Tracify2.0 : Real Time Object Tracking and Tracing

Tracify2.0 is the updated version of Tracify where some feature are added :-

• Multiple object tracking at single frame / previous version is detecting only single object
• Trace the path of object till Multiple frames
• YOLOv9 is used here previous version was based on YOLOv5

Introduction

Tracify 2.0 utilizes computer vision techniques for real-time object detection and tracking with YOLOv9 and DeepSORT algorithms. With Tracify, you can monitor and track objects or individuals within a specified area with high accuracy and efficiency.it is versatile surveillance system that combines object detection and multi-object tracking (MOT) to provide enhanced security and monitoring capabilities.

Features

• Real-time Object Detection: Tracify employs YOLOv5, a highly efficient object detection model, to detect objects in real-time from various input sources such as webcams, video files, or live streams.

• Multi-object Tracking (MOT): DeepSORT is integrated into Tracify to perform multi-object tracking, allowing the system to track multiple objects simultaneously across consecutive frames with high accuracy.

• Customizable Configuration: Tracify offers customizable configuration options, allowing users to adjust parameters such as confidence thresholds, NMS thresholds, and more to suit their specific requirements.

Installation

Prerequisites

Before installing Tracify, ensure you have the following prerequisites installed:

• Python 3.10
• Git
• Requirements specified in requirements.txt
• PyTorch
• Conda

Installation Steps

1. Clone the Repository:

Clone the Tracify repository to your local machine using Git:

   git clone https://github.com/AwnishRanjan/Tracify2.0.git
   cd Tracify
   pip install -r requirements.txt