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Flutter Face Recognition - Build Attendance & Security Apps (Udemy.com)

Build Face Detection & Recognition Apps in Flutter | Real-Time Camera Integration | AI Models | TFLite | iOS & Android

Created by: Mobile ML Academy by Hamza Asif

Last updated June 2025

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What you will learn

  • Build face recognition apps in Flutter using AI models like FaceNet and MobileFaceNet
  • Perform face detection with Google ML Kit using both images and real-time camera feed
  • Implement real-time face recognition in Flutter using the camera and TensorFlow Lite
  • Capture and process images from gallery and camera in Flutter for face analysis
  • Use TensorFlow Lite to integrate machine learning models in cross-platform mobile apps
  • Develop face-based login and authentication systems for Android and iOS
  • Store and manage registered faces with user names in a Flutter database
  • Create intelligent attendance and security systems powered by face recognition
  • Learn how to display and process live camera frames for real-time AI tasks
  • Master end-to-end flow of AI-powered facial recognition in Flutter app development

How it compares

Against the other 149 rated Udemy courses in Mobile Development on CourseDuck:

  • Rating4.2 out of 5higher than 13% of them
  • Reviews159#77 of 150 by number of reviews
  • Length5 hoursshorter than 67% of them
  • Last updatedJune 2025more recently than 60% of them

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Course Description

Update December 2024 – All libraries and code fully updated for the latest Flutter and TensorFlow Lite versions.

Unlock the power of AI and facial recognition in your mobile apps with this complete hands-on guide to Face Recognition in Flutter! Whether you're a beginner or intermediate Flutter developer, this course will take you from understanding the basics of face detection and recognition to building fully functional, real-world applications using TensorFlow Lite, ML Kit, and the device camera.


What You’ll Learn:

How Face Recognition Systems Work (Face Detection + Face Matching)
Face Registration and Storage using Images & Live Camera Input
Face Recognition using AI Models like FaceNet and Mobile FaceNet
Real-time Face Detection & Recognition in Flutter using Camera Plugin
Image Selection from Gallery & Camera Integration
Use of TensorFlow Lite Models for On-Device Processing
Face Detection using Google’s ML Kit in Flutter
Implementing Face-Based Authentication Systems
Build Real Apps for Security, Attendance, and User Verification


Real-World Applications You’ll Build:

  • Face Recognition Login App (Authentication via Camera)

  • Attendance Tracking App for schools and workplaces

  • Surveillance-Style App with real-time detection and recognition

  • Face Database Management with user registration & name mapping


Technologies & Tools Covered:

  • Flutter (Cross-platform mobile framework)

  • TensorFlow Lite (For running ML models on-device)

  • MobileFaceNet & FaceNet Models (Pre-trained models for recognition)

  • ML Kit Face Detection (Google's fast and reliable API)

  • Camera Plugin & Image Picker (Capture & load images easily)


Who Should Enroll?

  • Flutter Developers interested in integrating Machine Learning

  • AI Enthusiasts looking to build Face Recognition mobile apps

  • App Developers building secure login/authentication systems

  • Anyone interested in AI-powered camera apps with real-world utility


By the End of This Course, You Will Be Able To:

  • Build and deploy AI-powered Face Recognition apps on iOS & Android

  • Use TensorFlow Lite models in real-time with live camera footage

  • Detect and recognize faces in both images and video frames

  • Create face-based user verification and attendance apps

  • Master image input pipelines and real-time processing in Flutter


Don't miss this opportunity to master face recognition in Flutter, a must-have skill in today’s AI-driven mobile development landscape. Enroll now and start building powerful, intelligent apps that stand out!

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Instructor Details

Mobile ML Academy by Hamza Asif

Hi, I'm Hamza Asif.

I am passionate about teaching people the use of Machine Learning and AI in Android, IOS, and Flutter Applications. I have taught over 55,000 students in 170 countries worldwide.

I have extensive experience in Mobile App Development & Data Science.

My goal is to make you a great developer who can build ML & AI-powered NextGen applications.


If you are interested in Flutter App Development, I offer the following NextGen Flutter courses

Face Recognition and Detection in Flutter - The 2024 Guide

Machine Learning for Flutter - The Complete Flutter ML Guide

Build A Gallery App in Flutter With Circle To Search Feature

Train Object Detection & Image Classify models for Flutter

ChatGPT & Flutter -Build AI based Smart Apps in Flutter

Flutter & ML : Train Tensorflow Lite models for Flutter Apps


If you are interested in Android App Development using Java & Kotlin, I offer the following NextGen Android Courses

Face Recognition and Detection in Android- The 2024 Guide

Android & ML: Train Tensorflow Lite models for Android Apps

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Reviews

4.2

159 ratings on Udemy

Select a bar to show only those reviews.Select the bar again to show every rating.

By Carlos Eduardo Pacheco on 10/4/2024

O curso em si faz o que e proposto, porém a dinâmica é confusa e boa parte das aulas tudo já está pronto, dando pouca noção ao espectador de como é realizado todo o procedimento

By Mailene Gabriela Alpuche Velazquez on 9/16/2024

Muy bueno, todo esta muy claro y los pasos son simples.

By Yuri Barduchi Robin on 8/23/2024

Era o que eu esperava, um passo a passo detalhado de como realizar reconhecimento facial e detecção de faces em Flutter. Um diferencial seria se aprofundar mais nas diferentes opções do Interpretador, na validação de velocidade do reconhecimento e na diferença entre modelos de IA usados, bem como um aprofundamento na conversão destes modelos.

By Marco Aurelio Velazquez Velazco on 7/4/2024

Excelente curso, todo muy claro y preciso.

By Mou Rani Biswas on 5/25/2024

Thank you letting us understand the other properties of Facial Recognition of ML kit. Great explanation.

By Thamizharaasan Chandran on 5/24/2024

It is really helpful Well explained

By Ronakumar Bhesaniya on 4/15/2024

some device not working and this code wrong recognize

By Muham'mad Ady Saputra on 2/19/2024

Its work and tutorial latest is easy to learn

By Shahzaib on 1/10/2024

Something i was looking for a long time

By Joel Achi on 1/3/2024

Yeah it was, I can't wait to get to the end of it

Showing all 10 reviews on CourseDuck

Read all 159 reviews on Udemy

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Overall Score : 84 / 100