Unique Human Detection and Tracking in Videos

This project implements a system to detect and count unique humans in video footage using the YOLO (You Only Look Once) object detection model and object tracking techniques. The goal is to ensure that each person is counted only once, even if they reappear in different frames.

Features

Human Detection: Uses YOLOv3 for real-time human detection.

Unique Human Counting: Ensures that each person is counted only once throughout the video.

Tracking: Utilizes tracking algorithms to maintain identity across frames.

Requirements

• Python 3.6 or higher
• OpenCV
• NumPy
• SciPy
• Matplotlib
• Imutils

Model Files

Ensure you have the following model files:

• yolov3.weights - Pre-trained YOLOv3 weights.
• yolov3.cfg - YOLOv3 configuration file.
• coco.names - File containing the class labels for YOLO (e.g., person).

Download these files from the YOLO website or the official YOLO repository.