Torchvision

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Highlights

Encoding / Decoding images

Torchvision is further extending its encoding/decoding capabilities. For this version, **we added a WEBP decoder**, and a **batch JPEG decoder on CUDA GPUs**, which can lead to 10X speed-ups over CPU decoding.

We have also improved the UX of our decoding APIs to be more user-friendly. The main entry point is now `torchvision.io.decode_image()`, and it can take as input either a path (as str or `pathlib.Path`), or a tensor containing the raw encoded data.

[Read more on the docs!](https://pytorch.org/vision/stable/io.html)

We also added support for HEIC and AVIF decoding, but these are currently only available when building from source. We are working on making those available directly in the upcoming releases. Stay tuned!


Detailed changes


Bug Fixes

[datasets] Update URL of SBDataset train_noval (8551)
[datasets] EuroSAT: fix SSL certificate issues (8563)
[io] Check average_rate availability in video reader (8548)


New Features

[io] Add batch JPEG GPU decoding (`decode_jpeg()`) (8496)
[io] Add WEBP image decoder: `decode_image()`, `decode_webp()` (8527, 8612, 8610)
[io] Add HEIC and AVIF decoders, only available when building from source (8597, 8596, 8647, 8613, 8621)


Improvements

[io] Add support for decoding 16bits png (8524)
[io] Allow decoding functions to accept the mode parameter as a string (8627)
[io] Allow `decode_image()` to support paths (8624)
[io] Automatically send video to CPU in io.write_video (8537)
[datasets] Better progress bar for file downloading (8556)
[datasets] Add Path type annotation for ImageFolder (8526)
[ops] Register nms and roi_align Autocast policy for PyTorch Intel GPU backend (8541)
[transforms] Use Sequence for parameters type checking in `transforms.RandomErase` (8615)
[transforms] Support `v2.functional.gaussian_blur` backprop (8486)
[transforms] Expose `transforms.v2` utils for writing custom transforms. (8670)
[utils] Fix f-string in color error message (8639)
[packaging] Revamped and improved debuggability of setup.py build (8535, 8581, 8581, 8582, 8590, 8533, 8528, 8659)
[Documentation] Various documentation improvements (8605, 8611, 8506, 8507, 8539, 8512, 8513, 8583, 8633)
[tests] Various tests improvements (8580, 8553, 8523, 8617, 8518, 8579, 8558, 8617, 8641)
[code quality] Various code quality improvements (8552, 8555, 8516, 8526, 8602, 8615, 8639, 8532)
[ci] 8562, 8644, 8592, 8542, 8594, 8530, 8656


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, AJS Payne, Andreas Floros, Andrey Talman, Bhavay Malhotra, Brizar, deekay42, Ehsan, Feng Yuan, Joseph Macaranas, Martin, Masahiro Hiramori, Nicolas Hug, Nikita Shulga , Sergii Dymchenko, Stefan Baumann, venkatram-dev, Wang, Chuanqi

This is a patch release, which is compatible with [PyTorch 2.4.1](https://github.com/pytorch/pytorch/releases/tag/v2.4.1). There are no new features added.

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!](https://pytorch.org/vision/stable/io.html)

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!](https://pytorch.org/vision/stable/generated/torchvision.transforms.v2.Resize.html#torchvision.transforms.v2.Resize)

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

This is a patch release, which is compatible with [PyTorch 2.3.1](https://github.com/pytorch/pytorch/releases/tag/v2.3.1). There are no new features added.

BC-Breaking changes

[datasets] [`gdown`](https://github.com/wkentaro/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](https://github.com/pytorch/vision/issues/7545#issuecomment-1631441616) 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.