Distilled Face:

1. Setup

1. Create new conda environement: conda env create -f environment.yml
2. Activate conda environment: conda activate cl-distilled
3. Install pip requirements: pip install -r requirements.txt
4. Download training data: ./scripts/download_training_data.sh
5. Download evaluation data: ./scripts/download_eval_data.sh
6. Make cl-distilled env available for Jupyter: python -m ipykernel install --user --name=cl-distilled

And we're good to go! Distilled Face :)

2. Notebooks and Source Code

1. Source code for modules required by DistilFACE can be found in:

• src/distilface/modules/pooler.py
• src/distilface/modules/similarity.py

2. Main DistilFACE model implementation can be found in the notebooks in folder:

• Section 2 of notebooks/training/*.ipynb

3. Hyperparameter tuning results can be found in all the notebooks in:

• Section 4 of notebooks/training/*.ipynb

3. LaTEX Setup

1. Install required binaries:

$ apt-get update && apt-get install texlive-latex-base texlive-fonts-recommended texlive-fonts-extra texlive-bibtex-extra

2. Generate LaTeX Report:

make report

Referenced from Bibliography_management_with_bibtex