Roulette Video Processor

Overview

This project is a proof of concept designed to explore the capabilities of computer vision in the context of object tracking. Using OpenCV and YOLO (You Only Look Once). The implementation includes RouletteWheelTracker and RouletteBallTracker for tracking the roulette wheel and ball, respectively.

Prerequisites

• Python 3.10
• Important: PyTorch must be installed before proceeding with the installation of other dependencies. Visit the official PyTorch website for detailed installation instructions.

Installation

Clone the repository to your local machine:

git clone https://github.com/cbaezp/roulette
cd roulette

After installing PyTorch, install the remaining Python dependencies:

pip install -r requirements.txt

Usage

To run the video processing script, navigate to the repository's root directory and execute:

python roulette.py

Parameters

• VIDEO_PATH: Path to the input video file (e.g., videos/roulette_test.mp4).
• OUTPUT_PATH: Path for the output video file (e.g., output_video.mp4).
• Both, RouletteWheelTracker and RouletteBallTracker have additional parameters that could be updated based on the video, angle, etc.

Customization

You can customize the behavior of the trackers by modifying their initialization parameters in roulette.py.

Components

VideoProcessor

Manages the video processing pipeline, handling frame reading and writing operations.

RouletteWheelTracker

Detects and tracks the roulette wheel in video frames.

RouletteBallTracker

Utilizes YOLO, powered by PyTorch, for the precise tracking of the ball's position and trajectory.

Proof of Concept

This project demonstrates the practical application of computer vision techniques, showcasing object tracking under dynamic conditions.

YouTube

![Check out the youtube video]