Skip to main content

Gluon CV Toolkit

Project description

GluonCV provides implementations of the state-of-the-art (SOTA) deep learning models in computer vision.

It is designed for engineers, researchers, and students to fast prototype products and research ideas based on these models.

Installation

To install, use:

pip install gluoncv mxnet>=1.6.0 --upgrade
# for installing gluoncv with all dependencies
pip install gluoncv[full] mxnet>=1.6.0 --upgrade

To enable different hardware supports such as GPUs, check out mxnet variants.

For example, you can install cuda-11.0 supported mxnet alongside gluoncv:

pip install gluoncv mxnet-cu110>=1.6.0 --upgrade

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

gluoncv-0.11.0b20220221.tar.gz (1.0 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

gluoncv-0.11.0b20220221-py2.py3-none-any.whl (1.3 MB view details)

Uploaded Python 2Python 3

File details

Details for the file gluoncv-0.11.0b20220221.tar.gz.

File metadata

  • Download URL: gluoncv-0.11.0b20220221.tar.gz
  • Upload date:
  • Size: 1.0 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.62.3 importlib-metadata/4.8.3 keyring/23.4.1 rfc3986/1.5.0 colorama/0.4.4 CPython/3.6.8

File hashes

Hashes for gluoncv-0.11.0b20220221.tar.gz
Algorithm Hash digest
SHA256 e0d9f089be1681056da402a624262b28676cb3a2e2a35d3d7c8a37f46e59d7e5
MD5 7cfaf7a32f59e65601b6652005ed632b
BLAKE2b-256 a58061598d704dbb7c2f34b2176cacaa907f039899577d39ab545e58fd2830a1

See more details on using hashes here.

File details

Details for the file gluoncv-0.11.0b20220221-py2.py3-none-any.whl.

File metadata

  • Download URL: gluoncv-0.11.0b20220221-py2.py3-none-any.whl
  • Upload date:
  • Size: 1.3 MB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.62.3 importlib-metadata/4.8.3 keyring/23.4.1 rfc3986/1.5.0 colorama/0.4.4 CPython/3.6.8

File hashes

Hashes for gluoncv-0.11.0b20220221-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 93a9c7ffac55e5b94f2a2aa3a9ff143abedb8fd97a732ae442c6f9ff0d33d2e3
MD5 324d5eafbc350726814c21dab19f6e30
BLAKE2b-256 3e6d0c3d788d36398d78a28e9a95d595935ab7902b670d2db861f72691533449

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page