GitLab

* Improve read_file for Windows

* Fix lint

* Use _stat64 instead

* Apply suggesion

* Fix lint

* Added GaussianBlur transform

* fixed linting

* supports fixed radius for kernel

* [WIP] New API for gaussian_blur

* Gaussian blur with kernelsize and sigma API

* Fixed implementation and updated tests

* Added large input case and refactored gt into a file

* Updated docs

* fix kernel dimesnions order while creating kernel

* added tests for exception handling of gaussian blur

* fix linting, bug in tests

* Fixed failing tests, refactored code and other minor fixes
Co-authored-by: vfdev-5 <vfdev.5@gmail.com>

* adding base files

* setup modification to actually build the thing

* video api constructor registration

* FAIL metadata

* FAIL update for QS

* revert

* debugging with Victor

* adding base files

* setup modification to actually build the thing

* video api constructor registration

* FAIL metadata

* FAIL update for QS

* revert

* debugging with Victor

* metadata registration works

* API build next

* test

* Merge change

* formatting parameters to avoid the segfault

* next now works on a video

* make size of the output tensor format dependent

* Make next work on audio stream only as well

* refactoring the _setCurrentStream param

* Fixing the last frame return and sensor

* todo docs

* Formatting

* cleanup and comments

* introducing new tests for the API

* cleanup

* Comment out unnecesary format (will add following FFMPEG fix)

* Reformat parsing function

* removing the seek bug `get_decoder_params`

* Removing unnecessary code/variables

* enforce RGB24 as a reading format (will crash before ffmpeg fix)

* permute the dimensions to return (RGB x H x W)

* Changing the return type to std::tuple<torch::Tensor, double> as opposed to tensor list

* Adjusting tests for the new return type

* remove unnecessary jitter

* clangangangang

* Metadata return changes (#1)

* remove implicit calls to set a current stream (#2)

* Adding new tests to check the accuracy of the seek

* cleanup debugging statements

* adding base files

* setup modification to actually build the thing

* video api constructor registration

* FAIL metadata

* FAIL update for QS

* revert

* debugging with Victor

* adding base files

* video api constructor registration

* FAIL metadata

* FAIL update for QS

* revert

* debugging with Victor

* metadata registration works

* API build next

* test

* Merge change

* formatting parameters to avoid the segfault

* next now works on a video

* make size of the output tensor format dependent

* Make next work on audio stream only as well

* refactoring the _setCurrentStream param

* Fixing the last frame return and sensor

* todo docs

* Formatting

* cleanup and comments

* introducing new tests for the API

* cleanup

* Comment out unnecesary format (will add following FFMPEG fix)

* Reformat parsing function

* removing the seek bug `get_decoder_params`

* Removing unnecessary code/variables

* enforce RGB24 as a reading format (will crash before ffmpeg fix)

* permute the dimensions to return (RGB x H x W)

* Changing the return type to std::tuple<torch::Tensor, double> as opposed to tensor list

* Adjusting tests for the new return type

* remove unnecessary jitter

* clangangangang

* Metadata return changes (#1)

* remove implicit calls to set a current stream (#2)

* Adding new tests to check the accuracy of the seek

* cleanup debugging statements

* Addressing PR comments

* addressing Francisco's comments

* CLANG build formatting

* Updated testing to test against pyav for the video tensor reads

* Formatting

* remove pyav from pip deps and add it to conda build

* add pyav and ffmeped to conda builds

* Formatting?

* Setting up linter once and for all hopefully

* Testing pyav

* Fix to 8.0.0

* Try 6.2.0

* See what happens with av from pip

* Remove FFMPEG blocker

* What is going on?

* More tests

* Forgot something

* unblocker

* Check if cache is messing up with things

* Now try with different ffmpeg

* Now try with different ffmpeg

* Testing pyav

* Fix to 8.0.0

* Try 6.2.0

* See what happens with av from pip

* What is going on?

