What you'll learn
Train Image Recognition models on Custom Datasets & build Flutter Applications
Use Image Recognition models in Flutter with both images & live camera footage
Use popular image classification models in Flutter like MobileNet, EfficientNet & ResNet
Use Image Labeling models of ML Kit in Flutter
Collect datasets for training image classification models
Requirements
Android Studio or Visual Studio Installed in your system
Description
Do you want to Train custom Image Recognition Models Use those models in Flutter Learn the use of popular existing image recognition models in a flutterUse the image labeling feature of ML Kit in Flutterthen welcome to this course. In this course, you will learn the practical implementation of image recognition in flutter. My name is Muhammad Hamza Asif and I am teaching the use of machine learning & computer vision in mobile applications since 2018.Image RecognitionImage recognition is the process of recognizing different entities or things in an image. Like you can recognize animals, plants, food, activities, colors, things, fictional characters, drinks, etc with image recognition.Uses of Image Recognition in AppsProduct categorizationIn e-commerce applications image classification can be used to categorize products based on their visual features, So it is used to organize products into categories for easy browsing.Visual searchImage classification can be used to power visual search in mobile apps, so users can take a picture of an object and then find similar items for sale.Medical diagnosisImage classification can be used in medical apps to diagnose diseases based on medical images, such as X-rays or CT scans.Standalone Recognition SystemsWe can use image classification to build countless recognition applications for performing a number of tasks like we can train a model and build applications to recognizeDifferent Breeds of DogsDifferent Types of PlantsDifferent Species of AnimalsDifferent kinds of precious stonesCourse CurriculumThe course is divided into several sections and each will take you to one step closer to the perfection of using image recognition models in Flutter.Handling Images & Videos In FlutterAs during this course you will learn to use image recognition models with both images & videos. So firstly you will learn to choose images from the gallery and capture images using the camera in Flutter Applications. After that you will learn to display the live camera footage in Flutter. Image Labeling With ML KitAfter handling images and videos we will start with a relatively easy thing which is using image labeling models of ML Kit in Flutter for performing image recognition. So we will use the default model of ML Kit and build two flutter applicationsImage Labeling With Images ApplicationRealtime Image Labeling ApplicationImage Labeling With Tensorflow Lite ModelsIn this section, you will learn to use popular image recognition models in a tensorflow lite format in Flutter. So we are going explore popular families of image classification models and build smart flutter applications using them. So during this section, we are going to perform image labeling usingMobile Net ModelsEfiicientNet ModelsTraining Image Recognition Models for FlutterAfter learning the integration of Image Recognition models in Flutter with both Images and live camera footage you will learn to train your custom image recognition models. So during this section, you will learn toCollect & organize datasets for Model TrainingTrain Image Recognition models on those datasetsRetrain MobileNet Models on our custom datasetsRetrain EfficientNet Models on our custom datasetsRetrain ResNet Models on our custom datasetsTest & Evaluate Image Recognition ModelsConvert trained models in tflite format so that we can them in FlutterSo after completing this section you will be able to train your custom models on your own datasets.Using Our Trained Models in FlutterSo after training models, we will learn to use those models in Flutter With both Images and videos. So inside this section, we are going to build two flutter applications using the models we trained.This course is a complete cookbook for image recognition implementation in Flutter for both Android& ios. So what are you waiting for join the course now and start training & using image recognition models in Flutter.
Overview
Section 1: Introduction
Lecture 1 Course Introduction
Lecture 2 Image Recognition & its Applications
Section 2: Handling Images in Flutter
Lecture 3 Creating a new Flutter Project and GUI of Application
Lecture 4 Adding the Library and setting configurations for Android & IOS
Lecture 5 Choosing Images From Gallery In Flutter
Lecture 6 Capturing Images using Camera in Flutter
Lecture 7 Overview
Section 3: Displaying Live Camera Footage in Flutter
Lecture 8 Creating new Flutter project and Adding library
Lecture 9 Displaying Live Camera Footage in Flutter
Lecture 10 Live Feed Application Demo
Lecture 11 Camera Package Overview
Section 4: Image Labeling / Classification in Flutter with ML kit
Lecture 12 Section Introduction
Lecture 13 Importing Starter application code for image labeling
Lecture 14 Choosing or capturing images in Flutter
Lecture 15 Performing Image Labeling with images in Flutter
Lecture 16 Testing the application and handling output of image classification
Lecture 17 Image Labeling with Images Overview
Lecture 18 Importing Starter Code for Realtime Image Labeling application
Lecture 19 Adding the Package and creating Image Labeler
Lecture 20 Performing Image Labeling with frames of live camera footage
Lecture 21 Testing Realtime Image labeling application
Lecture 22 Real Time Image Labeling Flutter Application Overview
Section 5: Image Recognition in Flutter With Tensorflow Lite Models
Lecture 23 Pretrained models for Image Classification
Lecture 24 Setting Up the Images Project
Lecture 25 Tensorflow Hub: How to download Pretrained Machine Learning Models
Lecture 26 Image Classification In Flutter with MobileNet Model
Lecture 27 How to Get Names of Classes Which a Model can Recognize
Lecture 28 Custom Model Integration In Flutter With Images Overview
Lecture 29 Setting Up the RealTime Image Classification Project
Lecture 30 Adding the Custom Model In Flutter Project
Lecture 31 Using MobileNet Model With Live Camera Footage In Flutter
Lecture 32 Testing MobileNet Model for Realtime Image Classification
Lecture 33 Custom Model Integration With Live Camera Footage Overview
Section 6: Image Recognition In Flutter With EfficientNet Models
Lecture 34 Downloading the EfficientNet Models
Lecture 35 Using EfficientNet Model In Flutter With Images
Lecture 36 Building Realtime Image Classification Application In Flutter Using EfficientNet
Lecture 37 Test RealTime Image Classification Application
Section 7: Training Image Recognition Models for Flutter Applications
Lecture 38 Section Introduction
Lecture 39 Data Collection for Model Training
Lecture 40 Uploading Data On Google Drive For Model Training
Lecture 41 Google Colab for Model Training
Lecture 42 Training ML Model for Flutter
Lecture 43 Testing the Model And Converting it to Tensorflow Lite
Lecture 44 Retraining MobileNet Model
Lecture 45 Retraining ResNet Models
Lecture 46 Using other EfficientNet Models for Training
Lecture 47 Retraining EfficientNet Lite4 Model
Lecture 48 Detailed Process For Model Training
Lecture 49 Model Training For Flutter Overview
Section 8: Using Trained Model For Image Recognition In Flutter
Lecture 50 Setting Up Image Classification With images Project
Lecture 51 Using Fruits EfficientNet Model in Flutter
Lecture 52 Using Fruits MobileNet Model in Flutter
Lecture 53 Using Fruits ResNet Model in Flutter
Lecture 54 Using Our Own Trained Model in Flutter With Images Overview
Lecture 55 Setting Up Realtime Image Classification Application Project
Lecture 56 Using Fruit Model With Live Camera Footage To Perform Image Classification
Lecture 57 Realtime Fruit Recognition Application Testing
Lecture 58 Using MobileNet and Other Fruits Model In Flutter
Beginner Flutter Developers who want to build computer vision based Flutter Applications for Android & IOS,Experienced Flutter Professional who want to train image recognition models and build Flutter Applications


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