Flandmark keypoint localization library
Project description
Flandmark keypoint localization library
This package is part of the signal-processing and machine learning toolbox Bob. It contains 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},
}
Installation
Complete Bob’s installation instructions. Then, to install this package, run:
$ conda install bob.ip.flandmark
Contact
For questions or reporting issues to this software package, contact our development mailing list.
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
bob.ip.flandmark-2.1.8.zip
(2.1 MB
view details)
File details
Details for the file bob.ip.flandmark-2.1.8.zip.
File metadata
- Download URL: bob.ip.flandmark-2.1.8.zip
- Upload date:
- Size: 2.1 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | f74d045260f200fda1790103c696067a7564b899a255409ae8d4e646e1a4d8b4 |
|
| MD5 | 47c708e978cdecc3ce0b1a0cb6f1bf66 |
|
| BLAKE2b-256 | 9ad2cb61f7abba804e2d78f85773845c1f06073c55151e055f5f53b4f1aa3734 |