* More tests

* Forgot something

* Check if cache is messing up with things

* Now try with different ffmpeg

* Now try with different ffmpeg

* Do not install av

* Test with ffmpeg 4.2

* clean up video tests

* cleaning up the tests a bit to better test partial reading

* arrgh linter

* Forgot the av test

* forgot av test

* checkout build files from master

* revert circleci

* addressing Franciscos comments

* addressing Franciscos comments

* Ignore ffmpeg in travis
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>
Co-authored-by: Edgar Andrés Margffoy Tuay <andfoy@gmail.com>

* fixies small bug in box_convert

* activates jit test

* Passes JIT test

* fixes typo

* adds error tests, removes assert

* implements to proposal2

* Add write_file

* Fix lint

* Add PyTorch FFmpeg to wheel and conda distributions

* Try to install wget from conda

* Add yq flag on Mac

* Correct copy instructions

* Use cURL on Windows

* Call bzip2 directly due to msys2/MSYS2-packages#1548

* Copy ffmpeg binaries to system-wide directories

* Try to use std:c++17 on Windows

* Try to define ssize_t on Windows

* Use C++14

* Declare AVRational structs explicitly

* Initialize AVRational explicitly

* Replace macro to prevent errors on Windows

* Replace AV_TIME_BASE_Q

* Add library paths for video extension

* Force ffmpeg from pytorch channels?

* Fix clang style warnings

* Update CONDA_CHANNEL_FLAGS

* Fix clang style issues

* Update unittest

* Use FFmpeg 4.2

* Install correct version on Mac

* Pin av version to 8.0.0

* Fix string formatting issue

* Fix pip pinning

* Try with 8.0.1

* Use av 8.0.2

* Remove trailling whitespaces

* Disable test_io_opt.py

* Disable test_datasets_video_utils
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

* Add read_file

* Add test for non-existent file

* Fix lint

* Lint v2

* Try fix windows

* Try fix Windows v2

* Lint

* Windows v3

* Missed one change in the adapted function

* Try again on Windows

* One more try on Windows

* Give up on tempfile for now

* Are extensions what's missing on Windows?

* Investigating if the issue is on our side

* Try deleting tensor which could hold into the file

* Put back temporary folder

* Negative padding for functional_tensor symmetric

Along with #2744 this will make negative padding
uniform between PIL and Tensor #2381

* Enable tests for negative symmetric pad with tensor
Co-authored-by: vfdev <vfdev.5@gmail.com>

* add download tests for CIFAR

* fix tests in case of bad request

* make convert_image_dtype scriptable

* move convert dtype to functional_tensor since only works on tensors

* retain availability of convert_image_dtype in functional.py

* Update code and tests

* Replaced int by torch.dtype

* int -> torch.dtype and use F instead of F_t

* Update functional_tensor.py

* Added CPU/CUDA+batch tests

* Fixed tests according to review
Co-authored-by: Brian <nairbv@yahoo.com>

* make convert_image_dtype scriptable

* move convert dtype to functional_tensor since only works on tensors

* retain availability of convert_image_dtype in functional.py

* Update code and tests

* Replaced int by torch.dtype

* int -> torch.dtype and use F instead of F_t

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

* Negative padding for functional_pil #2381

* Tests for PIL negative padding #2381

* Move PIL vs tensor test inside test_pad

* Adapt test_pad from test_transforms_tensor.py
Co-authored-by: vfdev <vfdev.5@gmail.com>

* adds boxes conversion

* adds documentation

* adds xywh tests

* fixes small typo

* adds tests

* Remove sphinx theme

* corrects assertions

* cleans code as per suggestion
Signed-off-by: Aditya Oke <okeaditya315@gmail.com>

* reverts assertion

* fixes to assertEqual

* fixes inplace operations

* Adds docstrings

* added documentation

* changes tests

* moves code to box_convert

* adds more tests

* Apply suggestions from code review

Let's leave those changes to a separate PR

* fixes documentation
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

- Updated code and tests to support batch of tensors, e.g. input of shape (B, C, H, W).

* add download tests for Caltech(101|256)

* lint

Otherwise, torch jit scripted function raises exception on save

* Add encode/write_png functions

* Do not redefine

* Style issues correction

* Comply with low-level interface

* Minor comment correction

* Add python frontend functions

* Add encode_png test

* Pass compession level to encode_png

* Do not compare output buffers

* Convert to bytes

* Compare pil image instead of buffer

* Add error tests

* Add test_write_png

* Remove png test assets

* Register writePNG correctly

* Update write_png docstring

* Do not preserve PIL image beyond the scope
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

* Add decode_image op

* Fix lint

* More lint

* Add C10_EXPORT

* fix triggers for scheduled workflow

* more fix

* add missing repository checkout

* try fix label in template

* rewrite test infrastructure

* trigger issue generation

* try fix issue template

* try remove quotes

* remove buggy label

* try fix title

* cleanup

* add more test details

* reenable issue creation
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

* Add decode and write JPEG ops

* Fix styling issues

* Use int64_t instead of int

* Use std::string

* Use jpegcommon.h for read_jpeg

* Minor updates to error handling in read

* Include header only once

* Reverse header inclusion

* Update common header

* Add common definitions

* Include string

* Include header?

