______ ___ __ _ _____ _____
/ ____/___ _________ / | ____ / /_(_) / ___/____ ____ ____ / __(_)___ ____ _
/ /_ / __ `/ ___/ _ \ / /| | / __ \/ __/ / \__ \/ __ \/ __ \/ __ \/ /_/ / __ \/ __ `/
/ __/ / /_/ / /__/ __/ / ___ |/ / / / /_/ / ___/ / /_/ / /_/ / /_/ / __/ / / / / /_/ /
/_/ \__,_/\___/\___/ /_/ |_/_/ /_/\__/_/ /____/ .___/\____/\____/_/ /_/_/ /_/\__, /
/_/ /____/
This project aims to evaluate the performance of lightweight face models for facial anti-spoofing (FAS), comparing their accuracy and computational complexity with state-of-the-art deep models.
Input: Image with face
Output: Fake or Real
LCCD FASD Dataset. Link: https://www.kaggle.com/datasets/faber24/lcc-fasd
-
ResNeXT50
-
MobileNetV3
-
FeatherNet
We evaluate on LCCD FASD Development after preprocessing. Link: CV_dataset
Model | APCER | NPCER | ACER |
---|---|---|---|
ResNeXT50 | 0.1308 | 0.3037 | 0.2127 |
MobileNetV3 | 0.1727 | 0.2111 | 0.1917 |
FeatherNet | 0.1994 | 0.1284 | 0.1639 |
- Clone Project
git clone https://github.com/dtruong46me/face-anti-spoofing.git
cd face-anti-spoofing
- Install requirements.txt
bash setup.sh
- Training
First, you should download CV_dataset and put it into the folder
/face-anti-spoofing/cv-dataset
and run the scipt:
python run_training.py \
--train_path "cv-dataset/final_data/train" \
--test_path "cv-dataset/final_data/valid" \
--batch_size 128 \
--modelname "seresnext50"\
--wandb_token "<your_wandb_token>" \
--wandb_runname "<your_wandb_run_name>" \
--num_classes 2 \
--max_epochs 40
or your can use bash train_all.sh
to train, evaluate, predict all pretrained models.
You can follow scipts in the notebook: https://www.kaggle.com/code/dtruon46/master-face-anti-spoofing or the file: /face-anti-spoofing/code train.ipynb
- Demo
You can download weights of models (.ckpt
file) and put it into the /face-anti-spoofing/FAS_detector/model/your_model.ckpt
. Put your test image in the /face-anti-spoofing/assets/samples/your_images.jpg
Then run the scripts
python predict_sample.py \
--model_checkpoint "your_model.ckpt" \
--image "your_test_image.jpg"\
--modelname "seresnext50"
-
Supervisor: Prof. Dang Tuan Linh
-
Group Members
No. | Name | Student ID | |
---|---|---|---|
1 | Vu Tuan Minh (Leader) | 20210597 | [email protected] |
2 | Nguyen Tien Doanh | 20214881 | [email protected] |
3 | Nguyen Tung Luong | 20214913 | [email protected] |
4 | Phan Dinh Truong | 20214937 | [email protected] |