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    bob.ip.mtcnn

Face detection and landmark extraction using MTCNN pretrained model


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.. vim: set fileencoding=utf-8 : .. Tiago de Freitas Pereira tiago.pereira@idiap.ch .. Fri 17 Jul 02:49:53 2016 CEST

.. image:: http://img.shields.io/badge/docs-v1.0.3-yellow.svg :target: https://www.idiap.ch/software/bob/docs/bob/bob.ip.mtcnn/v1.0.3/index.html .. image:: http://img.shields.io/badge/docs-latest-orange.svg :target: https://www.idiap.ch/software/bob/docs/bob/bob.ip.mtcnn/master/index.html .. image:: https://gitlab.idiap.ch/bob/bob.ip.mtcnn/badges/v1.0.3/build.svg :target: https://gitlab.idiap.ch/bob/bob.ip.mtcnn/commits/v1.0.3 .. image:: https://gitlab.idiap.ch/bob/bob.ip.mtcnn/badges/v1.0.3/coverage.svg :target: https://gitlab.idiap.ch/bob/bob.ip.mtcnn/commits/v1.0.3 .. image:: https://img.shields.io/badge/gitlab-project-0000c0.svg :target: https://gitlab.idiap.ch/bob/bob.ip.mtcnn .. image:: http://img.shields.io/pypi/v/bob.ip.mtcnn.svg :target: https://pypi.python.org/pypi/bob.ip.mtcnn

===================================================== Bob interface for MTCNN face and landmark detection

This package wraps the MTCNN face and landmark detection from the paper

@ARTICLE{7553523, 
    author={K. Zhang and Z. Zhang and Z. Li and Y. Qiao}, 
    journal={IEEE Signal Processing Letters}, 
    title={Joint Face Detection and Alignment Using Multitask Cascaded Convolutional Networks}, 
    year={2016}, 
    volume={23}, 
    number={10}, 
    pages={1499-1503}, 
    keywords={Benchmark testing;Computer architecture;Convolution;Detectors;Face;Face detection;Training;Cascaded convolutional neural network (CNN);face alignment;face detection}, 
    doi={10.1109/LSP.2016.2603342}, 
    ISSN={1070-9908}, 
    month={Oct},}

Installation

Complete Bob's installation_ instructions. Then, to install this package, run::

$ conda install bob.ip.mtcnn

Documentation

For further documentation on this package, please read the Latest Version <https://www.idiap.ch/software/bob/docs/bioidiap/bob.ip.mtcnn/master/index.html>_ of the documentation.

.. _bob: https://www.idiap.ch/software/bob

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