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-0.3.0b20180730.tar.gz (100.9 kB view details)

Uploaded Source

Built Distribution

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

gluoncv-0.3.0b20180730-py2.py3-none-any.whl (139.3 kB view details)

Uploaded Python 2Python 3

File details

Details for the file gluoncv-0.3.0b20180730.tar.gz.

File metadata

  • Download URL: gluoncv-0.3.0b20180730.tar.gz
  • Upload date:
  • Size: 100.9 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-0.3.0b20180730.tar.gz
Algorithm Hash digest
SHA256 d098c1ee6b348ebaf139375c3e81bfb25387113f0bc52c6febbd96562a3a2d20
MD5 2fd551db5ed4aab051c1255d89e56405
BLAKE2b-256 9b3e1669a01b79b86905f43240672755d5db7709ee3c4d3fbb92e2d7f5045005

See more details on using hashes here.

File details

Details for the file gluoncv-0.3.0b20180730-py2.py3-none-any.whl.

File metadata

  • Download URL: gluoncv-0.3.0b20180730-py2.py3-none-any.whl
  • Upload date:
  • Size: 139.3 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-0.3.0b20180730-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 0b92359e6d35a6444fe0f4d9f39f45f528d92b795de826916b4944097f8a90c3
MD5 d66625c84f9cfe3f04a7ad2d203aa7ce
BLAKE2b-256 80a3ebb2f3d5d4a62b8ab8259df903960a79a0bca911e046db82b4c6f3bcf45b

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