refactored the tests

* cast mnist targer to int

* fix unused variables

* fix syntax in tests

* remove # noqa; rename l variable to line_split; use except OSError

* add W504

* add W504

* add W503,W504 tox.ini

* Fix PIL link

* Make normalize more efficient

* fix a bug described in issue #488

* improve doc described in issue #488

* add arguments in RandomCrop as proposed by vfdev-5 in PR #489

* Add case in test_to_tensor for PIL Images mode '1'

* Add support in ToTensor for PIL Images mode '1'

* Fix pep8 issues

* Added reflect, symmetric and edge padding

* Updated padding docs, added tests

Add testing case with Pillow-SIMD, fix bug in RandomAffine if Pillow<5.0.0, add missing docs for affine (#439)

* Add random affine transformation

* Rewrite __repr__

* Refactor affine transform and update tests

if on dtype -> elif on dtype

Fixes https://github.com/pytorch/vision/issues/399.

The only case of floating point supported by PIL seems to be `F`, so this should fix it.

* add to_grayscale + randomGrayscale

add rotate and RandomRotation to transforms

* refactor transforms and add transforms/functional.py

* add __all__ to transforms.py