Keras Flask Deploy Webapp

Abstract

1. Introduction

A minimal and customizable repo to deploy your image models as web app easily.

2. Objective

:smiley_cat: Pretty & simple image classifier app template. Deploy your own trained model or pre-trained model (VGG, ResNet, Densenet) to a web app using Flask in 10 minutes.

This project demonstrates how JavaScript, Keras, TensorFlow can be applied to a real-world Full Stack Web Development problem.

3. Key Features / Modules

• Enhanced, mobile-friendly UI
• Support image drag-and-drop
• Use vanilla JavaScript, HTML and CSS. No jQuery or Bootstrap
• Switch to TensorFlow 2.x and tf.keras by default
• Upgrade Docker base image to Python 3.11

4. Technology Stack

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

• Node.js (LTS) and npm
• A modern web browser
• VS Code or any code editor
• Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/imfing/keras-flask-deploy-webapp.git
cd keras-flask-deploy-webapp

1. Quick run with Docker:
2. Go to http://localhost:5000 and enjoy

docker run --rm -p 5000:5000 ghcr.io/imfing/keras-flask-deploy-webapp:latest

# 1. First, clone the repo
$ git clone https://github.com/imfing/keras-flask-deploy-webapp.git
$ cd keras-flask-deploy-webapp

# 2. Install Python packages
$ pip install -r requirements.txt

# 3. Run!
$ python app.py

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

• Add role-based access control
• Deploy on a VPS or cPanel hosting with a custom domain
• Add automated tests and a CI pipeline

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

1. Explain the frontend, backend and database layers of this application.
2. How is user authentication and authorisation implemented?
3. Describe the main database tables / collections and their relationships.
4. Which REST APIs or routes are exposed and what do they return?
5. How would you deploy this application to production?

9. Source Code & License

This project is developed by imfing and published on GitHub under the Apache License 2.0. Please follow the license terms and credit the original author when you use or modify this code.