Automatic Attendance

How To Build

Download source project

git clone https://github.com/chautruonglong/NHOM_14.git

Recognition - Facenet

• Requires:

  	Linux OS	Window OS
  Python	3.6.*	3.6.*
  SVM
  KNN
  FAISS

  Note: You should use Anaconda tool to fast setup enviroment

• Move to dir "NHOM_14/Recogniton-AI/Face-Recognition/":

  cd NHOM_14/Recogniton-AI/Face-Recognition/

• Crawl data:

  • Using these modules in folder "NHOM_14/Recogniton-AI/Data-Processing" to crawl face images
  • Put them in folder "NHOM_14/Recogniton-AI/Face-Recognition/dataset/raw/"

• Install packages:

  pip install -r requirements/requirements_pip.txt

  conda install --file requirements/requirements_conda.txt

• Preprocessing data:

  python src/preprocessing.py

• Training Classifier Model:

  python src/training.py

• Test:

  Option	Command
  Webcam	python src/webcam.py python src/webcam_faiss.py
  Video	python src/video.py python src/video_faiss.py
  Image	python src/image.py python src/image_faiss.py

Server Side - Backend

• Requires:

  	Linux OS	Window OS
  Python	3.6.*	3.6.*
  SVM
  KNN
  FAISS

  Note: You should use Anaconda tool to fast setup enviroment

• Move to dir "NHOM_14/Backend-API/backend_api/":

  cd NHOM_14/Backend-API/backend_api/

• Install packages:

  pip install -r requirements.txt

• Run server:

  Note: First, create database follow name "automatic_attendance" using MySQL (XAMPP or Main Website)

  python manage.py runserver 0.0.0.0:8000

Raspberry (option)

Note: Using SSH protocol to remote raspberry

• Move to dir "NHOM_14/Raspberry-Camera/raspberry/":

  cd NHOM_14/Raspberry-Camera/raspberry/

• Install packages:

  pip install -r requirements.txt

• Run raspberry server:

  python manage.py runserver 0.0.0.0:8000

Client Side - Mobile

• Requires:

  OS	Window OS
  IDEs	Visual Studio 2019
  Devices	Virtual Machine or Mobile
  Android API	API 27

• Install Visual Studio IDE:

• Open folder "NHOM_14/Mobile-App/Mobile/AutoAttendant.sln" with Visual Studio IDE

• Build it on Virtual Machine or Mobile Device

System Overview

Mobile App

Login

Activities

Recognition System

Database Diagram

Server API

Raspberry API