@@ -42,12 +42,27 @@ This repository is organised as follows:
...
@@ -42,12 +42,27 @@ This repository is organised as follows:
## Running the pipeline
## Running the pipeline
1. Download the database from the following link: https://www.idiap.ch/en/dataset/phymatt
1. Download the database from the following link: https://www.idiap.ch/en/dataset/phymatt
2. Create a list of the videos to be used for the experiment. The list should contain the path for each video you want in the experiment. If you want all videos, you can use the following command: `find <path_to_database> -name "*.mp4" > <path_to_list>`
2. Create a list of the videos to be used for the experiment. The list should contain the path for each video you want in the experiment. If you want all videos, you can use the following command:
3. Run the frames extraction code as follows: `python preprocessor/extract_frames.py -l <path_to_list> -o <path_to_output_folder>`
4. Run the database organization code as follows: `python database/create_database_dataframe.py --frames_list --output_path -metadata_filename -save_mode --min_face_size`
6. Once you have the score files, namely the `score-dev.csv`, you can use the script `utils/split_scores.sh` to split the scores into bona-fide and attack scores. The script will create three files: `scores-dev_print-attack.csv`, `scores-dev_replay-attack.csv` and `scores-dev_hyg-maks.csv`.
6. Once you have the score files, namely the `score-dev.csv`, you can use the script `utils/split_scores.sh` to split the scores into bona-fide and attack scores. The script will create three files: `scores-dev_print-attack.csv`, `scores-dev_replay-attack.csv` and `scores-dev_hyg-maks.csv`.
7. You can then use these files to compute the metrics as follows: `bob vuln metrics scores-dev_print-attack.csv scores-dev_replay-attack.csv scores-dev_hyg-maks.csv`
7. You can then use these files to compute the metrics as follows: