Update dependency torchvision to v0.19.1

[renovate]

This PR contains the following updates:

Package	Change	Age	Adoption	Passing	Confidence
torchvision	==0.17.1 -> ==0.19.1

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Release Notes

pytorch/vision (torchvision)

v0.19.1

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v0.19.0: Torchvision 0.19 release

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Highlights

Encoding / Decoding images

Torchvision is extending its encoding/decoding capabilities. For this version, we added a GIF decoder which is available as torchvision.io.decode_gif(raw_tensor), torchvision.io.decode_image(raw_tensor), and torchvision.io.read_image(path_to_image).

We also added support for jpeg GPU encoding in torchvision.io.encode_jpeg(). This is 10X faster than the existing CPU jpeg encoder.

Read more on the docs!

Stay tuned for more improvements coming in the next versions. We plan to improve jpeg GPU decoding, and add more image decoders (webp in particular).

Resizing according to the longest edge of an image

It is now possible to resize images by setting torchvision.transforms.v2.Resize(max_size=N): this will resize the longest edge of the image exactly to max_size, making sure the image dimension don't exceed this value. Read more on the docs!

Detailed changes

Bug Fixes

[datasets] SBDataset: Only download noval file when image_set='train_noval' (#​8475)
[datasets] Update the download url in class EMNIST (#​8350)
[io] Fix compilation error when there is no libjpeg (#​8342)
[reference scripts] Fix use of cutmix_alpha in classification training references (#​8448)
[utils] Allow K=1 in draw_keypoints (#​8439)

New Features

[io] Add decoder for GIF images (decode_gif(), decode_image(),read_image()) (#​8406, #​8419)
[transforms] Add GaussianNoise transform (#​8381)

Improvements

[transforms] Allow v2 Resize to resize longer edge exactly to max_size (#​8459)
[transforms] Add min_area parameter to SanitizeBoundingBox (#​7735)
[transforms] Make adjust_hue() work with numpy 2.0 (#​8463)
[transforms] Enable one-hot-encoded labels in MixUp and CutMix (#​8427)
[transforms] Create kernel on-device for transforms.functional.gaussian_blur (#​8426)
[io] Adding GPU acceleration to encode_jpeg (10X faster than CPU encoder) (#​8391)
[io] read_video: accept BytesIO objects on pyav backend (#​8442)
[io] Add compatibility with FFMPEG 7.0 (#​8408)
[datasets] Add extra to install gdown (#​8430)
[datasets] Support encoded RLE format in for COCO segmentations (#​8387)
[datasets] Added binary cat vs dog classification target type to Oxford pet dataset (#​8388)
[datasets] Return labels for FER2013 if possible (#​8452)
[ops] Force use of torch.compile on deterministic roi_align implementation (#​8436)
[utils] add float support to utils.draw_bounding_boxes() (#​8328)
[feature_extraction] Add concrete_args to feature extraction tracing. (#​8393)
[Docs] Various documentation improvements (#​8429, #​8467, #​8469, #​8332, #​8262, #​8341, #​8392, #​8386, #​8385, #​8411).
[Tests] Various testing improvements (#​8454, #​8418, #​8480, #​8455)
[Code quality] Various code quality improvements (#​8404, #​8402, #​8345, #​8335, #​8481, #​8334, #​8384, #​8451, #​8470, #​8413, #​8414, #​8416, #​8412)

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 J. Stewart ahmadsharif1, AJS Payne, Andrew Lingg, Andrey Talman, Anner, Antoine Broyelle, cdzhan, deekay42, drhead, Edward Z. Yang, Emin Orhan, Fangjun Kuang, G, haarisr, Huy Do, Jack Newsom, JavaZero, Mahdi Lamb, Mantas, Nicolas Hug, Nicolas Hug , nihui, Richard Barnes , Richard Zou, Richie Bendall, Robert-André Mauchin, Ross Wightman, Siddarth Ijju, vfdev

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.

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