Book Image

Machine Learning Projects for Mobile Applications

By : Karthikeyan NG
Book Image

Machine Learning Projects for Mobile Applications

By: Karthikeyan NG

Overview of this book

Machine learning is a technique that focuses on developing computer programs that can be modified when exposed to new data. We can make use of it for our mobile applications and this book will show you how to do so. The book starts with the basics of machine learning concepts for mobile applications and how to get well equipped for further tasks. You will start by developing an app to classify age and gender using Core ML and Tensorflow Lite. You will explore neural style transfer and get familiar with how deep CNNs work. We will also take a closer look at Google’s ML Kit for the Firebase SDK for mobile applications. You will learn how to detect handwritten text on mobile. You will also learn how to create your own Snapchat filter by making use of facial attributes and OpenCV. You will learn how to train your own food classification model on your mobile; all of this will be done with the help of deep learning techniques. Lastly, you will build an image classifier on your mobile, compare its performance, and analyze the results on both mobile and cloud using TensorFlow Lite with an RCNN. By the end of this book, you will not only have mastered the concepts of machine learning but also learned how to resolve problems faced while building powerful apps on mobiles using TensorFlow Lite, Caffe2, and Core ML.
Table of Contents (16 chapters)
Title Page
Dedication
Packt Upsell
Contributors
Preface
Index

Face detection


With face detection, you can automatically detect human faces in an image or video. This reports the actual position of the face inside the media with size and orientation. Once a face is identified, we can further detect other body parts in it such as nose, eyes, and mouth. The face detection API detects the following:

  • Bounding box of the detected face
  • Tilt angle and rotating angle of the face
  • Coordinates of the nose base, bottom of the mouth, left-hand side of the mouth, and right-hand side of the mouth
  • Probability that the left eye is open, the right eye is open, and the person is smiling

There are a few terms associated with the face detection feature of ML Kit.

Face orientation tracking

Facetracking can be used to detect a particular face in a video. We can calculate the amount of frames that a particular face appears in, and we can also detect whether two faces are similar based on the position and motion of the face (this is typically possible in a video).

Face position is...