* Include header?

* Add Python frontend calls

* Use unsigned long directly

* Fix style issues

* Include cstddef

* Ignore clang-format on cstddef

* Also include stdio

* Add JPEG and PNG include dirs

* Use C10_EXPORT

* Add JPEG encoding test

* Set quality to 75 by default and add write jpeg test

* Minor error correction

* Use assertEquals by assertEqual

* Remove test results

* Use pre-saved PIL output

* Remove extra PIL call

* Use read_jpeg instead of PIL

* Add error tests

* Address review comments

* Fix style issues

* Set test case to uint8

* Update test error check

* Apply suggestions from code review

* Fix clang-format

* Fix lint

* Fix test

* Remove unused file

* Fix regex error message

* Fix tests
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

* tries adding genaralized_iou

* fixes linting

* Adds docs for giou, iou and box area

* fixes lint

* removes docs to fixup in other PR

* linter fix

* Cleans comments

* Adds tests for box area, iou and giou

* typo fix for testCase

* fixes typo

* fixes box area test

* fixes implementation

* updates tests to tolerance

* [WIP] All transforms are now derived from torch.nn.Module
- Compose, RandomApply, Normalize can be jit scripted

* Fixed flake8

* Updated code and docs
- added getattr to Lambda and tests
- updated code and docs of Compose
- added failing test with append/extend on Composed.transforms

* Fixed flake8

* Updated code, tests and docs

* Make JPEG/PNG return images in CHW format

* Use int array

* [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

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

* Removed float16/cpu case

* Add CMake build pipeline

* Add CMake build workflow

* Add executable permissions to script

* Install cmake on Windows/MacOS

* Install conda-build before setting up MSVC

* Install PyTorch from nightly

* Do not use conda-build variables

* Add path to CMake

* Install libpng and libjpeg

* Perform make

* Call msbuild on Windows

* Add missing yq

* Use vc_env_helper

* Use string instruction

* Escape configuration option

* Remove configuration flag

* Try to pass -p

* Use caret to escape equal sign

* Escape string option in Windows

* Try to call other bat

* Remove Windows/GPU CMake

* Add tracing cpp test

* Script model instead of tracing it

* Try to register operators manually

* Use manylinux-cuda102

* Activate conda env on Linux

* Build and run sample tracing test

* Add empty echo

* Remove unnecessary register

* Copy headers on Mac

* Revert to 2xlarge

* Include /usr/local/include on Mac

* Install pillow on Windows

* Install future

* Install torchvision on Windows

* Set include flag

* Add torchlib to PATH

* Normalize path via cygpath

* Register ops on Windows

* Minor error correction

* Register CPU/GPU ops on DLL library and register ops via reference

* Install dataclasses

* Install dataclasses using pip

* Address clang formatting issue

* Try to use an actual GPU instance on Linux

* Remove extra environment section

* Declare environment explicitly

* Regenerate

* Pass env variables to Dokcer

* Regenerate circleci

* Test tracing on GPU

* Use GPU medium

* Regenerate

* Use cuda101

* Regenerate

* Do not use pre-trained weights

Avoids having to download pretrained files, which could cause flaky tests
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

* split off tests for dataset downloadability

* ignore download tests during normal test suite

* lint

* add retry mechanic

* 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

* Rewritten adjust_* tests
- split test_adjustments into 3 separate tests
- unified testing approach with test_adjust_gamma

* Added ColorJitter tests

* Relaxed tolerance for functional adjust-* tests

* Removed wrong merge and commented code

* [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

* Add support for export ROIAlign

* Fix for feedback

* flake8

* fix images extraction

* remove test split

* fix tests

* be less clever in test data generation

* remove micro optimization

* lint

* Improve transforms test codebase
- refactored compareTensorToPIL, _create_data, approxEqualTensorToPIL methods

* Fixed flake8

* initial draft

* [dirty] progress

* remove inheritance from ImageFolder

* add tests

* lint

* fix type hints

* align getitem with other datasets

* remove unused import

* add docstring

* guard existing image folders from overwrite

* add missing entry in docstring

* make fixpath more legible

* add Places365 to docs