Building GANs Application and Deploying it on Streamlit & Heroku

Generative Adversarial Networks (GANs) are a type of deep learning architecture that has become increasingly popular for generating new and realistic data, such as images, videos, and audio.

Building a GAN model is one thing, but deploying it as a user-friendly web application is another challenge altogether. In this article, we will explore how to build and deploy a GAN Streamlit web application on the Heroku platform.

First, we will cover the background and problem statement, set up the working environment, load a pre-trained GAN model and images, and build the Streamlit web application. Then will focus on deploying the application to the Heroku platform and making it accessible to users.

Table of Contents:

1. Background & Problem Statment

2. Setting Up Working Environment

3. Loading Pretrained GAN Model & Images

4. Building Streamlit Web Application

5. Running the Web Application

6. Create a GitHub Repository for Your Application

7. Create a requirements.txt, setup.sh, and Procfile Files

8. Connect to Heroku

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