Update dependency torchvision to v0.19.1 #27
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This PR contains the following updates:
==0.17.1
->==0.19.1
Release Notes
pytorch/vision (torchvision)
v0.19.1
Compare Source
v0.19.0
: Torchvision 0.19 releaseCompare Source
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)
, andtorchvision.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 tomax_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
indraw_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 tomax_size
(#8459)[transforms] Add
min_area
parameter toSanitizeBoundingBox
(#7735)[transforms] Make
adjust_hue()
work withnumpy 2.0
(#8463)[transforms] Enable one-hot-encoded labels in
MixUp
andCutMix
(#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
: acceptBytesIO
objects onpyav
backend (#8442)[io] Add compatibility with FFMPEG 7.0 (#8408)
[datasets] Add extra to install
gdown
(#8430)[datasets] Support encoded
RLE
format in forCOCO
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 deterministicroi_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 ReleaseCompare Source
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 ReleaseCompare Source
BC-Breaking changes
[datasets]
gdown
is now a required dependency for downloading datasets that are on Google Drive. This change was actually introduced in0.17.1
(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 whennum_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
inMaxViT
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 toImageFolder
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
withpyav
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 todraw_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 ReleaseCompare Source
This is a patch release, which is compatible with PyTorch 2.2.2. There are no new features added.
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