This is a Streamlit-based Python application for detecting image forgery, deployed using Microsoft Azure and Docker. LIVE URL : https://tsp-image-forgery.azurewebsites.net
This application provides a user-friendly interface for detecting image forgery using various techniques such as image manipulation detection, tampering detection, and deep learning-based approaches. Users can upload an image and the app will analyze it to detect any signs of forgery or manipulation.
- Upload Image: Users can upload an image directly through the app interface.
- Forgery Detection: The app utilizes advanced algorithms to analyze the uploaded image and detect any signs of forgery or manipulation.
- Real-Time Analysis: The forgery detection process is carried out in real-time, providing instant results to the users.
- User-Friendly Interface: The app interface is designed to be intuitive and easy to use, allowing users to analyze images without any technical expertise.
The application is deployed on Microsoft Azure, leveraging its cloud services for hosting and scalability. Azure provides a reliable and secure environment for running the app.
Docker is used for containerizing the application, ensuring consistency in deployment across different environments. Docker simplifies the deployment process and enables easy scaling of the application.
To use the Image Forgery Detection app:
- Visit the deployed URL of the application.
- Upload an image using the provided interface.
- Wait for the analysis to complete.
- View the results indicating whether the image shows any signs of forgery or manipulation.
- Python
- Streamlit
- Azure
- Docker
To run the application locally, follow these steps:
- Clone this repository to your local machine.
- Install the necessary dependencies using
pip install -r requirements.txt. - Run the Streamlit app using
streamlit run FRONTEND.py. - Access the app through the provided local URL.