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-0.11.0b20220810.tar.gz (1.0 MB view details)

Uploaded Source

Built Distribution

gluoncv-0.11.0b20220810-py2.py3-none-any.whl (1.3 MB view details)

Uploaded Python 2 Python 3

File details

Details for the file gluoncv-0.11.0b20220810.tar.gz.

File metadata

  • Download URL: gluoncv-0.11.0b20220810.tar.gz
  • Upload date:
  • Size: 1.0 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.3 readme-renderer/34.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.11 tqdm/4.64.0 importlib-metadata/4.8.3 keyring/23.4.1 rfc3986/1.5.0 colorama/0.4.5 CPython/3.6.8

File hashes

Hashes for gluoncv-0.11.0b20220810.tar.gz
Algorithm Hash digest
SHA256 056fb057a867f375fa6bf2b2063f2b1650a1496dfdaeff7e6c5cc6ee6423f4a7
MD5 1c87a94d8b822ed116033ec3aa094bb5
BLAKE2b-256 1e1aa160322301aae789280e9c7dc8fb5bafd28f29393c799ceb813a9ff2ae56

See more details on using hashes here.

File details

Details for the file gluoncv-0.11.0b20220810-py2.py3-none-any.whl.

File metadata

  • Download URL: gluoncv-0.11.0b20220810-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/1.8.3 readme-renderer/34.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.11 tqdm/4.64.0 importlib-metadata/4.8.3 keyring/23.4.1 rfc3986/1.5.0 colorama/0.4.5 CPython/3.6.8

File hashes

Hashes for gluoncv-0.11.0b20220810-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 45e5365ec4517e10f6e26bba273072a10d845f0e1697698fdb1cb8aed75fe3f5
MD5 3a46ed252ac7caa9da8bc7d50cba86ae
BLAKE2b-256 4ecb121da7d82f712e97362542d03de46148eec0e07117831950aded62eebddb

See more details on using hashes here.

Supported by

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