| # Deep fake detection Django Application | |
| ## Requirements: | |
| **Note :** Nvidia GPU is mandatory to run the application. | |
| - CUDA version >= 10.0 for GPU | |
| - GPU Compute Capability > 3.0 | |
| You can find the list of requirements in [requirements.txt](https://github.com/abhijitjadhav1998/Deepfake_detection_using_deep_learning/blob/master/Django%20Application/requirements.txt). Main requirements are listed below: | |
| ``` | |
| Python >= v3.6 | |
| Django >= v3.0 | |
| ``` | |
| ## Directory Structure | |
| - ml_app -> Directory containing code in views.py file | |
| - project_settings -> Contains Django settings and files to run in production | |
| - static -> Contains all css, js and json files (for face-api) | |
| - templates -> Template files for HTML | |
| <b>Note:</b> Before running the project make sure you have created directories namely <strong>models, uploaded_images, uploaded_videos</strong> in the project root and that you have proper permissions to access them. | |
| # Running application on Docker | |
| #### Step 1: Install docker desktop and start the Docker daemon | |
| #### Step 2: Run the deepfake detection docker docker image | |
| ``` | |
| docker run --rm --gpus all -v static_volume:/home/app/staticfiles/ -v media_volume:/app/uploaded_videos/ --name=deepfakeapplication abhijitjadhav1998/deefake-detection-20framemodel | |
| ``` | |
| #### Step 3: Run the Ngnix reverse proxy server docker image | |
| ``` | |
| docker run -p 80:80 --volumes-from deepfakeapplication -v static_volume:/home/app/staticfiles/ -v media_volume:/app/uploaded_videos/ abhijitjadhav1998/deepfake-nginx-proxyserver | |
| ``` | |
| #### Step 4: All set now launch up your application at [http://localhost:80](http://localhost:80) | |
| ### Step 5: Star⭐ this repo 😉 on <a href="https://github.com/abhijitjadhav1998/Deepfake_detection_using_deep_learning" > <img src="https://img.shields.io/badge/GitHub-100000?style=for-the-badge&logo=github&logoColor=white" /> </a> and Star⭐ this image on <a href="https://hub.docker.com/r/abhijitjadhav1998/deefake-detection-20framemodel"> <img src="https://img.shields.io/badge/Docker-2CA5E0?style=for-the-badge&logo=docker&logoColor=white" /> </a> | |
| ## We deserve a Coffee ☕ <a href="https://www.buymeacoffee.com/abhijitjadhav" target="_blank"><img src="https://www.buymeacoffee.com/assets/img/custom_images/orange_img.png" alt="Buy Me A Coffee" style="height: 35px !important;width: 174px !important;box-shadow: 0px 3px 2px 0px rgba(190, 190, 190, 0.5) !important;-webkit-box-shadow: 0px 3px 2px 0px rgba(190, 190, 190, 0.5) !important;" ></a> | |
| Please note that currently we have only pushed the image of 20 Frames model, If you can to create your own image of other frames model follow the steps given in the [blog](https://abhijithjadhav.medium.com/dockerise-deepfake-detection-django-application-using-nvidia-cuda-40cdda3b6d38). | |
| # Running application locally on your machine | |
| ### Prerequisite | |
| 1. Copy your trained model to the models folder. | |
| - You can download our trained models from the [Google Drive](https://drive.google.com/drive/folders/1UX8jXUXyEjhLLZ38tcgOwGsZ6XFSLDJ-?usp=sharing) or you can train your models using the steps mentioned in Model Creation directory. | |
| #### Step 1 : Clone the repo and Navigate to Django Application | |
| `git clone https://github.com/abhijitjadhav1998/Deepfake_detection_using_deep_learning.git` | |
| #### Step 2: Create virtualenv (optional) | |
| `python -m venv venv` | |
| #### Step 3: Activate virtualenv (optional) | |
| `venv\Scripts\activate` | |
| #### Step 4: Install requirements | |
| `pip install -r requirements.txt` | |
| #### Step 5: Copy Models | |
| `Copy your trained model to the models folder i.e Django Application/models/` | |
| - You can download our trained models from [Google Drive](https://drive.google.com/drive/folders/1UX8jXUXyEjhLLZ38tcgOwGsZ6XFSLDJ-?usp=sharing) | |
| **Note :** The model name must be in specified format only i.e *model_84_acc_10_frames_final_data.pt*. Make sure that no of frames must be mentioned after certain 3 underscores `_` , in the above example the model is for 10 frames. | |
| ### Step 6: Run project | |
| `python manage.py runserver` | |
| ## Demo | |
| ### You can watch the [youtube video](https://www.youtube.com/watch?v=_q16aJTXVRE&t=823s) for demo | |
| <p align="center"> | |
| <img src="https://github.com/abhijitjadhav1998/Deepfake_detection_using_deep_learning/blob/master/github_assets/fakegif.gif" /> | |
| </p> | |