PatchNet: A Simple Face Anti-Spoofing Framework via Fine-Grained Patch Recognition

This repository implements PatchNet from paper PatchNet: A Simple Face Anti-Spoofing Framework via Fine-Grained Patch Recognition

Reference

[1] PatchNet: PatchNet: A Simple Face Anti-Spoofing Framework via Fine-Grained Patch Recognition
[2] CDCN repository: CDCN-Face-Anti-Spoofing.pytorch

Project Structure

Implementation-patchnet
      |
      |---config
      |     |--config.yaml
      |
      |---dataset
      |     |--FAS_dataset.py
      |     |--transform.py
      |
      |---engine
      |     |--__init__.py
      |     |--base_trainer.py
      |     |--Patchnet_trainer.py
      |
      |---metrics
      |     |--losses.py
      |     |--meter.py
      |
      |---models
      |     |--CDCNs.py
      |     |--convnext_tiny.py
      |     |--DC_CDN.py
      |     |--resnet18.py
      |     |--swin_base.py
      |
      |---tool
      |     |--test.py
      |     |--train.py
      |
      |---utils
      |     |--utils.py
      |
      |---README.md
      |---requirements.txt

Installation

$ python3 -m venv env
$ source env/bin/activate
$ pip install -r requirements.txt

Usage

Data preparation

datasets
    |---images
    |     |--img1
    |     |--img2
    |     |...
    |---train.csv
    |---val.csv
    |---test.csv

with [set_name.csv] have format (label only has 2 class: 0-Spoofing, 1-Liveness): \

image_name  |  label
img_name1   |    0
img_name2   |    1
...

training

python3 train.py

Testing

Go to tool/test.py and fix saved_name to your path to checkpoint
Run

python3 test.py

Contributer

Tien Thong Doan
Minh Chau Nguyen
Minh Hung Nguyen