pfla
pfla: A Python Package for Dental Facial Analysis using Computer Vision and Statistical Shape Analysis - Published in JOSS (2018)
Science Score: 93.0%
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 7 DOI reference(s) in README and JOSS metadata -
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Links to: joss.theoj.org -
○Committers with academic emails
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✓JOSS paper metadata
Published in Journal of Open Source Software
Keywords
Repository
pfla: Python Facial Landmark Analysis
Basic Info
- Host: GitHub
- Owner: maxrousseau
- License: mit
- Language: Python
- Default Branch: master
- Homepage: https://pfla.readthedocs.io/en/master/?badge=master#
- Size: 79.9 MB
Statistics
- Stars: 6
- Watchers: 1
- Forks: 2
- Open Issues: 1
- Releases: 4
Topics
Metadata Files
README.md
pfla: Python Facial Landmark Analysis
A simple command line interface to automate facial analysis. pfla uses a
pre-trained neural networks to detect faces and annotate them with 68
landmarks. The program also compute four commonly used facial metrics. The
output is saved to a file to allow for easy statistical analysis by the user.
Publication
This software was published in JOSS. Since version 1.0.0, the packaged has changed considerably. The publication release is still available here.
Citing
If you use this software please use this citation:
@article{Rousseau_2018,
doi = {10.21105/joss.00855},
url = {https://doi.org/10.21105%2Fjoss.00855},
year = 2018,
month = {dec},
publisher = {The Open Journal},
volume = {3},
number = {32},
pages = {855},
author = {Maxime Rousseau and Jean-Marc Retrouvey},
title = {pfla: A Python Package for Dental Facial Analysis using Computer Vision and Statistical Shape Analysis},
journal = {Journal of Open Source Software}}
Features
- Face detection using mtcnn
- Landmark placement
- Facial metric calculations
Requirements and Dependencies
- Python 3.5 (or higher)
- Python packages:
- numpy
- pandas
- pytest
- pillow
- facenet-pytorch
- face-alignment
- pytest-cov
- pytorch
Installation
Install with pip:
shell
pip install -r requirements-pytorch.txt \ # pytorch for CPU
-f https://download.pytorch.org/whl/torch_stable.html
pip install -r requirements.txt # other dependencies
pip install pfla
Usage
```shell usage: pfla [-h] [-d] [-l] [-m] [-o OUTPUT] [-v] path
PFLA: python facial landmark analysis. This program will read the image(s) given as input and can apply a face detection algorithm, landmark placement and computation of metrics. The results are returned as a text stream.
positional arguments: path path to the image or directory of images
optional arguments: -h, --help show this help message and exit -d, --detect detect faces and output bounding box -l, --landmark annotate detected faces and output coordinates -m, --metrics compute metrics and output results -o OUTPUT, --output OUTPUT specify output filename and format/filetype of the data -v, --verbose increase output verbosity
AUTHOR: Maxime Rousseau LICENSE: MIT ```
Testing
To test your installation run the following commands:
shell
cd [PATH_TO_PACKAGE_INSTALLATION]
pytest
Documentation
Documentation of the package can be found here: https://pfla.readthedocs.io/en/master
Contribute
- Contribution guidelines: https://github.com/maxrousseau/pfla/blob/master/contributing.md
- Issue Tracker: https://github.com/maxrousseau/pfla/issues
- Source Code: https://github.com/maxrousseau/pfla
License
The project is licensed under the MIT license.
Contact
Maxime Rousseau, DMD candidate 2020 McGill University, Faculty of Dentistry - Email: maximerousseau08@gmail.com - Website: https://maxrousseau.github.io/portfolio/
Owner
- Name: Maxime Rousseau
- Login: maxrousseau
- Kind: user
- Location: Montreal, Canada
- Website: https://maxrousseau.github.io/portfolio/
- Repositories: 6
- Profile: https://github.com/maxrousseau
DMD
JOSS Publication
pfla: A Python Package for Dental Facial Analysis using Computer Vision and Statistical Shape Analysis
Authors
McGill University, Faculty of Dentistry
McGill University, Faculty of Dentistry
Editor
Ariel Rokem
Tags
facial analysis dentistry statistical shape analysis euclidean geometryGitHub Events
Total
- Watch event: 1
Last Year
- Watch event: 1
Committers
Last synced: 7 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| maxrousseau | m****8@g****m | 89 |
| maxime | m****x@t****0 | 59 |
| Guillaume Lemaitre | g****8@g****m | 36 |
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 13
- Total pull requests: 3
- Average time to close issues: 20 days
- Average time to close pull requests: about 12 hours
- Total issue authors: 3
- Total pull request authors: 3
- Average comments per issue: 2.92
- Average comments per pull request: 3.67
- Merged pull requests: 2
- Bot issues: 0
- Bot pull requests: 1
Past Year
- Issues: 0
- Pull requests: 1
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 1
- Average comments per issue: 0
- Average comments per pull request: 0.0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 1
Top Authors
Issue Authors
- glemaitre (7)
- mnarayan (5)
- arokem (1)
Pull Request Authors
- dependabot[bot] (2)
- glemaitre (1)
- maxrousseau (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
-
Total downloads:
- pypi 24 last-month
- Total dependent packages: 0
- Total dependent repositories: 1
- Total versions: 18
- Total maintainers: 1
pypi.org: pfla
Python facial landmarking and analysis
- Homepage: https://github.com/maxrousseau/pfla
- Documentation: https://pfla.readthedocs.io/
- License: MIT
-
Latest release: 1.0.0
published almost 6 years ago
Rankings
Maintainers (1)
Dependencies
- alabaster *
- docutils ==0.16
- mock *
- sphinx *
- sphinxcontrib-applehelp *
- sphinxcontrib-devhelp *
- sphinxcontrib-htmlhelp *
- sphinxcontrib-jsmath *
- sphinxcontrib-napoleon *
- sphinxcontrib-qthelp *
- sphinxcontrib-serializinghtml *
- torch ==1.5.0
- torchvision ==0.6.0
- face-alignment *
- facenet-pytorch *
- numpy *
- pandas *
- pillow *
- pytest *
- pytest-cov *