Jamal, Aidan, Chidansh, and Ahmed

Additional data sets can be found on Kaggle

• Joint Feature and Similarity Deep Learning for Vehicle Re-identification
• Variational Fair Autoencoder
• A Cloud-guided Feature Extraction Approach for Image Retrieval in Mobile Edge Computing
• HyperFace: A Deep Multi-task Learning Framework for Face Detection, Landmark Localization, Pose Estimation, and Gender Recognition
• Deep Feature Consistent Variational Autoencoder

• Pytorch VAE Git Repo
• Theanos VFAE Git Repo

• Bala's Intro to Amarel Video
• Kaltura Videos
• OnDemand
• OARC
• User Guide
• Add the following to SLURM to use GPUs:

#SBATCH --gres=gpus:1
#SBATCH -partition=gpu

• To clone the repo, enter below snippet into your command line

git clone https://github.com/Behavioral-Informatics-Lab/Face_Matching.git

• Remember to pull to avoid version conflicts!

git pull

• To push your changes to the git repo, enter the following (or a similar variant) in your command line:

git add .
git commit -m "Your comment"
git push

• If pushes are taking too long, then consider

git config http.postBuffer 524288000

• Locally install the images ONLY from the CelebA data set. This should be a zip file. The annotations should already be a part of the repo. The file structure:

├── Checkpoints
└── Data Sets
    └── CelebA
        ├── annot
        └── img_align_celeba
            └── [INSERT IMAGES HERE]
    └── UMD Faces

• first use (0), after checkpoint saved (1)

load_net = 0 

• CPU (0), GPU (1)

use_cuda = 0 

• Modify train, validation, and test ratios accordingly

train_ratio = 0
val_ratio = 0
test_ratio = 1-train_ratio-val_ratio

• Make sure you are using the correct version of pytorch for running Jamal's code

pip install torch===1.6.0 torchvision===0.7.0 -f https://download.pytorch.org/whl/torch_stable.html 

• Run code (here is what my command line looks like)

PS C:\Users\austr\Desktop\BIL Face Matching Alg Fairness\Face_Matching> & C:/Users/austr/anaconda3/python.exe "c:/Users/austr/Desktop/BIL Face Matching Alg Fairness/Face_Matching/Paper1Scripts/low_high_celeb_adversal_test_all.py"