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-0.11.0b20220402.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-0.11.0b20220402-py2.py3-none-any.whl (1.3 MB view details)

Uploaded Python 2Python 3

File details

Details for the file gluoncv-0.11.0b20220402.tar.gz.

File metadata

  • Download URL: gluoncv-0.11.0b20220402.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/34.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.9 tqdm/4.63.1 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-0.11.0b20220402.tar.gz
Algorithm Hash digest
SHA256 bbbbf745ac04137af09d47d3fe9d67f5cdd75811a8f783f058b42440ff1c1ae3
MD5 846660795fec67175a55404b8e8a13c8
BLAKE2b-256 2e305d427029500db6ceb08d863309ec17e4148f4a5834b2dfced08156d479da

See more details on using hashes here.

File details

Details for the file gluoncv-0.11.0b20220402-py2.py3-none-any.whl.

File metadata

  • Download URL: gluoncv-0.11.0b20220402-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/34.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.9 tqdm/4.63.1 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-0.11.0b20220402-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 1d41f2974c1880343ecd205f11e54b23efa6c327f3819b8c445f76eff39de1a4
MD5 69b77e377b3d058a4d651d6f6bbbaf45
BLAKE2b-256 2f86997d88c77bf03a4ac9c5a4af3b592d49038a9efd779397590b4645d6c69a

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