Update dependency torchvision to >=0.24.1,<0.25.0

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This PR contains the following updates:

Package	Change	Age	Confidence
torchvision	>=0.20.0,<0.21.0 -> >=0.24.1,<0.25.0

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Release Notes

pytorch/vision (torchvision)

v0.24.1: TorchVision 0.24.1 Release

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This is a patch release, which is compatible with PyTorch 2.9.1. There are no new features added.

v0.24.0: Torchvision 0.24 release

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Improving KeyPoints and Rotated boxes support!

We are releasing a tutorial on how to use KeyPoint transformations in our Transforms on KeyPoints with a preview below!

[!NOTE]
These features are still in BETA status. The API are unlikely to change, but we may have some rough edges and we may make some slight bug fixes in future releases. Please let us know if you encounter any issue!

Detailed changes

Improvements

[ops] Improve efficiency of the box_area and box_iou functions by eliminating the intermediate to "xyxy" conversion (#​8992)
[ops] Update box operations to support arbitrary batch dimensions (#​9058)
[utils] Add control for the background color of label text boxes (#​9204)
[transforms] Add support for uint8 image format to the GaussianNoise transform (#​9169)
[transforms] Accelerate the resize transform on machines with AVX512 (#​9190)
[transforms] Better error handling in RandomApply for empty list of transforms (#​9130)
[documentation] New tutorial for KeyPoints transforms (#​9209)
[documentation] Various documentation improvements (#​9186, #​9180, #​9172)
[code quality] Various code quality improvements (#​9193, #​9161, #​9201, #​9218, #​9160)

Bug Fixes and deprecations

[transforms] Fix output of some geometric transforms for rotated boxes (#​9181, #​9175)
[transforms] Fix clamping for key points and add sanitization feature (#​9236, #​9235)
[datasets] Update download links to official repo for the Caltech-101 & 256 datasets (#​9205)
[ops] Raise error in drop_block[2,3]d by enforcing odd-sized block sizes (#​9157)
[io] Removed deprecated video_reader video decoding backend. (#​9208)

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: @​alperenunlu, @​AndreiMoraru123, @​atalman, @​AntoineSimoulin, @​5had3z, @​dcasbol, @​GdoongMathew, @​hrsvrn, @​JonasKlotz, @​zklaus, @​NicolasHug, @​rdong8, @​scotts, @​get9, @​diaz-esparza, @​ZainRizvi, @​Callidior, and @​pytorch/xla-devs

v0.23.0: Torchvision 0.23 release

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Highlight - Transforming KeyPoints and Rotated boxes!

📦 This release is introducing two highly popular feature requests: Transforms support for KeyPoints and Rotated Bounding Boxes!

• Rotated Bounding Boxes provide a tighter fit and alignment with rotated and elongated objects, which improves the localization, reduces overlap in densely packed images, and improves isolation of objects in crowded scenes.
• KeyPoints offer a robust and accurate way to identify and locate specific points of interest within an image or video frame. These features aim at improving developer experience to implement use cases, including detecting & tracking objects, estimating pose, analyzing facial expressions, and creating augmented reality experiences.

We illustrated the use of Rotated Bounding Boxes below. You can expect keypoints and rotated boxes to work with all existing torchvision transforms in torchvision.transforms.v2. You can find some examples on how to use those transformations in our Transforms on Rotated Bounding Boxes tutorials.

[!NOTE]
These features are released in BETA status. The API are unlikely to change, but we may have some rough edges and we may make some slight bug fixes in future releases. Please let us know if you encounter any issue!

Detailed changes

New Features

[transforms] Added support for BoundingBoxes formats and transforms (#​9104, #​9084, #​9095, #​9138)
[transforms] Added the KeyPoints to TVTensor and support for transforms (#​8817)

Improvements

[utils] Add label background to draw_bounding_boxes (#​9018)
[MPS] Add deformable conv2d kernel support on MPS (#​9017, #​9115)
[documentation] Various documentation improvements (#​9063, #​9119, #​9083, #​9105, #​9106, #​9145)
[code-quality] Bunch of code quality improvements (#​9087, #​9093, #​8814, #​9035, #​9120, #​9080, #​9027, #​9062, #​9117, #​9024, #​9032)

Bug Fixes

[datasets] Fix COCO dataset to avoid issue when copying the dataset results (#​9107)
[datasets] Raise error when download=True for LFW dataset, which is not available for download anymore #​9040)
[tv_tensors] Add error message when setting 1D tensor ToImage() (#​9114)
[io] Warn when webp is asked to decode into grayscale (#​9101)

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: @​AlannaBurke, @​Alexandre-SCHOEPP, @​atalman, @​AntoineSimoulin, @​BoyuanFeng, @​cyyever, @​elmuz, @​emmanuel-ferdman, @​hmk114, @​Isalia20, @​NicolasHug, @​malfet, @​chengolivia, @​RhutvikH, @​hvaara, @​scotts, @​alinpahontu2912, @​tsahiasher, and @​youcefouadjer.

v0.22.1: TorchVision 0.22.1 Release

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Key info

⚠️ We are updating the areas that TorchVision will be prioritizing in the future. Please take a look at #​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.

This is a patch release, which is compatible with PyTorch 2.7.1. There are no new features added.

v0.22.0: Torchvision 0.22 release

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Key info

⚠️ We are updating the areas that TorchVision will be prioritizing in the future. Please take a look at #​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

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Configuration

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Documentation

Find out how to configure dependency updates in MintMaker documentation or see all available configuration options in Renovate documentation.

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⚠️ Artifact update problem

Renovate failed to update an artifact related to this branch. You probably do not want to merge this PR as-is.

♻ Renovate will retry this branch, including artifacts, only when one of the following happens:

• any of the package files in this branch needs updating, or
• the branch becomes conflicted, or
• you click the rebase/retry checkbox if found above, or
• you rename this PR's title to start with "rebase!" to trigger it manually

The artifact failure details are included below:

File name: uv.lock

Command failed: uv lock --upgrade-package torchvision
Using CPython 3.12.12 interpreter at: /usr/bin/python3
  × No solution found when resolving dependencies for split (markers:
  │ python_full_version == '3.12.*' and platform_machine == 'aarch64' and
  │ platform_python_implementation != 'CPython' and sys_platform == 'linux'):
  ╰─▶ Because torchvision>=0.24.1 depends on torch==2.9.1 and only the
      following versions of torchvision are available:
          torchvision<=0.24.1
          torchvision==0.24.1+cpu
          torchvision==0.24.1+d801a34
      we can conclude that torchvision>=0.24.1 depends on torch==2.9.1.
      And because your project depends on torch>=2.5.0,<2.6.0 and
      torchvision>=0.24.1, we can conclude that your project's requirements
      are unsatisfiable.

      hint: The resolution failed for an environment that is not the current
      one, consider limiting the environments with `tool.uv.environments`.

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