DeepSafe

DeepSafe - DeepFake Detection made easy

DeepSafe consiste of 3 tools.

WebApp
DeepSafe API
Chrome Extension

WebApp - Live here

This is a limited access app, for the full access contact me.

Clone the repository:

git clone https://github.com/siddharthksah/DeepSafe
cd DeepSafe

Creating conda environment

Python version

Main supported version : 3.8
Other supported versions : 3.7 & 3.9

conda create -n deepsafe python==3.8 -y
conda activate deepsafe

Install dependencies:

pip install -r requirements.txt

Download Model Weights

Service	Google Drive	Mega Drive
Link	Google Drive	Mega Drive

Or you can use Gdown

Installation

pip install gdown

# to upgrade
pip install --upgrade gdown

import gdown

#this takes a while cause the folder is quite big about 3.4G

url = "https://drive.google.com/drive/folders/1Gan21zLaPD0wHbNF3P3a7BzgKE91BOpq?usp=sharing

gdown.download_folder(url, quiet=True, use_cookies=False)

Start the application:

streamlit run main.py

Dockerize the webapp

Container on Docher Hub

#Base Image to use
FROM python:3.7.9-slim

#Expose port 8080
EXPOSE 8080

#Optional - install git to fetch packages directly from github
RUN apt-get update && apt-get install -y git
RUN apt-get install ffmpeg libsm6 libxext6  -y


#Copy Requirements.txt file into app directory
COPY requirements.txt app/requirements.txt

#install all requirements in requirements.txt
RUN pip install -r app/requirements.txt

#Copy all files in current directory into app directory
COPY . /app

#Change Working Directory to app directory
WORKDIR /app

#Run the application on port 8080
ENTRYPOINT ["streamlit", "run", "main.py", "--server.port=8080", "--server.address=0.0.0.0"]

Building the Docker Image

docker build -f Dockerfile -t app:latest .

Running the docker image and creating the container

docker run -p 8501:8501 app:latest

Getting the image to Docker Hub

After you made your own Docker image, you can sign up for an account on https://hub.docker.com/. After verifying your email you are ready to go and upload your first docker image.

Log in on https://hub.docker.com/
Click on Create Repository.
Choose a name (e.g. verse_gapminder) and a description for your repository and click Create.
Log into the Docker Hub from the command line

docker login --username=yourhubusername --email=youremail@company.com

just with your own user name and email that you used for the account. Enter your password when prompted. If everything worked you will get a message similar to

WARNING: login credentials saved in /home/username/.docker/config.json
Login Succeeded

Check the image ID using

docker images

and what you will see will be similar to

REPOSITORY              TAG       IMAGE ID         CREATED           SIZE
verse_gapminder_gsl     latest    023ab91c6291     3 minutes ago     1.975 GB
verse_gapminder         latest    bb38976d03cf     13 minutes ago    1.955 GB
rocker/verse            latest    0168d115f220     3 days ago        1.954 GB

and tag your image

docker tag bb38976d03cf yourhubusername/verse_gapminder:firsttry

The number must match the image ID and :firsttry is the tag. In general, a good choice for a tag is something that will help you understand what this container should be used in conjunction with, or what it represents. If this container contains the analysis for a paper, consider using that paper’s DOI or journal-issued serial number; if it’s meant for use with a particular version of a code or data version control repo, that’s a good choice too - whatever will help you understand what this particular image is intended for.

Push your image to the repository you created

docker push yourhubusername/verse_gapminder

Deploy WebApp on Google Cloud

Build and deploy

Command to build the application. Please remeber to change the project name and application name

gcloud builds submit --tag gcr.io/<ProjectName>/<AppName>  --project=<ProjectName>

Command to deploy the application

gcloud run deploy --image gcr.io/<ProjectName>/<AppName> --platform managed  --project=<ProjectName> --allow-unauthenticated

If you are new to GCP - Follow the steps below -

Activate gcloud Command Line Tool and Push Local Image to GCP

To install the app on Google Cloud, need to have account and gcloud tool installed in the system. Initiate GCloud

gcloud init

Set Project,Billing, Service Account and Region and Zone exmaple to set Region as Mumbai India...

gcloud config set compute/region asia-south1
gcloud config set compute/zone asia-south1-b

Enable Container Registry and Cloud Run Api run the following command in glocud terminal

gcloud services enable run.googleapis.com containerregistry.googleapis.com

Push Local Image to GCP Cloud Container Registry Following command will allow local docker engine tobe used by gcloud tool

gcloud auth configure-docker

Following step will create a tag of the local image as per gcp requirment.

docker  tag st_demo:v1.0  gcr.io/< GCP PROJECT ID > /st_demo:v1.0

Push Local Image to GCP Registry

docker push gcr.io/< GCP PROJECT ID > /st_demo:v1.0

Finally ! Deploy on Serverless Cloud Run Run the following Single Line command to deploy / host the app.

gcloud run deploy < service name >  --image < gcp image name>   --platform managed --allow-unauthenticated --region < your region > --memory 2Gi --timeout=3600

< service name >          : Service Name User Supplied 
< gcp image name>         : Image Pushed into GCP 
< your region >           : Region was set at the Gcloud Init.
< platform managed >      : GCP Specific Parameter, consult GCP Manual for further details.
< allow-unauthenticated > : GCP Specific Parameter, consult GCP Manual for further details.
< memory >                : Memory to be allocated for the container deployment.
< timeout >               : GCP Specific Parameter, consult GCP Manual for further details. For streamlit deployment, this value should be set to a high value to avoid a timeout / connection error.