Face Recognition in Flutter - Build Smart Apps in Flutter

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Hamza Asif

4:43:23

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1. Introduction

1. Introduction.mp4

02:28

2. How Face Recognition is Performed.mp4

10:49

2. Choose Images from Gallery or capture Images using Camera in Flutter

1. Setting Up a new Flutter Project and Creating Application GUI.mp4

09:31

2. Adding the Library and setting configurations for Android & IOS.mp4

05:12

3. Choosing Images From Gallery In Flutter.mp4

06:00

4. Capturing Images using Camera in Flutter.mp4

03:02

5. Overivew.mp4

03:23

3. Face Recognition With images in Flutter

1. Face Recognition With Images Section Introduction.mp4

04:10

2. Setting Up Face Recognition With Images Project.mp4

05:48

3. Choosing or Capturing Images for Performing Face Recognition in Flutter.mp4

05:17

4. Performing Face Detection in Flutter.mp4

14:07

5. Drawing Rectangles around detected faces on images in Flutter.mp4

08:33

6. Cropping Detected Faces from Images in Flutter.mp4

16:17

7. Removing Rotation of Camera Captured Images in Flutter.mp4

03:57

8. Adding FaceNet Model in Flutter Application.mp4

05:49

9. Setup for IOS.mp4

02:33

10. Analyzing a tflite model.mp4

03:25

11. Passing Cropped Faces to Model and Getting Embeddings in Flutter.mp4

10:01

12. Registering Faces in our Flutter Application.mp4

04:33

13. Face Registration in Flutter Overview.mp4

03:32

14. Storing Registered Faces in Flutter Globally.mp4

02:13

15. Performing Face Recognition in Flutter With Images.mp4

10:24

16. Showing Recognized Names above faces in Flutter.mp4

13:50

17. Face Recognition With Images in Flutter Overview.mp4

02:47

18. Using Mobile FaceNet Model in Flutter for Face Recognition.mp4

03:10

4. Tensorflow Lite in Flutter

1. Loading FaceNet (tflite) model in Flutter.mp4

05:42

2. Passing Input to Face Recognition Model in Flutter and Getting Output.mp4

09:57

3. How Recognition in Performed - Find Nearest Neighbors.mp4

05:04

5. Displaying Live Camera Footage in Flutter

1. Creating new Flutter project and Adding library.mp4

06:58

2. Displaying Live Camera Footage in Flutter.mp4

09:14

3. Live Feed Application Demo.mp4

00:46

4. Camera Package Overview.mp4

01:26

6. Realtime Face Recognition in Flutter

1. Realtime Face Recognition Section Introduction.mp4

03:03

2. Setting Up Realtime Face Recognition Project.mp4

04:16

3. GUI of Realtime Face Recognition Application.mp4

05:05

4. Getting Frames of Live Camera in Flutter.mp4

07:11

5. Switching Between Front and Back Camera in Flutter.mp4

02:28

6. Performing Face Detection With Live Camera Footage in Flutter.mp4

08:29

7. Drawing Rectangles around detected faces in Realtime.mp4

07:18

8. Testing Realtime Face Detection Application.mp4

00:56

9. Face Detector Painter in Flutter.mp4

05:41

10. Cropping faces in Flutter in Realtime.mp4

06:26

11. Adding FaceNet model & Getting Embedding in Realtime.mp4

06:40

12. Performing Realtime Face Registration in Flutter.mp4

05:58

13. Performing Realtime Face Recognition in Flutter.mp4

10:05

14. Testing Realtime Face Recognition Application.mp4

01:36

15. Improving performance of Realtime Face Recognition Application.mp4

02:59

16. Realtime Face Recognition Overview.mp4

05:14

Description

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

What You'll Learn?

Use of Face Recognition models with images and live camera footage
Build Face Recognition based Security & Attendance Systems
Build Face Recognition Based Flutter Application 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

Who is this for?

