Metadata-Version: 2.1
Name: gradgpad
Version: 2.0.2
Summary: gradgpad
Home-page: https://github.com/acostapazo/gradgpad
Author: ALiCE Biometrics
Author-email: acosta@alicebiometrics.com
License: MIT
Description: # The GRAD-GPAD framework 🗿 [![version](https://img.shields.io/github/release/acostapazo/gradgpad/all.svg)](https://github.com/acostapazo/gradgpad/releases) [![ci](https://github.com/acostapazo/gradgpad/workflows/ci/badge.svg)](https://github.com/acostapazo/gradgpad/actions) [![pypi](https://img.shields.io/pypi/dm/gradgpad)](https://pypi.org/project/gradgpad/)
        
        
        👉  The GRAD-GPAD framework is a comprehensive and modular framework to evaluate the performance of face-PAD (face Presentation Attack Detection) approaches in realistic settings, enabling accountability and fair comparison of most face-PAD approaches in the literature.
        
        🙋  GRAD-GPAD stand for Generalization Representation over Aggregated Datasets for Generalized Presentation Attack Detection
        
        
        ## 💻 Installation
        
        ```console
        pip install gradgpad
        ```
        
        ## 🚀 Getting Started
        
        The best way to learn how to use the GRAD-GPAD framework is through the Notebook examples available in:
        
        *  [gradgpad-notebooks](https://github.com/acostapazo/gradgpad-notebooks) 📔 
        
        ## 📺 Video Tutorial
        
        [![Tutorial](https://img.youtube.com/vi/y5lQox0hmGU/0.jpg)](https://www.youtube.com/watch?v=y5lQox0hmGU)
        
        ## 📰 Reproducible Research
        
        ```console
        $ gradgpad --reproducible-research -o <output-folder> 
        ```
        
        Use `gradgpad --help` to check available parameter
        
        ```
        $ gradgpad --help                         
        usage: gradgpad [-h] [--reproducible-research] [--zip]
                        [--output-path OUTPUT_PATH]
        
        optional arguments:
          -h, --help            show this help message and exit
          --reproducible-research, -rr
                                Create a folder with reproducible research results
          --zip, -z             Zip result folder
          --output-path OUTPUT_PATH, -o OUTPUT_PATH
                                Output path
        ```
        
        ## 🤔 Contributing
        
        There is a lot of work ahead (adding new categorizations, datasets, improving documentation...), feel free to add and propose any improvements you can think of! If you need help getting started, don't hesitate to contact us :v:
        
        * 🛠️ Environment
        
        ```console
        >> conda create -n grad-gpad python=3.6
        >> conda activate grad-gpad
        (grad-gpad) >> pip install lume
        (grad-gpad) >> lume -install
        ```
        
        * ✅ Testing
        
        ```console
        (grad-gpad) >> lume -test
        ```
        
        
Keywords: face-PAD,framework,evaluation
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Description-Content-Type: text/markdown
