Train Image Classification Models & Build Smart Android Apps

Use Image Classification Models in Android with Images or Videos | Learn to train Image Recognition Models from Scratch

What you'll learn

Train Custom Image Classification Models from Scratch & Convert models into Android compatible tensorflow lite format

Use Custom Image Classification Models in Android with Images and Camera Footage

Collect Datasets for Training Custom Image Classification Models

Use Transfer Learning to Retrain Existing Image Classification Models and use them in Android

Train Custom Image Classification Models for Android using Two Different Approaches

Requirements

No ML and Data Science Knowledge Required

A very little knowledge of Android App Development

Description

Unlock the full potential of mobile app development with our comprehensive course on training custom image classification models and integrating them into Android applications. This course is designed to guide you from the basics of machine learning and deep learning to creating sophisticated, real-time image recognition apps in Android Kotlin.What You Will Learn:Introduction to Machine Learning and Deep Learning: Start with the foundational concepts of machine learning, deep learning, and image classification to build a strong base for your journey.Dataset Collection: Learn effective methods to collect and prepare datasets for training your image classification models.Model Training Approaches: Train image classification models using two powerful approaches:Teachable Machine: A user-friendly platform to create custom models.Transfer Learning: Advanced technique to leverage pre-trained models for better accuracy and efficiency.Tensorflow Lite Conversion: Convert your trained models into TensorFlow Lite format, making them compatible with mobile applications.Android Integration: Seamlessly integrate your models into Android apps:Image Classification: Choose or capture images in Android and use your models for accurate image recognition.Real-Time Camera Footage: Display live camera footage in Android, pass frames to your models, and build real-time, intelligent mobile apps.Projects Included:Fruit and Vegetable Classification Model: Create an app that identifies different fruits and vegetables.Brain Tumor Classification Model: Develop a model to classify brain tumor images.Flower Classification Model: Build a system to recognize various types of flowers.By the end of this course, you'll be able to:Train custom image classification models tailored to your specific needs.Seamlessly integrate your models into Android applications built with Kotlin.Craft intelligent mobile apps that leverage real-time image recognition functionalities.So join us to become proficient in Android app development and create cutting-edge mobile apps with image and video recognition capabilities using Kotlin.Enroll now and start your journey towards mastering Android and Image Classification.

Overview

Section 1: Introduction

Lecture 1 Introduction

Lecture 2 Image Classification Introduction & Applications

Section 2: Machine Learning & Deep Learning for Flutter

Lecture 3 What is Machine Learning

Lecture 4 Supervised Machine Learning

Lecture 5 Regression and Classification

Lecture 6 Unsupervised Machine Learning & Reinforcement Learning

Lecture 7 Deep Learning and Neural Network Introduction

Lecture 8 Neural Network Example

Lecture 9 Working of Neural Networks for Image Classification

Lecture 10 Basic Concepts of Machine Learning

Section 3: Data Collection - Collecting Dataset for Training Image Classification Model

Lecture 11 Data Collection Introduction

Lecture 12 Finding ready to use dataset for training image classification models

Lecture 13 Exploring Downloaded dataset for training custom image classification models

Section 4: Train Your First Custom Image Classification Model in 15 Minutes

Lecture 14 Section Introduction

Lecture 15 Exploring Teachable Machine and Uploading Dataset for Model Training

Lecture 16 Training, Testing and Converting Model into Tensorflow Lite

Lecture 17 Attaching Metadata with Trained Tensorflow Lite Models

Lecture 18 Google Colab Introduction

Lecture 19 Attaching Metadata and Downloading Ready to Use Model

Section 5: Training Custom Image Classification Model with Transfer Learning

Lecture 20 Transfer Learning Introduction

Lecture 21 Google Colab Introduction

Lecture 22 Installing and Importing Libraries for Model Training

Lecture 23 Uploading Dataset and Connecting Google Drive

Lecture 24 Dividing dataset into train test and validation parts

Lecture 25 Training Custom Image Classification Model

Lecture 26 Testing the model and Converting it to Tensorflow Lite Format

Section 6: Training Brain Tumor Classification Model

Section 7: Android App Development

Lecture 27 Section Introduction

Section 8: Image Picker Android - Choose or Capture Images

Lecture 28 Creating a new Android Studio Project and Building GUI of Android App

Lecture 29 Choosing Images from Gallery in Android

Lecture 30 Capturing Images using Camera in Android

Lecture 31 File Provider : Share Data Between Android Apps Securely

Lecture 32 Capturing Images in Android Overview

Section 9: Image Classification With Images

Lecture 33 Adding Tesnorflow Lite Model & Libraries in Android

Lecture 34 Analyzing and loading Tesnorflow Lite Model in Android

Lecture 35 Passing Input to tflite model and getting output in Android

Lecture 36 Showing Results of Custom Image Classification Model on Screen in Android

Section 10: Background Of Using Tensorflow Lite Models in Android

Lecture 37 Loading Tensorflow Lite Model in Android

Lecture 38 Passing input to the Tesnorflow Lite model and Getting output

Lecture 39 How Tensorflow Lite Models return Results in Android

Lecture 40 Converts Model Output into Results in Android

Section 11: Using Transfer Learning Trained Model in Android & GUI Improvements

Lecture 41 Using Transfer Learning Trained Model in Android

Lecture 42 Improving GUI of Image Classification with Images Application

Section 12: Display Live Camera Footage in Android with Camera2 API

Lecture 43 Creating New Android Project and handling Camera Permission

Lecture 44 Displaying Live Camera Footage in Android with Camera2 API

Lecture 45 How we are displaying Camera in Android

Lecture 46 Getting Frames of Live Camera Footage as Bitmaps in Android

Section 13: Realtime Image Classification Android

Lecture 47 Adding Models and Libraries in Android Studio Proect

Lecture 48 Loading Tensorflow Lite Models in Android and Passing Frames of Camera

Lecture 49 Showing Models results on Screen in Android

Lecture 50 Using Transfer Learning Trained Model in Android

Lecture 51 Setting Confidence Threshold in Android

Lecture 52 Working on GUI of Realtime Image Classification Android Application

Beginner Android Developers looking to build Machine Learning Powered Android Apps,Anyone who want to train Image Classification Models and than use them in Android Apps,Android Developers looking to enhance their skills by learning to train and use image classification models in Android