Skip to main content

Python bindings to the flandmark keypoint localization library

Project description

http://img.shields.io/badge/docs-stable-yellow.png http://img.shields.io/badge/docs-latest-orange.png https://travis-ci.org/bioidiap/bob.ip.flandmark.svg?branch=v2.1.1 https://coveralls.io/repos/bioidiap/bob.ip.flandmark/badge.svg?branch=v2.1.1 https://img.shields.io/badge/github-master-0000c0.png http://img.shields.io/pypi/v/bob.ip.flandmark.png http://img.shields.io/pypi/dm/bob.ip.flandmark.png

Python Bindings to Flandmark

This package is a simple Python wrapper to the (rather quick) open-source facial landmark detector Flandmark, version 1.0.7 (or the github state as of 10/february/2013). If you use this package, the author asks you to cite the following paper:

@inproceedings{Uricar-Franc-Hlavac-VISAPP-2012,
  author =      {U\v{r}i\v{c}\'a\v{r}, Michal and Franc, Vojt\v{e}ch and Hlav\'a\v{c}, V\'{a}clav},
  title =       {Detector of Facial Landmarks Learned by the Structured Output {SVM}},
  year =        {2012},
  pages =       {547-556},
  booktitle =   {VISAPP '12: Proceedings of the 7th International Conference on Computer Vision Theory and Applications},
  editor =      {Csurka, Gabriela and Braz, Jos{\'{e}}},
  publisher =   {SciTePress --- Science and Technology Publications},
  address =     {Portugal},
  volume =      {1},
  isbn =        {978-989-8565-03-7},
  book_pages =  {747},
  month =       {February},
  day =         {24-26},
  venue =       {Rome, Italy},
  keywords =    {Facial Landmark Detection, Structured Output Classification, Support Vector Machines, Deformable Part Models},
  prestige =    {important},
  authorship =  {50-40-10},
  status =      {published},
  project =     {FP7-ICT-247525 HUMAVIPS, PERG04-GA-2008-239455 SEMISOL, Czech Ministry of Education project 1M0567},
  www = {http://www.visapp.visigrapp.org},
}

You should also cite Bob, as a core framework, in which these bindings are based on:

@inproceedings{Anjos_ACMMM_2012,
  author = {Anjos, Andr\'e AND El Shafey, Laurent AND Wallace, Roy AND G\"unther, Manuel AND McCool, Christopher AND Marcel, S\'ebastien},
  title = {Bob: a free signal processing and machine learning toolbox for researchers},
  year = {2012},
  month = oct,
  booktitle = {20th ACM Conference on Multimedia Systems (ACMMM), Nara, Japan},
  publisher = {ACM Press},
  url = {http://publications.idiap.ch/downloads/papers/2012/Anjos_Bob_ACMMM12.pdf},
}

Installation

To install this package – alone or together with other Packages of Bob – please read the Installation Instructions. For Bob to be able to work properly, some dependent packages are required to be installed. Please make sure that you have read the Dependencies for your operating system.

Documentation

For further documentation on this package, please read the Stable Version or the Latest Version of the documentation. For a list of tutorials on this or the other packages ob Bob, or information on submitting issues, asking questions and starting discussions, please visit its website.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

bob.ip.flandmark-2.1.1.zip (2.1 MB view details)

Uploaded Source

File details

Details for the file bob.ip.flandmark-2.1.1.zip.

File metadata

File hashes

Hashes for bob.ip.flandmark-2.1.1.zip
Algorithm Hash digest
SHA256 db4bed128d23794415484d96197da31bd44d395e172eaa6ccce2ae6bf9ba70b6
MD5 0467a7450e3e9f15d79ada16ebe65fb4
BLAKE2b-256 ff8e9f43a6dde24937758a8034373c869b6e7523ef497ac730b356f470d550b3

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