Image Recognition App Google

Image Recognition App Google: Google Vision API and Ionic

Image Recognition App Google could be considered one of the best image search tools out there. Check out this post to find out more. 

Image Recognition App Google: Google Vision API and Ionic

Computer vision enables computers to identify photos as humans do. In the past, it did get complicated to work with text-recognizing pictures.

With the introduction of the Cloud Vision API by Google, developers now have a versatile set of software available for artificial intelligence testing from an organization with some of the strongest image recognition.

In this tutorial, we will create an Ionic app that scans photos using the Cloud Vision API.

The enjoyable portion.

The use of the API includes uploading an encoded picture to a pre-determined endpoint URL.

Have a peek at this sample JSON file.


Although the input appears to be in text, it views a picture in the encoded text.

In this case, you have to turn any base64 encoded string representation of an image into an actual image. The features property enables different features of photos to remove.

Image Labeling aims to identify an image by assigning it a marking or definition.

It’ll work out like this:

If there is greater uniformity in the degree of health across the wealthier countries, it may calculate by counting the number of dogs residing in each region. In this scenario, this, or this. Analogies.

You may still have those:

Using face recognition, we can guess where the faces are in a frame.

Landmark Detection identifies icons such as the Opera House in Sydney and Stonehenge in Wiltshire.

It detects various corporation logos.

Uses OCR tools to remove textual material from pictures.

Image classification based on safe-search criteria. Also, it classifies the picture as either an adult, extreme, gory, medical, or abusive.

Signing up for the Google Cloud Vision API.

You should check out Google Cloud Vision API for free before it goes available. Go to the Google Cloud Portal and press “try for free.”

This will direct you to an online form that demands details of your company and credit record.

Once developed, then connect the project to Google Developer Console and allow Google Vision API. I suggest you use API Key instead of the standard method.

Developing the software.

In this way, now you’re going to implement the app. Experts to provide a short description of the app you are going to create. The software would have one page with all the components needed to communicate with the Cloud Vision API.

It will have an icon and photo on a dropdown chart, a button for taking a picture, an image element for displaying the image taken, and a heading component for displaying a summary of the image.

Implementing Networking.

You will need a new terminal window to install Cordova.

Install and operate Cordova. Ions.

Using a blank design would build a whole new Ionic project.

Ionic-power-component ionic-start ionic-vision blank.

Add the sites you would like to use (i.e., WordPress or Blogger). Although I am just going to update Android, the code has to run on iOS.

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You can have the novel. Free Add-on Platform for Android mobile devices.

You can add a certain camera, files and uploading plugins for creating the software.

add Cordova plugin Camera

Moreover, it will connect a file to a mobile project.

First, build a service utilizing Cordova-plugin-file-transfer.

Deploy ngCordova utilizing bower.

NgCordova bower install

The ngCordova library implements AngularJS wrappers for the built plugins. These wrappers make it simple to operate with Ionic plugins within an Ionic framework.

Putting in a joystick.

Open the js directory, build a Home.js file within the js directory and apply the following code:


Insert home controller here.

A controller action called “HomeController” in the Ionic3 project.

var me = this; me.current image = ‘img/koro-sensei.png’;.

Those are label identification, text detection, emblem detection, and landmark detection.

Set variable API key.

$scope.takePicture = function(){

var options = { sourceType: Camera.Picture.buffer };

Enter CAMERA here.

500 px, 500px.

True, cameras.

Camera direction: 0, encodingType: Image.EncodingType.JPEG.

cordovaCamera.getPicture(); (options).


Set the locale code to “en.”

var vision api json = { “requests”:[\s {\s “image”:{\s “content”: imagedata\s },\s “features”:[\s {\s “type”: me.detection type,\s “maxResults”: 1\s }\s ]\s }\s ]\s };

Get the file contents from Vision API.

cordova.file.writeFile( cordova.file.applicationStorageDirectory, file contents, file contents, ) .


var headers = { ‘Content-Type’: ‘application/json’

Likewise, .headers = headers ;

var filepath = cordova.file.applicationStorageDirectory + “file.json”;

Everything you need to do is:


var res = JSON.parse(result.response);

/* detectKey = ‘Annotations’; */






We should generate a warning depending on the error handler feature such that we can get a response in case of an error event.

}, role (err)

As this code runs, it shows an alert: An mistake occurred having the image from the camera.

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