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-0.3.0b20180805.tar.gz (120.9 kB view details)

Uploaded Source

Built Distribution

gluoncv-0.3.0b20180805-py2.py3-none-any.whl (163.4 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file gluoncv-0.3.0b20180805.tar.gz.

File metadata

  • Download URL: gluoncv-0.3.0b20180805.tar.gz
  • Upload date:
  • Size: 120.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/40.0.0 requests-toolbelt/0.8.0 tqdm/4.24.0 CPython/3.5.3

File hashes

Hashes for gluoncv-0.3.0b20180805.tar.gz
Algorithm Hash digest
SHA256 3605d81b9d287598f995033c6642fe496068554bd1eb973ba5bbbbe8a545eea5
MD5 44f5d44528e92cca31303aefcca634b5
BLAKE2b-256 52e81d963469d67db331dd8f1781332830b707942e3c206dec148d9481aa8f15

See more details on using hashes here.

File details

Details for the file gluoncv-0.3.0b20180805-py2.py3-none-any.whl.

File metadata

  • Download URL: gluoncv-0.3.0b20180805-py2.py3-none-any.whl
  • Upload date:
  • Size: 163.4 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/40.0.0 requests-toolbelt/0.8.0 tqdm/4.24.0 CPython/3.5.3

File hashes

Hashes for gluoncv-0.3.0b20180805-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 7bb5816e731c7b51ba8c659c8e8a055171f52fb85ae4bbad2264ea2650290bda
MD5 4f6737c4a8b2f1fb6fc1fcf63f4919a6
BLAKE2b-256 5d6f7cb337396efbef3684cb639b1dce0ea85a0f044dc008be4609d5c98f5276

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