gradgpad
Project description
The GRAD-GPAD framework 🗿
👉 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
pip install gradgpad
🚀 Getting Started
The best way to learn how to use the GRAD-GPAD framework is through the Notebook examples available in:
📺 Video Tutorial
📰 Reproducible Research
$ 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
>> conda create -n grad-gpad python=3.6
>> conda activate grad-gpad
(grad-gpad) >> pip install lume
(grad-gpad) >> lume -install
- ✅ Testing
(grad-gpad) >> lume -test
Project details
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.