chore(deps): update dependency torchvision to v0.18.1

[renovate]

This PR contains the following updates:

Package	Change	Age	Adoption	Passing	Confidence
torchvision	==0.16.0 -> ==0.18.1

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Release Notes

pytorch/vision (torchvision)

v0.18.1: TorchVision 0.18.1 Release

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This is a patch release, which is compatible with PyTorch 2.3.1. There are no new features added.

v0.18.0: TorchVision 0.18 Release

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BC-Breaking changes

[datasets] gdown is now a required dependency for downloading datasets that are on Google Drive. This change was actually introduced in 0.17.1 (repeated here for visibility) (#​8237)
[datasets] The StanfordCars dataset isn’t available for download anymore. Please follow these instructions to manually download it (#​8309, #​8324)
[transforms] to_grayscale and corresponding transform now always return 3 channels when num_output_channels=3 (#​8229)

Bug Fixes

[datasets] Fix download URL of EMNIST dataset (#​8350)
[datasets] Fix root path expansion in Kitti dataset (#​8164)
[models] Fix default momentum value of BatchNorm2d in MaxViT from 0.99 to 0.01 (#​8312)
[reference scripts] Fix CutMix and MixUp arguments (#​8287)
[MPS, build] Link essential libraries in cmake (#​8230)
[build] Fix build with ffmpeg 6.0 (#​8096)

New Features

[transforms] New GrayscaleToRgb transform (#​8247)
[transforms] New JPEG augmentation transform (#​8316)

Improvements

[datasets, io] Added pathlib.Path support to datasets and io utilities. (#​8196, #​8200, #​8314, #​8321)
[datasets] Added allow_empty parameter to ImageFolder and related utils to support empty classes during image discovery (#​8311)
[datasets] Raise proper error in CocoDetection when a slice is passed (#​8227)
[io] Added support for EXIF orientation in JPEG and PNG decoders (#​8303, #​8279, #​8342, #​8302)
[io] Avoiding unnecessary copies on io.VideoReader with pyav backend (#​8173)
[transforms] Allow SanitizeBoundingBoxes to sanitize more than labels (#​8319)
[transforms] Add sanitize_bounding_boxes kernel/functional (#​8308)
[transforms] Make perspective more numerically stable (#​8249)
[transforms] Allow 2D numpy arrays as inputs for to_image (#​8256)
[transforms] Speed-up rotate for 90, 180, 270 degrees (#​8295)
[transforms] Enabled torch compile on affine transform (#​8218)
[transforms] Avoid some graph breaks in transforms (#​8171)
[utils] Add float support to draw_keypoints (#​8276)
[utils] Add visibility parameter to draw_keypoints (#​8225)
[utils] Add float support to draw_segmentation_masks (#​8150)
[utils] Better show overlap section of masks in draw_segmentation_masks (#​8213)
[Docs] Various documentation improvements (#​8341, #​8332, #​8198, #​8318, #​8202, #​8246, #​8208, #​8231, #​8300, #​8197)
[code quality] Various code quality improvements (#​8273, #​8335, #​8234, #​8345, #​8334, #​8119, #​8251, #​8329, #​8217, #​8180, #​8105, #​8280, #​8161, #​8313)

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:

Adam Dangoor Ahmad Sharif , ahmadsharif1, Andrey Talman, Anner, anthony-cabacungan, Arun Sathiya, Brizar, Brizar , cdzhan, Danylo Baibak, Huy Do, Ivan Magazinnik, JavaZero, Johan Edstedt, Li-Huai (Allan) Lin, Mantas, Mark Harfouche, Mithra, Nicolas Hug, Nicolas Hug , nihui, Philip Meier, Philip Meier , RazaProdigy , Richard Barnes , Riza Velioglu, sam-watts, Santiago Castro, Sergii Dymchenko, Syed Raza, talcs, Thien Tran, Thien Tran , TilmannR, Tobias Fischer, vfdev, vfdev , Zhu Lin Ch'ng, Zoltán Böszörményi.

v0.17.2: TorchVision 0.17.2 Release

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This is a patch release, which is compatible with PyTorch 2.2.2. There are no new features added.

v0.17.1: TorchVision 0.17.1 Release

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This is a patch release, which is compatible with PyTorch 2.2.1.

Bug Fixes

• Add gdown dependency to support downloading datasets from Google Drive (https://github.com/pytorch/vision/pull/8237)
• Fix silent correctness with convert_bounding_box_format when passing string parameters (https://github.com/pytorch/vision/issues/8258)

v0.17.0: TorchVision 0.17 Release

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Highlights

The V2 transforms are now stable!

The torchvision.transforms.v2 namespace was still in BETA stage until now. It is now stable! Whether you’re new to Torchvision transforms, or you’re already experienced with them, we encourage you to start with Getting started with transforms v2 in order to learn more about what can be done with the new v2 transforms.

