Giter Club home page Giter Club logo

rohitkrishnanm / deepfake_detection_using_deep_learning Goto Github PK

View Code? Open in Web Editor NEW

This project forked from abhijitjadhav1998/deepfake_detection_using_deep_learning

0.0 0.0 0.0 63.93 MB

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.

License: GNU General Public License v3.0

Python 0.06% HTML 0.16% CSS 0.01% Jupyter Notebook 99.77%

deepfake_detection_using_deep_learning's Introduction

Deepfake detection using Deep Learning (ResNext and LSTM)

Please reach out to me on LinkedIn for Step by Step installation YouTube video links.

1. Introduction

This projects aims in detection of video deepfakes using deep learning techniques like ResNext and LSTM. We have achived deepfake detection by using transfer learning where the pretrained ResNext CNN is used to obtain a feature vector, further the LSTM layer is trained using the features. For more details follow the documentaion.

You can also watch this Youtube video to get a better intuition about the project

2. Directory Structure

For ease of understanding the project is structured in below format

Deepfake_detection_using_deep_learning
    |
    |--- Django Application
    |--- Model Creation
    |--- Documentaion
  1. Django Application
    • This directory consists of the django made application of our work. Where a user can upload the video and submit it to the model for prediction. The trained model performs the prediction and the result is displayed on the screen.
  2. Model Creation
    • This directory consists of the step by step process of creating and training a deepfake detection model using our approach.
  3. Documentation
    • This directory consists of all the documentation done during the project

3. System Architecture

4. Demo

You can watch the youtube video for demo

5. Our Results

Model Name No of videos No of Frames Accuracy
model_84_acc_10_frames_final_data.pt 6000 10 84.21461
model_87_acc_20_frames_final_data.pt 6000 20 87.79160
model_89_acc_40_frames_final_data.pt 6000 40 89.34681
model_90_acc_60_frames_final_data.pt 6000 60 90.59097
model_91_acc_80_frames_final_data.pt 6000 80 91.49818
model_93_acc_100_frames_final_data.pt 6000 100 93.58794

6. Contributors

  1. Abhijit Jadhav
  2. Jay Patel
  3. Hitendra Patil
  4. Abhishek Patange

If you need any help regarding the please contact us. We will be happy to help

7. License

License: GPL v3

deepfake_detection_using_deep_learning's People

Contributors

abhijitjadhav1998 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.