Bump torchvision from 0.18.1 to 0.22.0

[dependabot]

Bumps torchvision from 0.18.1 to 0.22.0.

Release notes

Sourced from torchvision's releases.

Torchvision 0.22 release

Key info

⚠️ We are updating the areas that TorchVision will be prioritizing in the future. Please take a look at pytorch/vision#9036 for more details.

⚠️ We are deprecating the video decoding and encoding capabilities of TorchVision, and they will be removed soon in version 0.25 (aimed for end of 2025). We encourage users to migrate existing video decoding code to rely on TorchCodec project, where we are consolidating all media decoding/encoding functionalities of PyTorch.

Detailed Changes

Deprecations

[io] Video decoding and encoding capabilities are deprecated and will be removed soon in 0.25! Please migrate to TorchCodec! (#8997)

Bug Fixes

[io] Fix sync bug with encode_jpeg on CUDA (#8929) [transforms] pin_memory() now preserves TVTensor class and metadata (#8921)

Improvements

[datasets] Most datasets now support a loader parameter, which allow you to decode images directly into tensors with torchvision.io.decode_image(), instead of relying on PIL. This should lead to faster pipelines! (#8945, #8972, #8939, #8922) [datasets] Add classes attribute to the Flowers102 dataset (#8838) [datasets] Added 'test' split support for Places365 dataset (#8928) [datasets] Reduce output log on MNIST (#8865) [ops] Perf: greatly speed-up NMS on CUDA when num_boxes is high (#8766, #8925) [ops] Add roi_align nondeterministic support for XPU (#8931) [all] Improvements on input checks and error messages (#8959, #8994, #8944, #8995, #8993, #8866, #8882, #8851, #8844, #8991) [build] Various build improvements / platforms support (#8913, #8933, #8936, #8792) [docs] Various documentation improvements (#8843, #8860, #9014, #9015, #8932) [misc] Other non-user-facing changes (#8872, #8982, #8976, #8935, #8977, #8978, #8963, #8975, #8974, #8950, #8970, #8924, #8964, #8996, #8920, #8873, #8876, #8885, #8890, #8901, #8999, #8998, #8973, #8897, #9007, #8852)

Contributors

We're grateful for our community, which helps us improve torchvision by submitting issues and PRs, and providing feedback and suggestions. The following persons have contributed patches for this release:

Aditya Kamath, Alexandre Ghelfi, PhD, Alfredo Tupone, amdfaa, Andrey Talman, Antoine Simoulin, Aurélien Geron, bjarzemb, deekay42, Frost Mitchell, frost-intel , GdoongMathew, Hangxing Wei, Huy Do, Nicolas Hug, Nikita Shulga, Noopur, Ruben, tvukovic-amd, Wenchen Li, Wieland Morgenstern , Yichen Yan, Yonghye Kwon, Zain Rizvi

Torchvision 0.21 release

Highlights

Image decoding

Torchvision continues to improve its image decoding capabilities. For this version, we added support for HEIC and AVIF image formats. Things are a bit different this time: to enable it, you'll need to pip install torchvision-extra-decoders, and the decoders are available in torchvision as torchvision.io.decode_heic() and torchvision.io.decode_avif(). This is still experimental / BETA, so let us know if you encounter any issue.

Read more in our docs!

Detailed changes

New Features

... (truncated)

Commits

• 9eb57cd [Cherry-pick for 0.22] Put back docs of decode_png (#9016)
• 2ddb698 [Cherry-pick for 0.22 release] Remove stanford cars download instructions (#9...
• fb8cdf8 0.22 Cherry-picks continued (#9004)
• d434a1e Revert rotated bboxes (#9000)
• b1e9dfc 0.22 Cherry-picks (#8983)
• 8dcfb1c [Release only] Use Release 2.7 instead of main for CI jobs (#8969)
• 697340a [release-only] Update version.txt for version .22 (#8968)
• 124dfa4 Remove quiet option from pre_build_script. Install libjpeg-turbo and ffmpeg i...
• dcd1e42 Fix RandomResizedCrop scale & ratio argument. (#8944)
• 05decc3 feats: add loader in classification task datasets. (#8939)
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