Udemy

Complete Face Recognition Using SQL Database Project 2025

立即報名
  • 10,023 名學生
  • 更新於 5/2025
4.1
(70 個評分)
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課程資料

報名日期
全年招生
課程級別
學習模式
修業期
1 小時 14 分鐘
教學語言
英語
授課導師
ARUNNACHALAM SHANMUGARAAJAN
評分
4.1
(70 個評分)

課程簡介

Complete Face Recognition Using SQL Database Project 2025

Face Recognition Project Step-by-Step | Real-World Face Recognition Project with SQL Database | Master Face Recognition

Complete Face Recognition Using SQL Database Project From Scratch

Course Description:

Welcome to the Face Recognition course – your complete hands-on guide to building a full Face Recognition system using Python and SQL Database integration.

In this project-based course, you’ll learn everything you need to implement Face Recognition from scratch. Whether you're a beginner or someone looking to strengthen your computer vision skills, this course breaks down the entire Face Recognition pipeline in an easy and practical way.

We’ll begin with the fundamentals of Face Recognition, covering facial feature extraction, training models, and detecting faces in real time. Then, we’ll integrate the system with a SQL Database to store and manage user data in your Face Recognition project.


What You Will Learn:

  1. Introduction to Face Recognition:

    • Understand the fundamentals of face recognition technology and its applications.

    • Learn about the importance of databases in storing and managing facial data.

  2. Setting Up the Project Environment:

    • Explore how to set up a SQL database environment on your local machine or server.

    • Install necessary tools and libraries for face recognition integration with SQL.

  3. Creating the Facial Database:

    • Learn how to design and create a SQL database schema for storing facial features.

    • Understand the structure of the database tables and relationships.

  4. Facial Feature Extraction and Encoding:

    • Dive into the process of extracting facial features from images using OpenCV.

    • Explore how to encode and store these features in the SQL database for comparison.

  5. Face Detection and Recognition Algorithms:

    • Implement face detection algorithms to locate faces within images or video streams.

    • Learn about various recognition algorithms such as Eigenfaces, Fisherfaces, and LBPH.

  6. Integration with SQL Database:

    • Establish connections between the face recognition algorithms and the SQL database.

    • Store and retrieve facial features and recognition results efficiently.



Why Enroll:

  • Hands-On Project Development: Engage in a complete project, from database design to user interface development.

  • Practical Skills Application: Apply face recognition algorithms in a real-world scenario using SQL databases.

  • Career Enhancement: Gain valuable experience in a cutting-edge technology field with practical project work.

Embark on this exciting journey to create a comprehensive face recognition system using SQL databases. By the end of this course, you'll have a fully functional project to showcase your skills in face recognition technology and SQL database integration. Enroll now and bring your face recognition project to life!

課程章節

  • 4 個章節
  • 11 堂課
  • 第 1 章 Introduction To Complete Face Recognition Using SQL Database Project
  • 第 2 章 DATASET CREATER MODULE COURSE - FACE RECOGNITION PROJECT
  • 第 3 章 TRAINING MODULE COURSE - FACE RECOGNITION PROJECT
  • 第 4 章 FACE RECOGNITION MODULE COURSE - FACE RECOGNITION PROJECT

課程內容

  • Understand the fundamentals of face recognition technology and its applications.
  • Learn how to design and create a SQL database schema for storing facial features.
  • Dive into the process of extracting facial features from images using OpenCV.
  • Establish connections between the face recognition algorithms and the SQL database.


評價

  • A
    Abubakar Sadiq Muhammad
    5.0

    This is an excellent project. I recommended it to anyone. I have used it and built attendance system for our staff. Thanks sir

  • B
    Bishop Akpabli
    5.0

    GREAT

  • A
    Arun George
    4.5

    it was a godd session, and the language is also understandable

  • S
    Sankalp Sharma
    2.0

    not descriptive

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