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-0.2.0b20180612.tar.gz (75.0 kB view details)

Uploaded Source

Built Distribution

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

gluoncv-0.2.0b20180612-py2.py3-none-any.whl (107.0 kB view details)

Uploaded Python 2Python 3

File details

Details for the file gluoncv-0.2.0b20180612.tar.gz.

File metadata

File hashes

Hashes for gluoncv-0.2.0b20180612.tar.gz
Algorithm Hash digest
SHA256 bf39fa1481df1804f6099744b59c5d56c4bacf2a3d52abdbb1fe2fb0b7fecc65
MD5 413fce240ad857cf37e77d0139c4abff
BLAKE2b-256 84d49fbde24fc62f26431ae7f682438ac1bd97a21eb030a7e027202ddc110032

See more details on using hashes here.

File details

Details for the file gluoncv-0.2.0b20180612-py2.py3-none-any.whl.

File metadata

File hashes

Hashes for gluoncv-0.2.0b20180612-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 c0b4d4fd97f5f9799642c1f7c01a8c3171ae2f5c34ace3267afdac82ece5475a
MD5 742bb3485c9711e43968c66e4042cdea
BLAKE2b-256 8a650202c04e51a25995d874ccd787b7b76bf73afa9ef7b1131457263755ff2c

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