Skip to main content

MXNet 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>=1.2.0

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

For example, you can install cuda-9.0 supported mxnet alongside gluoncv:

pip install gluoncv mxnet-cu90>=1.2.0

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-0.3.0b20180913.tar.gz (145.5 kB view details)

Uploaded Source

Built Distribution

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

gluoncv-0.3.0b20180913-py2.py3-none-any.whl (205.2 kB view details)

Uploaded Python 2Python 3

File details

Details for the file gluoncv-0.3.0b20180913.tar.gz.

File metadata

  • Download URL: gluoncv-0.3.0b20180913.tar.gz
  • Upload date:
  • Size: 145.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/40.2.0 requests-toolbelt/0.8.0 tqdm/4.26.0 CPython/3.5.3

File hashes

Hashes for gluoncv-0.3.0b20180913.tar.gz
Algorithm Hash digest
SHA256 12f3eca70f56732357b96d6498b04ba578a3816f31c5d9cf2998945a9c035573
MD5 b87262b5d3fb59d2e2bc3cd62a6922da
BLAKE2b-256 08dfe31ce2570498e57e213dd94a354c23cc739ef15f27f19bc368f555f4f3da

See more details on using hashes here.

File details

Details for the file gluoncv-0.3.0b20180913-py2.py3-none-any.whl.

File metadata

  • Download URL: gluoncv-0.3.0b20180913-py2.py3-none-any.whl
  • Upload date:
  • Size: 205.2 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/40.2.0 requests-toolbelt/0.8.0 tqdm/4.26.0 CPython/3.5.3

File hashes

Hashes for gluoncv-0.3.0b20180913-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 38a7a4440799f21dd01f165d6e8279e5582a5de9bd7f08ce9dda2fa03b98a513
MD5 edb39fced33de0480ec8837494b60815
BLAKE2b-256 b26529950c91f23bc544784e2bb20cbe2afe41db870453395fa6a1e80ea3b798

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