Accident Prediction Web Application

Project Overview

This project, named "Accident Prediction Web Application", aims to utilize video and image processing techniques to predict potential accidents in real-time using live CCTV footage.

Technology Stack

• Backend: Flask(3.0.0) on Python(3.11.7)
• Frontend: NextJs(14.0.4)
• Additional libraries:
  • tensorflow(2.15.0)
  • opencv-python(4.9.0.80)

Key Features

• Uploads video files for non-realtime or offline analysis.
• Captures images from live streaming CCTV feeds.
• Processes captured images and videos using AI models to predict potential accidents.
• Displays prediction results and alerts on the user interface.

Getting Started

• Prerequisites:

  • Python(3.11.7)
  • NodeJs(19.9.0) *or above

• Installation:

  1. Clone the repository (Please make sure you don't clone it on Cloud Storage like OneDrive etc.)

     git clone https://github.com/urikpro64/accident-prediction-rm.git

  2. Install dependencies

     • Backend

     cd backend
     pip install -r requirements.txt

     • Frontend

     cd frontend
     yarn install

     Setup env follow the .env.example in each directory

  3. Running Application

     • Backend

     cd backend
     flask run
     #--------------------------#
     flask --debug run #for debug mode

     • Frontend

     cd frontend
     yarn dev

• Use Docker Compose

  1. Clone the repository (Please make sure you don't clone it on Cloud Storage like OneDrive etc.)

     git clone https://github.com/urikpro64/accident-prediction-rm.git

  2. Running Application (Setup env in docker-compose.yml)

     docker compose up
     #--------------------------#
     docker compose up -d # for detach

Additional Notes

• This project is for educational and research purposes only. It is not intended to be a replacement for professional safety measures or real-world accident detection systems.
• Please refer to the project documentation for more detailed information on:
  • Training and deploying the prediction models.
  • Specific configurations or dependencies.
  • Contributing to the project or reporting issues.