Introduction
Huawei provides various services for developers to make ease of development and provides best user experience to end users. In this article, we will be integrating following kits:
Ads Kit
Game services
Analytics Kit
Location Kit
Push Kit
We will learn to integrate above HMS Kits in Unity game development using official plugin. And by integrating in single application gives experience the ease of development and give best user experience and showcases stability of the kits, and how we can use kits efficiently to make users experience the best of it.
Development Overview
You need to install Unity software and I assume that you have prior knowledge about the unity and C#.
Hardware Requirements
A computer (desktop or laptop) running Windows 10.
A Huawei phone (with the USB cable), which is used for debugging.
Software Requirements
Java JDK installation package.
Unity software installed.
Visual Studio/Code installed.
HMS Core (APK) 4.X or later.
Integration Preparations
1. Create a project in AppGallery Connect.
2. Create Unity project.
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3. Adding Huawei HMS AGC Services to project.
5. Generate a SHA-256 certificate fingerprint.
To generating SHA-256 certificate fingerprint use below command.
6. Configure the signing certificate fingerprint.
7. Download and save the configuration file.
Add the agconnect-services.json file following dir Assets > Plugins > Android
8. Add the following plugin and dependencies in LaucherTemplate
Code:
apply plugin: 'com.huawei.agconnect'
Code:
implementation 'com.huawei.agconnect:agconnect-core:1.4.1.300'
implementation 'com.huawei.hms:base:5.0.0.301'
implementation 'com.huawei.hms:hwid:5.0.3.301'
implementation 'com.huawei.hms:game:5.0.1.302'
implementation 'com.huawei.hms:push:4.0.1.300'
implementation 'com.huawei.hms:hianalytics:5.0.3.300'
9. Add the following dependencies in MainTemplate.
Code:
implementation 'com.huawei.agconnect:agconnect-core:1.4.1.300'
implementation 'com.huawei.hms:base:5.0.0.301'
implementation 'com.huawei.hms:hwid:5.0.3.301'
implementation 'com.huawei.hms:game:5.0.1.302'
implementation 'com.huawei.hms:hianalytics:5.0.3.300'
implementation 'com.huawei.hms:ads-lite:13.4.29.303'
implementation 'com.huawei.hms:ads-consent:3.4.30.301'
implementation 'com.huawei.hms:push:4.0.1.300'
implementation 'com.huawei.hms:location:5.0.0.301'
10. Add the following dependencies in MainTemplate.
repositories & class path in BaseProjectTemplate.
Code:
maven { url 'https://developer.huawei.com/repo/' }
Code:
classpath 'com.huawei.agconnect:agcp:1.2.1.301'
11. Add Achievement details in AGC > My apps
12. Add LeaderBoard details.
Continue reading..
Tips and Tricks
Add agconnect-services.json file without fail.
Add SHA-256 fingerprint without fail.
Add Achievements and LeaderBoad details before run.
Make sure dependencies added in build files.
Enable location and accept permission to read location.
Conclusion
We have learnt integration of HMS GameService Kit, Ads Kit,Location kit, Push Kit and Analytics kit in Unity. Error code while fetching Player extra information and Event Begin and end.
7006: The account has not been registered in Chinese mainland. In this case, perform bypass and no further action is required.
Thanks for reading, please do like and comment your queries or suggestions.
Read full article
References
Hms game services
HMS Ads Kit
HMS Analytics Kit
HMS Push Kit
Location Kit
Related
Introduction
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Quality improvement has become crucial in this era of digitalization where all our documents are kept in the folders, shared over the network and read on the digital device.
Imaging the grapple of an elderly person who has no way to read and understand an old prescribed medical document which has gone blurred and deteriorated.
Can we evade such issues??
NO!!
Let’s unbind what Huawei ML Kit offers to overcome such challenges of our day to day life.
Huawei ML Kit provides Text Recognition API to improvise the quality and visibility of old and blurred text on an image.
Text Recognition API is very important and useful the industries where the data is huge and required to be extracted from the images.
Text Recognition API provides two ways to read and process the data on an image:
Local
Huawei ML kit’s Text Recognition API can detect and read the text on an image using the algorithms configured on the device itself and does not require any interaction with cloud and internet.
Remote
Huawei ML kit’s Text Recognition API can analyse and read the text on an image using cloud algorithm API and require interaction with cloud and internet.
Development Overview
We will be focusing on simple text recognition from an image using on device detection API’s
Prerequisite
1. Must have a Huawei Developer Account
2. Must have a Huawei phone with HMS 4.0.0.300 or later
3. React Native environment with Android Studio, Node Js and Visual Studio code.
Major Dependencies
1. React Native CLI : 2.0.1
2. Gradle Version: 6.0.1
3. Gradle Plugin Version: 4.0.1
4. React Native ML Kit SDK : 5.0.0
5. react-native-hms-ml kit gradle dependency
6. AGCP gradle dependency
Software Requirements
1. Java SDK 1.8 or later
2. Android 5.0 or later
Preparation
1. Create a react native project using React Native CLI and open android directory.
2. Download the React Native ML Kit SDK and paste it under Node modules directory of React Native project.
3. Create an app and project in the Huawei AppGallery Connect.
4. Provide the SHA Key and App Package name of the project.
5. Enable the ML API and download the agconnect-services.json file and paste to the app folder of your android folder.
Integration
Add below to build.gradle (project) file, under buildscript/repositories and allprojects/repositories.
