/object-detection

A client side object detecting application, which scans through images and identify the various objects.

Primary LanguageTypeScript

Client-Side Object Detector

Overview

This application is a client-side object detector built using TensorFlow, Next.js, and TypeScript. It leverages modern web technologies to provide real-time detection of various objects through the user's webcam. Additionally, it checks for microphone availability, internet speed, and surrounding light conditions to ensure optimal performance.

Table of Contents

Features

  • Real-time Object Detection: Utilizes TensorFlow.js to perform object detection directly in the browser.
  • Webcam Availability Check: Ensures the user has a working webcam before proceeding.
  • Microphone Check: Verifies if a microphone is available for audio input.
  • Internet Speed Test: Measures the user's internet speed to ensure the application runs smoothly.
  • Ambient Light Check: Analyzes the surrounding light conditions to adjust the detection settings accordingly.
  • Responsive Design: Fully responsive and works across various devices and screen sizes.

Installation

Prerequisites

  • Node.js (>=14.x)
  • npm or yarn

Steps

  1. Clone the repository:

    git clone https://github.com/CodeBstack/object-detection.git
cd object-detection

  2. Install dependencies:

    npm install
# or
yarn install

  3. Run the development server:

    npm run dev
# or
yarn dev

  4. Open your browser and navigate to:

    http://localhost:3000

Usage

Starting the Application

  • Once the application is running, it will prompt you to grant access to your webcam and microphone.
  • After granting permissions, the application will perform an internet speed test and check the ambient light conditions.
  • If all checks are passed, the object detection will start automatically.

Object Detection

  • The application will display a live feed from your webcam.
  • Detected objects will be highlighted and labeled in real-time.

Configuration

  • Configuration settings can be adjusted in the config.ts file.
  • You can modify parameters such as detection sensitivity, minimum internet speed requirement, and more.

Dependencies

  • TensorFlow.js: For running the object detection model in the browser.
  • Next.js: For server-side rendering and static site generation.
  • TypeScript: For type safety and better development experience.
  • React: For building the user interface.

License

This project is licensed under the MIT License. See the LICENSE file for details.