Image-Combination-Using-GAN

This project implements a Generative Adversarial Network (GAN) to combine two images into a new, generated image based on user-uploaded content. The application provides a simple web interface using Flask, allowing users to upload images and receive a combined image as output.

Features

1. Image Upload: Users can upload two images from their local filesystem.
2. Image Processing: The GAN model processes the uploaded images to generate a new image that combines features from both.
3. Downloadable Output: The generated combined image can be downloaded directly from the web interface.
4. Easy Setup: The project is designed to be easily runnable with minimal configuration.

Technologies Used

1. Flask: A lightweight WSGI web application framework for Python.
2. TensorFlow/Keras: For building and training the GAN model.
3. OpenCV: For image processing tasks.
4. HTML/CSS: For the front-end interface

Project Structure