Object Tracking in Videos using Computer Vision

This project focuses on tracking objects within video sequences using computer vision techniques. The goal is to detect and follow objects (such as a football or players) across frames to analyze their movements and interactions.

Features

• Track multiple objects in real-time within video footage.
• Utilize algorithms such as Kalman Filters, Mean Shift, or Deep Learning-based trackers.
• Visualize tracking results with bounding boxes and object IDs.
• Applicable to various scenarios including sports analysis, security surveillance, and more.

Installation

To set up this object tracking project on your local machine, follow these steps:

1. Clone the Repository

   git clone https://github.com/username/object-tracking.git
   cd object-tracking

2. Set Up Virtual Environment (Optional but Recommended)

   python3 -m venv venv
   source venv/bin/activate   # On Windows: venv\Scripts\activate

3. Install Required Packages

   pip install -r requirements.txt

Usage

To start the object tracking system, provide a video file or stream and run the tracking script:

python object_tracking.py --input  --output