Beginner Flutter Developers want to Build Face Recognition Based Flutter Applications

Intermediate Flutter App Developers who want to build complete Face Recognition System in Flutter

Expert Flutter Developers who want to increase their Skillset

Anyone who want to build Face Recognition based smart Applications

More details

Description
Hello, and welcome to this exciting course.
In this course, you will learn to integrate Face Recognition Models in Flutter apps with both
Images
Live Camera Footage
Face recognition is the process of identifying people using their faces, and in today's world, it is being used for countless purposes. Like
Security agencies use it to identify and track criminals.
Companies use it to monitor their employees
Educational institutes use it for marking attendance
and so on.
So in this course, you will learn to integrate different face recognition models in Flutter App Development to build smart and powerful applications for both Android & IOS.

Course Curriculum
We will start by learning the basics that how a face recognition model works. So in a face recognition system, there are mainly two parts
Face Registration
Face Recognition
Face Registration
So in face registration, we register the faces so that we can recognize them later. So just like the face unlock feature of your mobile phone firstly we need to register faces so that we can recognize them later. So in this part, we ask the user to scan the face using either images or live camera footage. Once the scan is completed we ask the user to assign a name to that face and we will store that face along with that name in the database.
Face Recognition
And in the face recognition part, we recognize those registered faces. So in this part, once the user scans his face we compare that face with our registered faces using face recognition models. And where the difference between two faces is minimum we consider that registered face as our recognition.

Choosing or Capturing Images in Flutter
After that, we will learn to
Choose Images from Gallery in Flutter
Capture Images using Camera in Flutter
And we will learn that because later we need to pass these images to our face recognition models to register and recognize faces inside our Flutter Application.

Face Recognition With Images in Flutter
In this section, we will start building our first face recognition application in Flutter. So we are going to build an application where users can
Register faces
Recognize faces
by using images from a gallery or camera. And in this application, we will use two different models for performing face recognition in Flutter. And those models are
FaceNet Model
Mobile FaceNet Model

Realtime Face Recognition
After performing face recognition with images and understanding the integration of face recognition models in Flutter we will build a real-time face recognition application in Flutter. So we will register and recognize the faces using frames of live camera footage. So we will
Display the live camera footage in Flutter
Get the frames of live camera footage one by one
Pass those frames to our face recognition model
Recognize and register the faces in real time

Tensorflow Lite
To perform face recognition in Flutter apps we will use the models which are in Tensorflow lite format. TensorFlow lite is the proper format for using Machine Learning models in mobile applications. So during this course, we will also learn about this library.

So after completing this course
You will be able to integrate Face Recognition models in Flutter with both Images & the live camera footage
You can integrate Face Recognition based authentication in Flutter Applications
You can build fully functional Face Recognition based security & attendance systems in Flutter.
So in short this course is a complete cookbook for performing face recognition in Flutter app development. So what are you waiting for? Join the course now and learn the skill which matters the most.
Who this course is for:
Beginner Flutter Developers want to Build Face Recognition Based Flutter Applications
Intermediate Flutter App Developers who want to build complete Face Recognition System in Flutter
Expert Flutter Developers who want to increase their Skillset
Anyone who want to build Face Recognition based smart Applications

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Google Flutter

Hamza Asif

Instructor's Courses

Experienced Mobile Developer, specialized in Mobile Machine Learning using Tensorflow lite, ML Kit, and Google cloud vision API. Leading Android Machine learning instructor with over 50,000 students from 150 countries. I am an enthusiastic developer with a strong programming background and possess great app development skills. I have developed a bunch of native and cross-platform apps in the past and satisfied all of my clients. It has been +4 years doing Mobile development and providing support for Android Applications. Empowering mobile Applications using Machine Learning and Computer vision is my core skill.Powering Android Application with ML really fascinates me. So I learned Android development and then Machine Learning. I developed Android applications for several multinational organizations. Now I want to spread the knowledge I have. I'm always thinking about how to make difficult concepts easy to understand, what kind of projects would make a fun tutorial, and how I can help you succeed through my courses.

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