abhijithjadhav/Deepfake_detection_using_deep_learning
This projects aims in detection of video deepfakes using deep learning techniques like RestNext and LSTM. We have achived deepfake detection by using transfer learning where the pretrained RestNext CNN is used to obtain a feature vector, further the LSTM layer is trained using the features. For more details follow the documentaion.
The project includes a Dockerized Django web application enabling video upload and real-time prediction without dependency management overhead. Frame-based extraction feeds temporal sequences into the LSTM layer, with accuracy scaling from 84% to 93.5% depending on frame count (10-100 frames sampled per video). The implementation supports both CUDA and non-CUDA environments, targeting accessibility across different GPU configurations.
840 stars. No commits in the last 6 months.
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Jul 28, 2024
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