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

• os
• cv2 (OpenCV)
• numpy (np)
• face_recognition
• FastAPI
• BackgroundTasks
• HTTPException
• CORSMiddleware
• BaseModel (from pydantic)
• base64
• requests

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