a video lie detector using OpenFace and xgboost for this project, I used the OpenFace tool on a docker container. the project is available on linux only. tested on ubuntu 18.04.6

this project contains 2 scripts: train_xgboost_model.py- trains the model on the action units data predict_with_xgboost.py generates predictions from video files

in this project, I use OpenFace to extract the action units, an encoding method for facial movements, and passing a list of average of action units of each movement. the model currently has about 70% percent accuracy, with a 50/50 label distribution in the dataset. that means the model is capable of learning the dataset, and could improve if there was more data available

datset size: 121 samples distribution: 61 lies, 60 truthful accuracy score 0.71 precision score 0.73 recall score 0.67 f1 score 0.7