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Live-Object-Detection-with-Camera

Nathaniel Handan

Nathaniel Handan

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The "Live Object Detection with YOLO and OpenCV" project is a real-time object detection system that utilizes the YOLO (You Only Look Once) model and the OpenCV library to perform live object detection on a camera feed. This project aims to showcase the potential of real-time object detection and in ...learn more

Project status: Under Development

Artificial Intelligence

Intel Technologies
Intel CPU

Code Samples [1]

Overview / Usage

Main Objectives:

  • Real-Time Object Detection: Detect and identify various objects in a live video stream in real-time.
  • YOLO Model Integration: Utilize the speed and accuracy of the YOLO model for efficient object detection.
  • OpenCV Visualization: Visualize the detected objects with bounding box annotations using OpenCV.
Key Features
  • Efficiency: The YOLO model enables fast and reliable object detection in real-time, suitable for various applications.
  • Customization: Users can adjust the confidence threshold, modify annotation styles, and select specific object classes for detection.
  • Ease of Use: The code is user-friendly, with comprehensive documentation to guide users in setup and customization.
  • Versatility: The live object detection system can be used for security, surveillance, traffic monitoring, and interactive installations.

Methodology / Approach

Installation and Setup

To get started with the project, follow the installation and setup instructions in the Installation Guide. This will help you set up the necessary environment and install required dependencies.

Usage
  1. Make sure you have followed the installation instructions.
  2. Run the Jupyter notebook "demo.ipynb" to start the live object detection demo.
  3. Your webcam or connected camera will display a live video stream with object detection annotations.
  4. Press the 'q' key to stop the program and close the video window.

Technologies Used

Prerequisites
  • Python 3.6 or higher is required to run the code.
  • Ensure you have a webcam or any camera connected to your computer for live video feed.

Repository

https://github.com/Tinny-Robot/Live-Object-Detection-with-Camera.git

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