GitLab

* fix RandomPhotometricDistort

* Update torchvision/prototype/transforms/_color.py
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* add cleanup transformation for bounding boxes

* change the cleanup transform to an actual compose

* address review

* address naming

* use box_area op

* [skip ci] plural

* split compose into its parts and expose them

* cleanup

* more import cleanup

* Update torchvision/prototype/transforms/_misc.py
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* use the same base class for Label and OneHotLabel

* mypy

* rename typevar

* Move imports on constructor.

* Turn `_F` to a property.

* fix linter

* Fix mypy

* Make it class-wide attribute.

* Add tests based on code review

* Making changes from code-reviews.

* Remove the new tests.

* Clean up.

* Adding comments.

* Update the comment link.

* add deprecated color conversion functionals

* allow grayscale tensor inputs in rgb_to_grayscale

* add cloning to tensor no-op

* improve todo comment

* [skip ci]

* use legacy kernels

use legacy kernels

* fix import

* remove duplicate code

* remove duplicate check

* Fix out-of-bounds read in decode_png

* Fix lint

* Use size_t instead of int to fix sign-compare check

* Add a unit-test to decode currupted png file

* Fix linter

* Update torchvision/csrc/io/image/cpu/decode_png.cpp

* Replace png_error with TORCH_CHECK
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Update error message

* Update error message
Co-authored-by: vfdev <vfdev.5@gmail.com>

* Fix linter
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>
Co-authored-by: vfdev <vfdev.5@gmail.com>

* WIP

* [proto] Added SimpleCopyPaste transform

* Refactored and cleaned the implementation and added tests

* Fixing code

* Fixed code formatting issue

* Minor updates

* Fixed merge issue
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* cleanup prototype auto augment transforms

* remove custom fill parsing from auto augment

* fix MixUp and CutMix

* improve error message

* add dispatcher for erase image kernels

* simplify RandomErasing

* replace query_image with query_image_dimensions

* use value sentinel and fix test for RandomErasing

* image_dimensions -> chw

* remove BatchMultiCrop

* address review

* let FiveCrop return tuples

* WIP

* Fixed dtype correction and tests

* Removed PIL Image support and output always Tensor

* [proto] Fixed to_image_tensor and to_image_pil

* Fixed failing test

* S3D initial commit

* add model builder code and docstrings

* change classifier submodule, populate weights enum

* fix change of block args from List[List[int]] to ints

* add VideoClassification to transforms

* edit weights url for testing, add s3d to models.video init

* norm_layer changes

* norm_layer and args fix

* Overwrite default dropout

* Remove docs from internal submodules.

* Fix tests

* Adding documentation.

* Link doc from main models.rst

* Fix min_temporal_size

* Adding crop/resize parameters in references script

* Release weights.

* Refactor dropout.

* Adding the weights table in the doc
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>
Co-authored-by: Vasilis Vryniotis <vvryniotis@fb.com>

* port `FixedSizeCrop` from detection references to prototype transforms

* mypy

* [skip ci] call invalid boxes and corresponding masks and labels

* cherry-pick missing functions from #6401

* fix feature wrapping

* add test

* mypy

* add input type restrictions

* add test for _get_params

* fix input checks

* Added ETH3D stereo dataset

* Small doc-reformating

* Removed assertions with no use, changed np conversion

* Added ETH3D stereo dataset

* Removed assertions with no use, changed np conversion

* rebased on main

* Revert "Removed assertions with no use, changed np conversion"

This reverts commit 1478a8c056bbed59b6f4a67f78a5cfac84cc9fda.

* Update to np.bool instead of np.bool_

* lint and mypy nit fix

* test nit

* expand has_any and has_all to also accept check callables

* add test and fix has_all

* add support for simple tensor images to CutMix, MixUp and RandomIoUCrop

* remove TODO

* remove pythonic syntax sugar

* simplify

* use concreate examples in test rather than abstract ones

* simplify further

* Fix typos

* Fix link

* pre-commit

* Update torchvision/datasets/food101.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* replace query_recursively with pytree implementation

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

* [proto] Ported RandomIoUCrop from detection refs

* Scope acceptable data types

* Added get_params test

* Added test__transform_empty_params

* Added support for OneHotLabel and tests

* Added tests for mask

* Updated error message

* Apply suggestions from code review
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* Added support for OHE masks and tests

* Ignored mypy error

* Fixed forward call on sample

* Added a todo
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

Summary:
This diff adds **`skipOperationNotPermittedPackets`** to `DecoderParameters`.

Once that is set to `True`, it allows decoder to skip through those packets, that are causing `EPERM` errors and result into stoppage of consuming a stream.

Reviewed By: jdsgomes

Differential Revision: D38732706

fbshipit-source-id: a5cb64e14edda376e6ba240089ebee2e3a9865d0
Co-authored-by: Oleksandr Voietsa <ovoietsa@fb.com>

Summary:
Pull Request resolved: https://github.com/pytorch/vision/pull/6432



According to the documentation the packet has to be freed after `av_read_frame()` call.
```
 If pkt->buf is NULL, then the packet is valid until the next
 av_read_frame() or until avformat_close_input(). Otherwise the packet
 is valid indefinitely. In both cases the packet must be freed with
 av_packet_unref when it is no longer needed.
```

Differential Revision: D38747612

fbshipit-source-id: 2e4ccc8365d0d97e5da756ff9c1dcdf27ed323f0
Co-authored-by: Oleksandr Voietsa <ovoietsa@fb.com>

* Added Falling Things datasets

* Renamed split to variant

* Update torchvision/datasets/_stereo_matching.py

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

* added SceneFLow variant datasets

* Changed split name to variant name

* removed trailing commented code line

* Added InStereo2k dataset

* 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

* Added InStereo2k dataset

Resolves issue reported at https://github.com/pytorch/vision/commit/6e535db255cee3ce878dd7a54dda01d4ec8932c1#commitcomment-81409388

There seems to be a misspelling on the name of the parameter. This PR updates `total_steps` to `total_iters` which is the correct argument.

* 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