Bump torchvision from 0.18.1 to 0.19.1

[dependabot[bot]]

Bumps torchvision from 0.18.1 to 0.19.1.

Release notes

Sourced from torchvision's releases.

TorchVision 0.19.1 Release

This is a patch release, which is compatible with PyTorch 2.4.1. There are no new features added.

Torchvision 0.19 release

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)

... (truncated)

Commits

• 6194369 [cherry-pick] Restrict ffmpeg to 4.2+.X versions to resolve linux conda build...
• 5bada1f Cherry-Pick Pin setuptools to 72.1.0 (#8606)
• 99d97fa Update version.txt to 0.19.1
• 48b1edf Remove prototype area for 0.19 (#8491)
• f44f20c Use @​release/2.4 instead of @​main for CI jobs (#8490)
• 143d078 Adding GPU acceleration to encode_jpeg (#8391)
• f96c42f Re-enable vision MPS builds (#8485)
• f1bcbd3 [FBcode->GH] Fix using namespace in pytorch/vision/torchvision/csrc/io/video/...
• 27764a1 Skip flaky earth gif test on OSS CI (#8480)
• b09b3f6 Remove unused dynamo import (#8451)
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