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-0.11.0b20220407.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-0.11.0b20220407-py2.py3-none-any.whl (1.3 MB view details)

Uploaded Python 2Python 3

File details

Details for the file gluoncv-0.11.0b20220407.tar.gz.

File metadata

  • Download URL: gluoncv-0.11.0b20220407.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/4.64.0 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-0.11.0b20220407.tar.gz
Algorithm Hash digest
SHA256 e1e0ebedeab63428506147cf4d92c2f679dbba673885e856172ca4efd4e372e9
MD5 95200a073bda223e3ab60e8ff7e04c60
BLAKE2b-256 28d1ec4c8621a757df76e0511728fcbbd6288f1e14097b590a5ddae4d370689b

See more details on using hashes here.

File details

Details for the file gluoncv-0.11.0b20220407-py2.py3-none-any.whl.

File metadata

  • Download URL: gluoncv-0.11.0b20220407-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/4.64.0 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-0.11.0b20220407-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 681092e9411d3e74930731aaa56ffadc2ff00d7a4a676596cd2ed44b3c2df8b3
MD5 855b748a260ed918acbba2aea01f05cf
BLAKE2b-256 abaf381e786e4c933b8ccf2b43aa2a5664aef44747efee96f83c1e563c713f6a

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