This folder contains the neceseray code to run inference using the DeepFake Detection (DFDC) solution by team Selim Seferebekov. For more details on the project please visit the GitHub repository.

• torchvision==0.5.0
• torch==1.4.0
• numpy==1.18.1
• timm==0.3.4
• opencv_python==4.2.0.34
• albumentations==0.5.2
• facenet_pytorch==2.5.1
• Flask==1.1.2
• Pillow==8.1.0

To start a container that has all the requirements for using the model first build the image by running the following command in this directory:

docker build -t selimsef_i .

To use GPUs in the container you will need to install the NVIDIA container toolkit. To run the container in interactive mode use the following command.

docker run --runtime=nvidia -it selimsef_i

To run the models, the pretrained model weights will need to be placed in the containers workdir/weights directory. This can be done by running the download_weights.sh before building the image, or inside the container, or by mounting a volume containing the weights to the container at runtime:

docker run --runtime=nvidia -it -v <path to weight directory>:/workdir/weights  selimsef_i

from ensemble import Ensemble
submit = Ensemble()
prediction = submit.inference(video_path)