Skip to main content

torchvision

https://travis-ci.org/pytorch/vision.svg?branch=master https://codecov.io/gh/pytorch/vision/branch/master/graph/badge.svg https://pepy.tech/badge/torchvision https://img.shields.io/badge/dynamic/json.svg?label=docs&url=https%3A%2F%2Fpypi.org%2Fpypi%2Ftorchvision%2Fjson&query=%24.info.version&colorB=brightgreen&prefix=v

The torchvision package consists of popular datasets, model architectures, and common image transformations for computer vision.

Installation

TorchVision requires PyTorch 1.1 or newer.

Anaconda:

conda install torchvision -c pytorch

pip:

pip install torchvision

From source:

python setup.py install
# or, for OSX
# MACOSX_DEPLOYMENT_TARGET=10.9 CC=clang CXX=clang++ python setup.py install

By default, GPU support is built if CUDA is found and torch.cuda.is_available() is true. It’s possible to force building GPU support by setting FORCE_CUDA=1 environment variable, which is useful when building a docker image.

Image Backend

Torchvision currently supports the following image backends:

  • Pillow (default)

  • Pillow-SIMD - a much faster drop-in replacement for Pillow with SIMD. If installed will be used as the default.

  • accimage - if installed can be activated by calling torchvision.set_image_backend('accimage')

C++ API

TorchVision also offers a C++ API that contains C++ equivalent of python models.

Installation From source:

mkdir build
cd build
cmake ..
make
make install

Documentation

You can find the API documentation on the pytorch website: http://pytorch.org/docs/master/torchvision/

Contributing

We appreciate all contributions. If you are planning to contribute back bug-fixes, please do so without any further discussion. If you plan to contribute new features, utility functions or extensions, please first open an issue and discuss the feature with us.

Metadata

Release files for torchvision 0.4.1.post2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distributions (wheels)

Table of built distributions (wheels) for torchvision 0.4.1.post2
File
torchvision-0.4.1.post2-cp37-cp37m-macosx_10_9_x86_64.whl CPython 3.7 CPython 3.7 pymalloc macOS 10.9+ x86-64 Details
torchvision-0.4.1.post2-cp36-cp36m-macosx_10_7_x86_64.whl CPython 3.6 CPython 3.6 pymalloc macOS 10.7+ x86-64 Details
torchvision-0.4.1.post2-cp35-cp35m-macosx_10_6_x86_64.whl CPython 3.5 CPython 3.5 pymalloc macOS 10.6+ x86-64 Details
torchvision-0.4.1.post2-cp27-cp27m-macosx_10_7_x86_64.whl CPython 2.7 CPython 2.7 pymalloc macOS 10.7+ x86-64 Details

Total release size: 2.5 MB

Release files / torchvision-0.4.1.post2-cp37-cp37m-macosx_10_9_x86_64.whl

Download URL torchvision-0.4.1.post2-cp37-cp37m-macosx_10_9_x86_64.whl
Size 631.9 kB
Tags CPython 3.7 CPython 3.7 pymalloc macOS 10.9+ x86-64
SHA-256 checksum
How to use checksums
5db49b6ec5a30e270e7eca176bf8c52b10f9356fda2f798610f8822392dabfd4
BLAKE2b-256 checksum
How to use checksums
4b7541226e77b841258fff7b05404d709b5f67795ba601e09345d97db864b9d2
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.7.4

Release files / torchvision-0.4.1.post2-cp36-cp36m-macosx_10_7_x86_64.whl

Download URL torchvision-0.4.1.post2-cp36-cp36m-macosx_10_7_x86_64.whl
Size 631.9 kB
Tags CPython 3.6 CPython 3.6 pymalloc macOS 10.7+ x86-64
SHA-256 checksum
How to use checksums
ee8ab78e9f76a61d6a15c2829e0c26cdd5150b1b068806cc3a48af9d9f6b3f32
BLAKE2b-256 checksum
How to use checksums
6bdda1f9ba88252ebd44d69ad758bdd552529afa62e64ee1636f7592e785843a
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.7.4

Release files / torchvision-0.4.1.post2-cp35-cp35m-macosx_10_6_x86_64.whl

Download URL torchvision-0.4.1.post2-cp35-cp35m-macosx_10_6_x86_64.whl
Size 631.9 kB
Tags CPython 3.5 CPython 3.5 pymalloc macOS 10.6+ x86-64
SHA-256 checksum
How to use checksums
9421e453f0cfeefc62aa02d60df6b8681f21da0e4fc5583439de1ae97b1adab8
BLAKE2b-256 checksum
How to use checksums
880c659c4acb007ec77ff7d36646df52399e0f433afc3ae0b5e03618063e0ea8
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.7.4

Release files / torchvision-0.4.1.post2-cp27-cp27m-macosx_10_7_x86_64.whl

Download URL torchvision-0.4.1.post2-cp27-cp27m-macosx_10_7_x86_64.whl
Size 633.3 kB
Tags CPython 2.7 CPython 2.7 pymalloc macOS 10.7+ x86-64
SHA-256 checksum
How to use checksums
fdc1800c4e7e2d62e73a92101b68fddd1f41bb1f5d6d175a260b4f8e299e11cd
BLAKE2b-256 checksum
How to use checksums
cf1349ad91d2fe8e86f718a1681400c217a0eb70d88041554a2285f19e565871
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.7.4

Security for torchvision 0.4.1.post2

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

Release history Release notifications | RSS feed

This release

0.4.1.post2 This release

4 release files No provenance

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page