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-0.2.0b20180527.tar.gz (74.6 kB view details)

Uploaded Source

Built Distribution

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

gluoncv-0.2.0b20180527-py2.py3-none-any.whl (106.5 kB view details)

Uploaded Python 2Python 3

File details

Details for the file gluoncv-0.2.0b20180527.tar.gz.

File metadata

File hashes

Hashes for gluoncv-0.2.0b20180527.tar.gz
Algorithm Hash digest
SHA256 d1622f0a584798e8533fca1c88f3c40b288ac27ff0560a47793052568633eff0
MD5 2cde80d152f9f4debf6bc6af0a188343
BLAKE2b-256 3720f171cd1c6590c7f4cd6cae7fee9477b548c0a824bbcca529e1e8af58b90b

See more details on using hashes here.

File details

Details for the file gluoncv-0.2.0b20180527-py2.py3-none-any.whl.

File metadata

File hashes

Hashes for gluoncv-0.2.0b20180527-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 61b392ead35122ca40c6f6637a893b38e5f6591dbf0c98ec1004777e46526d62
MD5 961d5d094cec4bb55405b7e62384f1ae
BLAKE2b-256 1659a6c4c55338f689bac5012cce8cd757972033c8d0b56f7dcbf81ad4af0705

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