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)