- 2 x NVIDIA TESLA A100 40G GPU
- Ubuntu 18.04.5 LTS
- CUDA 11.4
- Python 3.6.9
conda env create -f environment.yml
conda activate zac2022
mkdir raw
mkdir train_video&&cd train_video
wget https://dl-challenge.zalo.ai/liveness-detection/train.zip
unzip train.zip
rm -rf train.zip
mv ./train/videos/*.mp4 .
mv ./train/label.csv ../raw
rm -rf train
cd ..
mkdir data&&cd data
wget https://dl-challenge.zalo.ai/liveness-detection/private_test.zip
unzip private_test.zip
rm -rf private_test.zip
mv ./private_test/videos/*.mp4 .
rm -rf private_test
cd ..
bash prepare_data.sh
python create_sample_sub.py
wget https://dl.fbaipublicfiles.com/convnext/convnext_xlarge_22k_1k_224_ema.pth -P weights
wget https://dl.fbaipublicfiles.com/convnext/convnext_large_22k_1k_224.pth -P weights
bash scripts/train_convnext_xlarge_fold0.sh
bash scripts/train_convnext_xlarge_fold1.sh
bash scripts/train_convnext_xlarge_fold2.sh
bash scripts/train_convnext_xlarge_fold3.sh
bash scripts/train_convnext_xlarge_fold4.sh
bash scripts/train_convnext_large_fold0.sh
bash scripts/train_convnext_large_fold1.sh
bash scripts/train_convnext_large_fold2.sh
bash predict.sh
Có thể sử dụng checkpoints nhóm mình đã train bằng cách download từ google drive:
bash download_weights.sh
bash predict.sh
Output là file submission.csv sẽ được lưu vào folder result. Sử dụng file này để nộp kết quả lên hệ thống.
