Metadata-Version: 2.1
Name: pfla
Version: 1.0.0
Summary: Python facial landmarking and analysis
Home-page: https://github.com/maxrousseau/pfla
Author: Maxime Rousseau
Author-email: maximerousseau08@gmail.com
License: MIT
Project-URL: Contribution guidelines, https://github.com/maxrousseau/pfla/blob/master/contributing.md
Project-URL: Issue Tracker, https://github.com/maxrousseau/pfla/issues
Project-URL: Source Code, https://github.com/maxrousseau/pfla
Description: pfla: Python Facial Landmark Analysis
        =====================================
        [![GitHub release](https://img.shields.io/github/release/maxrousseau/pfla.svg)](https://github.com/maxrousseau/pfla/releases)
        [![PyPI license](https://img.shields.io/pypi/l/pfla.svg)](https://pypi.org/project/pfla/)
        [![PyPI version fury.io](https://badge.fury.io/py/pfla.svg)](https://pypi.org/project/pfla/)
        [![PyPI pyversions](https://img.shields.io/pypi/pyversions/pfla.svg)](https://pypi.org/project/pfla/)
        [![Documentation
        Status](https://readthedocs.org/projects/pfla/badge/?version=master)](https://pfla.readthedocs.io/en/master/?badge=master)
        [![Build Status](https://travis-ci.org/maxrousseau/pfla.svg?branch=master)](https://travis-ci.org/maxrousseau/pfla)
        [![DOI](http://joss.theoj.org/papers/10.21105/joss.00855/status.svg)](https://doi.org/10.21105/joss.00855)
        
        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 compyte 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](https://joss.theoj.org/papers/10.21105/joss.00855). Since version 1.0.0,
        the packaged has changed considerably. The publication release is still
        available [here](https://github.com/maxrousseau/pfla/releases/tag/v0.1.1).
        
        
        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/>
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Scientific/Engineering :: Medical Science Apps.
Classifier: Topic :: Scientific/Engineering :: Image Recognition
Description-Content-Type: text/markdown
