Autism Prediction System

This repository contains an Autism Prediction System powered by Machine Learning and deployed using Next.js, FastAPI, and Golang. The project includes:

• A frontend built with Next.js
• A backend in Golang
• A FastAPI server for handling GPU-based ML computations
• A MySQL database

Prerequisites

Ensure you have the following installed:

• Python 3.11
• Virtual Environment (venv)
• MySQL Server
• Golang
• Node.js & npm
• Uvicorn (for FastAPI)

Setup Guide

1. Clone the Repository

git clone https://github.com/kspranav-az/AutismPredictionSystem.git
cd AutismPredictionSystem

2. Set Up the Python Environment

python3.11 -m venv env
source env/bin/activate  # On Windows, use `env\\Scripts\\activate`

3. Install Dependencies

pip install -r requirements.txt

4. Place Model Files

Put all required model files inside the models/ folder (located in the root directory).

5. Add Test Videos

Place test video files in the root directory.

6. Start the FastAPI Server

uvicorn main:app --host 0.0.0.0 --port 8000 --reload

7. Set Up and Run the Frontend

cd frontend
npm install
npm run dev

8. Configure and Run the Backend (Golang)

Edit app.go and update the MySQL DSN connection string:

dsn := "root:2004@tcp(127.0.0.1:3306)/aimed?parseTime=true"

Then, navigate to the backend directory and build/run the Go server:

cd backend
go build
./main

9. Access the Application

Once all servers are running, open your browser and visit:

http://localhost:3000

Notes

• Ensure MySQL is running with the correct credentials before starting the backend.
• Adjust firewall settings if necessary to allow API communication.
• If running on a remote machine, update localhost with the respective IP.

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