Building Image Recognition App Using React Native Framework

Introduction to React Native

React Native is a well-known JavaScript-based mobile application framework that allows you to build given mobile applications for iOS and Android. The framework allows you to make an application for different platforms by using a similar codebase.

React Native was first announced by Facebook as an open-source project in 2015. In only a few years, it will become one of the top solutions used for mobile app development. React Native App Development Company India uses to power some of the world’s leading mobile applications, including Instagram, Facebook, and Skype.

Technologies such as React Native make this process simple. It will display the landmarks associated with this image with the geographical coordinates of each landmark and the image region. All the information put away in the application’s data set makes the incredible experience for users dependent on the content they share and more.

Introduction to Image Recognition App

The latest advancement in machine learning and Artificial intelligence has added to the development of computer vision and image recognition concepts. From controlling a driverless vehicle to carrying out face detection for biometric access, image recognition helps in handling and arranging objects based on trained algorithms.

Uses of Image Recognition

  • Drones:

Drones fix up with image recognition abilities can provide vision-based automatic tracking, investigation, and control of the assets located in remote areas.

  • Manufacturing:

Examining production lines, evaluating critical points inside the premises. Checking the nature of the end results to decrease the imperfections. Evaluating the condition of the workers can help to produce enterprises to have complete control of various activities in the frameworks.

  • Autonomous Vehicles:

Autonomous vehicles with image recognition can recognize activities on the road and take vital moves. Mini robots can help logistics businesses to locate and transfer the items from one place to another. It additionally keeps up the database of the product movement history to keep the item from being misplaced or stolen.

  • Military Surveillance:

Observation of unusual activities in the border areas and automatic dynamic abilities can help forestall penetration and result in saving the lives of the soldiers.

  • Forest Activities:

Unmanned Aerial Vehicles can screen the forest, expect changes that can result in forest fires, and forestall poaching. It can likewise give perfect monitoring of the vast lands; which humans can’t access easily.

Market Capabilities and Scope of Computer Vision

Over the years, the market for computer-based vision has developed significantly. It is currently valued at USD 11.94 Billion and is probably going to reach at USD 17.38 Billion by 2023, at a CAGR of 7.80% between 2018 and 2023.

This is because of the expansion of autonomous and semi-autonomous vehicles, drones, wearables, and smartphones. Also, the rising adoption of Industry 4.0 and robotization in manufacturing industries has additionally stimulated the demand for Computer Vision.

In view of about the developing capability of computer vision, many organizations are putting resources into image recognition to interpreter and examine information coming from visual sources for various uses, for example, medical image examination, recognizing objects in autonomous vehicles, face identification for security reason, and so forth

Image recognition is the capacity of a framework or software to distinguish objects, individuals, places, and activities in images. It utilizes machine vision innovations with artificial intelligence and trained algorithms to perceive images through a camera system.

Much fueled by the recent development in machine learning and an expansion in the computational power of the machines, image recognition has taken the world by storm.  

Automotive, e-commerce, retail, manufacturing industries, security, surveillance, medical services, farming and so forth, can have wide use of image recognition.

Approaches to Build Image Recognition in React Native

Expo gives a set of tools to create and publish React Native applications with least efforts. If you are not technically sound you can also hire React Native app development company for that minimum effort.

How to build an image recognition app in react native:

  • Installing Expo
  • Setting Up Firebase
  • Building the App
  • Installing Expo

Expo gives a set of tools to create and publish React Native applications minimum effort. Earlier, React Native had something called create-react-native-app which is now amalgamated with Expo-Cli and is an official way to create a React Native application.

  • Setting Up Firebase

In this section, you can set up a new Firebase project. It will give us the database and backend services and you don’t need to compose your own backend for this step, so saving time and focusing on what we need to learn. For simplicity, you can make the Firebase project data public for exhibit purposes.

  • Building the App

To get started you need to install a npm package called uuid to generate a unique blob for the image that is going to upload on the firebase storage service.

Steps to Build the App

  • Run the command npm install –save UUID
  • Open App.js
  • And copy code from here
  • uploadImageAsync- function uploads the image by generating a unique image ID or blob with the help of UUID
  • Explaining a default state in the App component and requesting user permissions for both using a camera roll or gallery or take a photo from the device’s camera.
  • The Button in the App component publishes the image to Google’s cloud vision API
  • Then submit to google method is what sends requests and communicates with the API to fetch the result when the button Analyze is press by the user.
  • The rest of the steps are in relation to vision API which can be taken according to the ongoing technology.