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-0.2.0b20180517.tar.gz (72.4 kB view details)

Uploaded Source

Built Distribution

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

gluoncv-0.2.0b20180517-py2.py3-none-any.whl (103.5 kB view details)

Uploaded Python 2Python 3

File details

Details for the file gluoncv-0.2.0b20180517.tar.gz.

File metadata

File hashes

Hashes for gluoncv-0.2.0b20180517.tar.gz
Algorithm Hash digest
SHA256 aa735264627b60bef8f52c9a2d76f4d1a06c579ff3f6c534da184fff39229ee6
MD5 959f4fd0d6065830a5708d2da3b67d71
BLAKE2b-256 7d6301b808f40cb66c2e8137a5a2728030e8e92a2f4d710c99742f2b2480d502

See more details on using hashes here.

File details

Details for the file gluoncv-0.2.0b20180517-py2.py3-none-any.whl.

File metadata

File hashes

Hashes for gluoncv-0.2.0b20180517-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 34cda85a691566985fedcc460066df8b5acd8111e92f3cd5fa8eceedcb4f0618
MD5 896a93e959085fca54239e485800f731
BLAKE2b-256 694eaec4f5b2b588103c0778ab46942663b88b1bbc9c7b08fb087fa1fe526fae

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