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ChainerCV: a Library for Deep Learning in Computer Vision

ChainerCV is a collection of tools to train and run neural networks for computer vision tasks using Chainer.

You can find the documentation here.

Supported tasks:

Guiding Principles

ChainerCV is developed under the following three guiding principles.

Installation

$ pip install -U numpy
$ pip install chainercv

The instruction on installation using Anaconda is here (recommended).

Requirements

For additional features

Environments under Python 2.7.12 and 3.6.0 are tested.

Data Conventions

Sample Visualization

Example are outputs of detection models supported by ChainerCV These are the outputs of the detection models supported by ChainerCV.

Citation

If ChainerCV helps your research, please cite the paper for ACM Multimedia Open Source Software Competition. Here is a BibTeX entry:

@inproceedings{ChainerCV2017,
    author = {Niitani, Yusuke and Ogawa, Toru and Saito, Shunta and Saito, Masaki},
    title = {ChainerCV: a Library for Deep Learning in Computer Vision},
    booktitle = {ACM Multimedia},
    year = {2017},
}

The preprint can be found in arXiv: https://arxiv.org/abs/1708.08169