W251_Project

Final Project for W251 MIDS Program

1. Download vggFace2 Dataset

Download dataset with 500 faces from (https://www.kaggle.com/greatgamedota/vggface2-test). The dataset is stored in W251_Project/data/test_no_mask folder

2. Dataset Augmentation with masks

Install packages in conda environment given in W251_project/conda_env.sh

python mask_the_face.py --inpath data/test_no_mask --outpath data/test_with_mask --mask_type <type-of-mask> --verbose --write_original_image

3. Facenet training without masks

Run jupyter notebook

jupyter notebook --allow-root

Run finetune_no_augmentation.ipynb

The trained model is saved as /data/model_no_mask.pt

4. Facenet training with masks

Run finetune_with_augmentation.ipynb

The trained model is saved as /data/model_with_mask.pt

The training with and without the augmentation are done to demonstrate improvements with the augmentation.

5. Masked face Inference on Jetson

The model trained in steps 3) and 4) are downloaded to W251_Project/data in Jetson. The Jetson files are in jetson-inference subfolder.

Run PyTorch docker container for inference

docker/run.sh

Run jetson-inference/infer.ipynb inisde the container

jupyter notebook --allow-root