Note: This repo was forked from the original on bitbucket: https://bitbucket.org/ericyang3721/headpose_forensic.git
This repository is the implementation of the work used in our ICASSP paper Exposing Deep Fakes Using Inconsistent Head Poses
- Ubuntu 16.04
- tqdm 4.28.1
- numpy 1.15.4
- dlib 19.16.0
- opencv-python 3.4.3.18
python run_test.py --input_dir=debug_data --classifier_path=path/to/trained/model --save_file=path/to/output/resultsThis will examine all images and videos in the folder of 'debug_data', print results in terminal, and the probability of being fake images/video could be saved in --save_file in the project root folder.
The result include a optout attribute, which indicate whether a image is not used for classification when it is true.
There are 3 steps to train the classifier:
step 1: extract landmarks of real and fake data
python train_step1_landmarks.py --real_video_dir=dir/to/real/videos --fake_video_dir=dir/to/fake/videos --output_landmark_path=path/to/save/landmarksstep 2: extract head poses
python train_step2_headposes.py --landmark_info_path=path/to/landmarks/in/step1 --headpose_save_path=path/to/save/headpose/datastep 3: train svm model
python train_step3_training.py --headpose_path=path/to/headposes/in/step2 --model_save_path=path/to/save/trained/modelPlease cite our paper in your publications if it helps your research.
@inproceedings{yang2019exposing,
title={Exposing Deep Fakes Using Inconsistent Head Poses},
author={Yang, Xin and Li, Yuezun and Lyu, Siwei},
booktitle={IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
year={2019}
}
This repository is NOT for commecial use. It is provided "as it is" and we are not responsible for any subsequence of using this code.