Face Recognition & Detection in Flutter – 2023 Guide

Use Face Recognition in Flutter with Images & Videos, Security & Attendance Systems in Flutter for Android and IOS

Welcome to an exhilarating journey of mastering Face Recognition and Face Detection Models in Flutter! This comprehensive course empowers you to seamlessly integrate facial recognition & detection into your Flutter apps, harnessing the power of both images and live camera footage.

What you’ll learn

  • Use of Face Recognition & Detection Machine Learning Models in Flutter With Both Images & Videos.
  • Build Face Recognition & Detection based Security & Attendance Systems For both Android & IOS.
  • Build Face Recognition Based Flutter Applications without Any Paid Facial Recognition Service.
  • Use of FaceNet and Mobile FaceNet models in Flutter.
  • Use of Tensorflow Lite models in Flutter for Performing On-Device Face Recognition.
  • Learn to Store Faces in Database for Registration.
  • Use of Google ML Kit library in Flutter for Face Detection.

Course Content

  • Introduction –> 2 lectures • 14min.
  • Choosing or Capturing Images in Flutter –> 5 lectures • 27min.
  • Face Detection With Images in Flutter –> 9 lectures • 49min.
  • Face Recognition With Images In Flutter –> 8 lectures • 55min.
  • Using Tensorflow Lite Models in Flutter for Face Recognition –> 2 lectures • 13min.
  • Storing Registered Faces In Database in Flutter –> 4 lectures • 18min.
  • Displaying Live Camera Footage In Flutter –> 4 lectures • 18min.
  • Realtime Face Detection In Flutter –> 8 lectures • 39min.
  • Realtime Face Recognition In Flutter –> 6 lectures • 26min.

Auto Draft

Requirements

Welcome to an exhilarating journey of mastering Face Recognition and Face Detection Models in Flutter! This comprehensive course empowers you to seamlessly integrate facial recognition & detection into your Flutter apps, harnessing the power of both images and live camera footage.

 

Face recognition has become a pivotal technology used across various industries:

 

– Security agencies employ it for identifying and tracking criminals.

– Companies utilize it to monitor employee activities.

– Educational institutions leverage it for streamlined attendance tracking.

 

In this course, you’ll acquire the skills to integrate diverse face recognition models into Flutter App Development, enabling you to create intelligent and robust applications for both Android and iOS.

 

Course Highlights:

 

Understanding the Basics:

 

Embark on your journey by grasping the fundamental principles behind face recognition models. Explore the two core components of a face recognition system:

 

1. **Face Registration:**

– Learn to register faces through image scans or live camera footage in Flutter.

– Capture and store faces along with user-assigned names in a database in Flutter.

 

2. **Face Recognition:**

– Dive into the process of recognizing registered faces in flutter.

– Utilize face recognition models to compare scanned faces with registered ones in flutter.

 

Image Handling in Flutter:

Discover essential techniques for handling images in Flutter, including:

 

– Choosing Images from Gallery in Flutter

– Capturing Images using Camera in Flutter

 

These skills are crucial for passing images to face recognition models within your Flutter application.

 

Face Recognition With Images in Flutter:

 

Build your first face recognition application in Flutter, allowing users to:

 

– Register faces

– Recognize faces

 

Utilize two distinct models for face recognition in Flutter:

 

1. FaceNet Model

2. Mobile FaceNet Model

 

Real-time Face Recognition:

 

Advance to real-time face recognition applications, registering and recognizing faces using live camera footage frames. Learn to:

 

– Display live camera footage in Flutter

– Process frames one by one with face recognition models in Flutter

– Achieve real-time recognition and registration in Flutter

 

TensorFlow Lite Integration:

 

Master the integration of face recognition models in Flutter using TensorFlow Lite. Explore why TensorFlow Lite is the ideal format for implementing machine learning models in mobile applications.

 

Face Detection:

In face recognition applications before recognizing faces we need to detect faces from images or frames of live camera footage. So for detecting those faces, we are going to use the face detection model of the ML Kit library in Flutter. So in this course, you will also learn to perform face detection in flutter with both images & live camera footage.

 

Course Outcomes:

 

Upon completion of this course:

 

– Integrate Face Recognition & Detection models in Flutter with both Images and live camera footage

– Implement Face Recognition-based authentication in Flutter Applications

– Construct fully functional Face Recognition-based security and attendance systems in Flutter

 

In essence, this course serves as a comprehensive guidebook for mastering face recognition in Flutter app development. Don’t miss out on this opportunity to acquire a skill that truly matters. Join the course now and unlock the potential of Face Recognition in Flutter!

Get Tutorial