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    Complete Face Recognition Attendance Software| Python Opencv

    Posted By: ELK1nG
    Complete Face Recognition Attendance Software| Python Opencv

    Complete Face Recognition Attendance Software| Python Opencv
    Published 1/2023
    MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
    Language: English | Size: 3.06 GB | Duration: 4h 12m

    Build complete Machine Learning face recognized attendance entry software using Python Pyqt OpenCV SQLite & Qt Designer

    What you'll learn

    Master the Python GUI programming language by developing a software for face recognition attendance entry with machine learning algorithm using python coding

    Add this project in your Portfolio or in your resume for python GUI developer jobs . you will learn complete step by step codes to develop this app.

    Design beautiful interfaces for data science, machine learning, deep learning and IOT projects to show data, images and hover effects using pyqt and qt designer

    You will be able to develop a filly functioning face recognition application for any business using Python, Qt Designer, SQLite Database using OpenCV

    You will be able to design SQLite database, tables for any application you want to develop yourself

    Able to design beautiful interfaces (GUIs) for any application in Qt Designer. You will learn how to create style sheets for each control in qt designed forms

    You will be able to connect the front end and back end using Python code. The use of try and except are implemented to track connections with SQLite database

    Learn the database operations like INSERT, SELECT and UPDATE in SQLite database using this project.

    You will learn how to download face recognition algorithm and how to implement in opencv to detect faces from the web cam video and draw rectangles in faces

    You will learn how create training datasets using webcam captured images and create folders to store each members captured images for verification

    Requirements

    Basic python programming knowledge is enough

    Need a laptop or desktop computer with internet connection

    Description

    Hello Students  Welcome to the course Complete Face Recognition attendance software using Python, Pyqt5,  OpenCv and Machine Learning using Qt Designer with SQLite databaseIn this course you will learn how to create a complete software to implement face recognition attendance system for a company or for a business to record daily attendance.First you will learn how to install the required software for our project PythonPyqt5Pyqt5-toolsOpen CvVs CodeDb BrowserThen you will learn how to create beautiful interfaces for the following processLogin processTraining processFace recognition attendance entry processReports processIn the interface creation process you will learn how to create controls for our requirementsQLabel QTabWidgetQPushButtonQLineEditQTableWidgetQDateEditQFrameThe main process you will learn while designing the forms How to provide images How to  fit images properly with QLabel How to capture passwords using Python GUI window.How to provide styles to all controls How to provide hover effects to controls in the  qt designer.Connect Qt Designer ui file with PythonThen you will learn how to connect python code with pyqt5 designed GUI using QT Designer.Create and connect SQLiteThen you will learn how to create sqlite3 database and tables using python code and check the database with db browser.These are the following modules we will develop in this project.1. Login ModuleIn this module, the admin will enter the password to enter into the system. The the python code will check if the entered password is correct or not. If it is correct, it will open the next form. We will use python if condition and user defined functions to check login. 2. Training ModuleIn this module, the admin will use haarcascade_frontalface_default.xml file to detect the human face shown in the webcam. The camera is capture is created using OpenCv. The captured image contverted to gray scale and Cascade Classifier algorithm will detect any face available in the captured image. If face is available, it will automatically create a directory and store the faces in 1.png, 2.png…. like that till the given number for training. If the face is not detected, then the system will not save the image file.3. Attendance ModuleThe member will show their face in the web cam. Now the system will create a LBPHFaceRecognizer model using cv2 library and this model will be trained using the existing dataset we already created image and label set. Then this model will predict with the web cam face and if the person is there in the trained database, it will record the attendance for the person. The attendance will be recorded only if the person is showing their face first time in the current date. If the person is showing their face more than one time, the system will not record the attendance. If a new person is showing their face, it will show unknown person message.4. Reports ModuleIn the reports module, the system will show the attendance records of all the day. The admin can select a particular date from the date select control, the system will show the attendance for the selected date.By doing this course, you will learn how to create a complete python GUI project using face recognition of OpenCV Library and use LBPHFaceRecognizer model. You will also learn how to create database, tables and insert records from the user interface. You will learn how to generate reports from the database and how to connect GUI and python code.Thank you for your interest in this course…I will see you in the course…

    Overview

    Section 1: Introduction

    Lecture 1 Introduction

    Lecture 2 Install Python

    Lecture 3 Install Pyqt5 and pyqt5-tools

    Lecture 4 Install Open CV library

    Lecture 5 Install visual studio code ( Optional ) - You can use any editor

    Lecture 6 Create Desktop shortcut to Qt Designer

    Lecture 7 Install Sqlite Browser

    Section 2: Resources download for form designs

    Lecture 8 Image files download

    Section 3: Login form design

    Lecture 9 Login form design

    Section 4: Main Form design

    Lecture 10 Main form design

    Section 5: Training form design

    Lecture 11 Training form design

    Section 6: Face recognition attendance entry form design

    Lecture 12 Face recognition attendance entry form design

    Section 7: Reports form design

    Lecture 13 Reports form design

    Section 8: Download the ui file

    Lecture 14 Download ui file

    Section 9: Code to connect ui file with python

    Lecture 15 Code to connect ui file with python

    Section 10: Login and logout code

    Lecture 16 Login code

    Lecture 17 Logout code

    Lecture 18 All form link button code

    Section 11: Algorithm xml file download

    Lecture 19 Algorithm file download

    Section 12: Training Process

    Lecture 20 Develop python code to provide training to the model

    Section 13: Face recognition attendance entry

    Lecture 21 Attendance entry process - training the model with existing dataset

    Lecture 22 Attendance entry process - code for face recognition

    Lecture 23 Attendance entry process - code to save the attendance record in the table

    Section 14: Reports generation

    Lecture 24 Attendance reports generation code

    Lecture 25 Develop code go generate date wise attendance reports

    Section 15: Removing the tab and frames in QTabWidget

    Lecture 26 Remove the tab titles and borders of tab widget

    Section 16: Complete code to download

    Lecture 27 User interface file

    Lecture 28 Python file

    If you are a student or a developer want to develop a complete advanced python software from the beginning to end,If you know basics of python programming and want to improve your skills in python GUI programming and Computer Vision (OpenCv),If you are want to convert the python program output into a GUI to present nicely with beautiful images,College students who want to develop their projects themselves in python and machine learning,To show your IOT programming output through GUI in the Computer,To learn how to develop an machine learning application using python programming and opencv library