Browse our main docs for general information and performance tips. The available transforms and functionals are listed in the API reference. Additional information and tutorials can also be found in our example gallery, e.g. Transforms v2: End-to-end object detection/segmentation example or How to write your own v2 transforms.

Towards torch.compile() support

We are progressively adding support for torch.compile() to torchvision interfaces, reducing graph breaks and allowing dynamic shape.

The torchvision ops (nms, [ps_]roi_align, [ps_]roi_pool and deform_conv_2d) are now compatible with torch.compile and dynamic shapes.

On the transforms side, the majority of low-level kernels (like resize_image() or crop_image()) should compile properly without graph breaks and with dynamic shapes. We are still addressing the remaining edge-cases, moving up towards full functional support and classes, and you should expect more progress on that front with the next release.

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Detailed Changes

Breaking changes / Finalizing deprecations

• [transforms] We changed the default of the antialias parameter from None to True, in all transforms that perform resizing. This change of default has been communicated in previous versions, and should drastically reduce the amount of bugs/surprises as it aligns the tensor backend with the PIL backend. Simply put: from now on, antialias is always applied when resizing (with bilinear or bicubic modes), whether you're using tensors or PIL images. This change only affects the tensor backend, as PIL always applies antialias anyway. (#​7949)
• [transforms] We removed the torchvision.transforms.functional_tensor.py and torchvision.transforms.functional_pil.py modules, as these had been deprecated for a while. Use the public functionals from torchvision.transforms.v2.functional instead. (#​7953)
• [video] Remove deprecated path parameter to VideoReader and made src mandatory (#​8125)
• [transforms] to_pil_image now provides the same output for equivalent numpy arrays and tensor inputs (#​8097)

Bug Fixes

[datasets] Fix root path expansion in datasets.Kitti (#​8165)
[transforms] allow sequence fill for v2 AA scripted (#​7919)
[reference scripts] Fix quantized references (#​8073)
[reference scripts] Fix IoUs reported in segmentation references (#​7916)

New Features

[datasets] add Imagenette dataset (#​8139)

Improvements

[transforms] The v2 transforms are now officially stable and out of BETA stage (#​8111)
[ops] The ops ([ps_]roi_align, ps_[roi_pool], deform_conv_2d) are now compatible with torch.compile and dynamic shapes (#​8061, #​8049, #​8062, #​8063, #​7942, #​7944)
[models] Allow custom atrous_rates for deeplabv3_mobilenet_v3_large (#​8019)
[transforms] allow float fill for integer images in F.pad (#​7950)
[transforms] allow len 1 sequences for fill with PIL (#​7928)
[transforms] allow size to be generic Sequence in Resize (#​7999)
[transforms] Making root parameter optional for Vision Dataset (#​8124)
[transforms] Added support for tv tensors in torch compile for func ops (#​8110)
[transforms] Reduced number of graphs for compiled resize (#​8108)
[misc] Various fixes for S390x support (#​8149)
[Docs] Various Documentation enhancements (#​8007, #​8014, #​7940, #​7989, #​7993, #​8114, #​8117, #​8121, #​7978, #​8002, #​7957, #​7907, #​8000, #​7963)
[Tests] Various test enhancements (#​8032, #​7927, #​7933, #​7934, #​7935, #​7939, #​7946, #​7943, #​7968, #​7967, #​8033, #​7975, #​7954, #​8001, #​7962, #​8003, #​8011, #​8012, #​8013, #​8023, #​7973, #​7970, #​7976, #​8037, #​8052, #​7982, #​8145, #​8148, #​8144, #​8058, #​8057, #​7961, #​8132, #​8133, #​8160)
[Code Quality] (#​8077, #​8070, #​8004, #​8113,

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:

Aleksei Nikiforov. Alex Wei, Andrey Talman, Chunyuan WU, CptCaptain, Edward Z. Yang, Gu Wang, Haochen Yu, Huy Do, Jeff Daily, Josh Levy-Kramer, moto, Nicolas Hug, NVS Abhilash, Omkar Salpekar, Philip Meier, Sergii Dymchenko, Siddharth Singh, Thiago Crepaldi, Thomas Fritz, TilmannR, vfdev-5, Zeeshan Khan Suri.

v0.16.2: TorchVision 0.16.2 Release

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This is a patch release, which is compatible with PyTorch 2.1.2. There are no new features added.

v0.16.1: TorchVision 0.16.1 Release

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This is a minor release that only contains bug-fixes

Bug Fixes

• [models] Fix download of efficientnet weights (#​8036)
• [transforms] Fix v2 transforms in spawn multi-processing context (#​8067)

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  Misses        925      925           
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