Anomaly Detection

This is an anomaly detection app built using TensorFlow 2, Django 3, Django REST Framework 3, React 18, and Material UI 5. The app uses a machine learning model built in TensorFlow and trained on the MNIST dataset to recognize handwritten digits.

Table of Contents

• Prerequisites
• Installation
• Running the application
• Copyright and License

Prerequisites

Install the following prerequisites:

1. Python
2. Node.js
3. Visual Studio Code

Installation

1. Create a virtual environment

From the root directory run:

cd backend

python -m venv venv

2. Activate the virtual environment

From the backend directory run:

On macOS:

source venv/bin/activate

On Windows:

venv\scripts\activate

3. Install required backend dependencies

From the backend directory run:

pip install -r requirements.txt

4. Run migrations

From the backend directory run:

python manage.py makemigrations

python manage.py migrate

5. Install required frontend dependencies

From the root directory run:

cd frontend

npm install

Run the application

To run the application, you need to have both the backend and the frontend up and running.

1. Run backend

From the backend directory run:

python manage.py runserver

2. Run frontend

From the frontend directory run:

npm start

3. View the application

Go to http://localhost:3000/ to view the application.

Copyright and License

Copyright © 2022 Hieu Le Cong Minh