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Swimmer Detection Using YOLO Algorithm

Swimmer detection application implemented in Python using the YOLO algorithm. The application includes a frontend served with a simple HTTP server and a Flask server that utilizes the model to detect swimmers in images or videos.

swimmer detection

Features

  • YOLO Algorithm: Utilizes the YOLO (You Only Look Once) algorithm for real-time object detection, specifically trained to detect swimmers.
  • Interactive Frontend: The frontend interface allows users to upload images or videos and view the detection results in real-time.
  • Flask Server: A Flask server processes the uploaded media and applies the YOLO model to detect swimmers, providing results back to the frontend.
  • Simple HTTP Server: The application frontend is served using a simple HTTP server command for easy setup and access.
  • Efficient Detection: The model is optimized for high accuracy and performance, making it suitable for real-time detection scenarios.

Requirements

  • Python 3.x
  • Flask Library
  • YOLO Model Files

How To Use

Clone this repository

$ git clone https://github.com/DBDoco/yolo-swimmer-detection.git

Install required libraries

$ pip install -r requirements.txt

Start the Flask server

$ python flask_server.py

Start the frontend server

$ python -m http.server

Access the application by navigating to http://localhost:8000 in your web browser. After that you can upload images and videos through the UI. Processed images or videos will be saved to the 'processed' folder.