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Attendance via Face Recognition

Overview

Attendance via Face is a system that automates attendance tracking using facial recognition technology. This project leverages Next.js for the front end and integrates various technologies to provide a seamless experience.

Features

  • Facial Recognition: Uses advanced algorithms to identify and verify faces.
  • Real-time Attendance: Automatically logs attendance as individuals are recognized.
  • User Management: Manage user profiles and attendance records efficiently.

Getting Started

Prerequisites

  • Node.js
  • npm or yarn

Installation

  1. Clone the repository:
    git clone https://github.com/Kuldeepsinghrajpoot/Attendance-via-Face.git
    cd Attendance-via-Face
  2. Install dependencies:
    npm install
    # or
    yarn install

Running the Application

  1. Start the development server:
    npm run dev
    # or
    yarn dev
    
  2. Open your browser and navigate to http://localhost:3000.
  3. Replace .env.temp with .env and update the file with the basic requirements they are asking for.

Technologies Used

Frontend

  • Next.js
  • React
  • Tailwind CSS

Programming Language

  • TypeScript
  • Python

Backend

  • Next.js
  • Rest API
  • FastAPI
  • ORM: Prisma
  • Database: MongoDB

ML Portion

Dependencies

Run server

install all the required dependencies then run :

uvicorn app:app --reload

##If you encounter issues installing face_recognition due to missing dependencies like dlib, you can try installing it manually. Follow these steps:

  1. Clone the Dlib Windows Python3.x repository from z-mahmud22/Dlib_Windows_Python3.x.
    git clone https://github.com/z-mahmud22/Dlib_Windows_Python3.x.git
  2. Navigate to the cloned repository.
    cd Dlib_Windows_Python3.x
  3. Install dlib using pip.
    pip install dlib-19.21.99-cp39-cp39-win_amd64.whl
  4. Replace dlib-19.21.99-cp39-cp39-win_amd64.whl with the appropriate wheel file for your Python version and architecture.

Once dlib is installed, you can proceed to install face_recognition

Replace dlib-19.21.99-cp39-cp39-win_amd64.whl with the appropriate wheel file for your Python version and architecture.

Once dlib is installed, you can proceed to install face_recognition

Run once again file

uvicorn app:app --reload

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