First create a conda environment using the following command:
conda env create -f environment.ymlThen activate the environment using the following command:
conda activate chimeraThen download the required data and models from this link
In the recapture-detection directory, run the following command:
python main.py --test --test_path TEST_PATH --config CONFIG --test_raw_dirnames RAW_DIRNAMES --test_recap_dirnames RECAP_DIRNAMESwhere TEST_PATH is the path to the model, CONFIG is the path to the configuration file, RAW_DIRNAMES is the list of raw directory names, and RECAP_DIRNAMES is the list of recapture directory names. Ensure that the configuration file matches the model being tested. Results should be printed to the terminal.
In the deepfake-detection directory, first update dataset paths in dataset_paths.py and move the deepfake detection model weights are in the pretrained_weights folder.
The following command:
./test.shwill run all the deepfake detection tests at once and save the results in the deepfake-detection/results directory.