Skip to content
This repository has been archived by the owner on Jan 3, 2023. It is now read-only.

Latest commit

 

History

History
100 lines (62 loc) · 3.42 KB

README.md

File metadata and controls

100 lines (62 loc) · 3.42 KB
Raw

DISCONTINUATION OF PROJECT

This project will no longer be maintained by Intel. This project has been identified as having known security escapes. Intel has ceased development and contributions including, but not limited to, maintenance, bug fixes, new releases, or updates, to this project. Intel no longer accepts patches to this project.

aeon

aeon is Intel Nervana's framework-independent deep learning dataloader committed to best performance. Designed for ease-of-use and extensibility.

  • Supports common media types: image, video. It is ready for use with classification, segmentation, localization, transcription and more.
  • Loads and augments data in parallel to framework computation.
  • Examples folder contains simple scripts showing how to use it.

For fast iteration and model exploration, it is already used by fastest performance deep learning framework neon.

See the new features in our latest release.

Getting Started

Installation

First grab Aeon's dependencies:

Ubuntu (release 16.04 LTS and later):

apt-get install git clang libopencv-dev
For Python 3.n
apt-get install python3-dev python3-pip python3-numpy

CentOS (release 7.2 and later):

yum install epel-release
yum install git clang gcc-c++ make cmake opencv-devel
For Python 2.7
yum install python-pip python-devel
For Python 3.n
yum install python-pip python34-pip python34-devel python34-opencv python34-numpy

OSX:

brew tap homebrew/science
brew install opencv

Code coverage

Code coverage in aeon depends on llvm-cov and lcov.
Report will be generated in html-coverage-report/index.html

Example:

sudo apt-get install llvm lcov
mkdir build
cd build
# COVERAGE flag must be set to generate coverage report
cmake .. -DCOVERAGE=ON
# If you want to generate report when unit test fails: make -i coverage
make coverage

To install Aeon:

git clone https://github.com/NervanaSystems/aeon.git
For Python 2.7
cd aeon
pip install -r requirements.txt
mkdir -p build && cd $_ && cmake .. && pip install .
For Python 3.n
cd aeon
pip3 install -r requirements.txt
mkdir -p build && cd $_ && cmake .. && pip3 install .

Note: if installing system wide (as opposed to within a virtual environment) you may need to run sudo

Now continue on to the user guide to get started using aeon. Or to the developer guide to developing custom loaders/transformers.

Documentation

The complete documentation for aeon is available here.

Support

For any bugs or feature requests please:

Search the open and closed issues list to see if we're already working on what you have uncovered. Check that your issue/request isn't framework related. File a new issue or submit a new pull request if you have some code you'd like to contribute

License

We are releasing aeon under an open source Apache 2.0 License. We welcome you to contact us with your use cases.