To run locally:

1. clone repo
2. pip install -r requirements.txt
3. store ur test-video in data folder.
4. python main.py --input_path data/test_video.mp4 --output_path results --info_path method_info.json --device cpu --checkpoint_path checkpoints/model.pth

To run using Docker:

1. https://hub.docker.com/r/tarunam172/altfreezing-image2
2. Use the above link and pull image to local.
3. To see the results folder, open a dir containing two folders (data,results) and CD to curr dir in cmd prompt.
4. Put the .mp4 video in data folder.
5. Run this cmd, docker run -v "path_to_dataFolder:/app/data" -v "path_to_resultsFolder:/app/results" tarunam172/altfreezing-image2 python main.py --input_path /app/data/your_test_video_name.mp4 --output_path /app/results --info_path /app/method_info.json --device cpu --checkpoint_path /app/checkpoints/model.pth
6. Once it is run, result.json file will be created in results folder.

To run in Google colab: Connect to GPU

1. Install python 3.9: !sudo apt-get install python3.9 python3.9-distutils python3.9-dev -y
2. Get pip and install: !wget https://bootstrap.pypa.io/get-pip.py and !python3.9 get-pip.py
3. Clone the github: !git clone https://github.com/Scoperr/deep-fake-dectection
4. Navigate to deep-fake-detection folder: %cd deep-fake-dectection
5. Install requirements.txt: !python3.9 -m pip install -r requirements.txt
6. Use this cmd: !python3.9 main.py --input_path data/test_video_name --output_path results --info_path method_info.json --device cuda --checkpoint_path checkpoints/model.pth