Code:
Maven {url 'http://developer.huawei.com/repo/'}
Add below to build.gradle (app) file, under dependencies to use the ML kit SDK in your React Native application.
Code:
dependencies{
// Import the SDK.
implementation project(":react-native-hms-ml ")
…
…
implementation 'com.huawei.agconnect:agconnect-core:1.2.1.301'
}
Add below under Settings.Gradle file
Code:
include ':react-native-hms-ml
project(':react-native-hms-ml).projectDir = new File(rootProject.projectDir, '../node_modules/react-native-hms-ml /android')
Add below under MainApplication,java file.
Code:
import com.huawei.hms.rn.ml.HmsMlPackage;
public class MainApplication extends Application implements ReactApplication {
...
@Override
protected List<ReactPackage> getPackages() {
@SuppressWarnings("UnnecessaryLocalVariable")
List<ReactPackage> packages = new PackageList(this).getPackages();
//Add following line. Don't forget to add import statement also.
packages.add(new HmsMlPackage());
return packages;
}
...
};
Use case
Huawei ML kit’s Text Recognition API provides many different use cases, however our focus would be reading a hand written note and display the text on the application using on device capabilities of the API.
App.js
App.js file acts as entry point and creates navigation to navigate on required service page.
More details, you can check https://forums.developer.huawei.com/forumPortal/en/topic/0204424693794850035
Interesting.
Rebis said:
Interesting.
Click to expand...
Click to collapse
THANKS
If the text is not visible properly using this service can we extract the data.
Introduction
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Image Classification is the process where a computer device can analyse and define the image category or class in simple language.
Image Classification can be used in many intelligent services, photo gallery application and to design highly efficient security products and services.
Huawei ML Kit enable developers to use its highly efficient API’s to implement the image classification for their mobile applications.
Huawei ML Kit classifies the elements presents in an image into defined categories such as objects, environment, artwork, animal, etc.
Huawei ML Kit’s Image Classification API’s are available for two different classification modes
On Device
Device based classification API’s analyse and detects the image category by running the on device algorithm and supports over 400 different image categories.
On Cloud
Cloud based classification API’s analyse and detects the image category by running the on cloud algorithm and supports over 12000 different image categories.
Development Overview
We will be focusing on simple Image Classification service from an image using on device API’s
Prerequisite
1. Must have a Huawei Developer Account
2. Must have a Huawei phone with HMS 4.0.0.300 or later
3. React Native environment with Android Studio, Node Js and Visual Studio code.
Major Dependencies
1. React Native CLI : 2.0.1
2. Gradle Version: 6.0.1
3. Gradle Plugin Version: 4.0.1
4. React Native ML Kit SDK : 5.0.0
5. react-native-hms-ml kit gradle dependency
6. AGCP gradle dependency
Software Requirements
1. Java SDK 1.8 or later
2. Android 5.0 or later
Preparation
1. Create a react native project using React Native CLI and open android directory.
2. Download the React Native ML Kit SDK and paste it under Node modules directory of React Native project.
3. Create an app and project in the Huawei AppGallery Connect.
4. Provide the SHA Key and App Package name of the project.
5. Enable the ML API and download the agconnect-services.json file and paste to the app folder of your android folder.
Integration
Add below to build.gradle (project) file, under buildscript/repositories and allprojects/repositories.
Maven {url 'http://developer.huawei.com/repo/'}
Add below to build.gradle (app) file, under dependencies to use the ML kit SDK in your React Native application.
Code:
dependencies{
// Import the SDK.
implementation project(":react-native-hms-ml ")
…
…
implementation 'com.huawei.agconnect:agconnect-core:1.2.1.301'
}
Add below under Settings.Gradle file
Code:
include ':react-native-hms-ml
project(':react-native-hms-ml).projectDir = new File(rootProject.projectDir, '../node_modules/react-native-hms-ml /android')
Add below under MainApplication.java file.
Code:
import com.huawei.hms.rn.ml.HmsMlPackage;
public class MainApplication extends Application implements ReactApplication {
...
@Override
protected List<ReactPackage> getPackages() {
@SuppressWarnings("UnnecessaryLocalVariable")
List<ReactPackage> packages = new PackageList(this).getPackages();
//Add following line. Don't forget to add import statement also.
packages.add(new HmsMlPackage());
return packages;
}
...
};
Add below under AndroidManifest.xml file
Code:
<uses-permission android:name="android.permission.INTERNET" /> <uses-permission android:name="android.permission.CAMERA" /> <uses-permission android:name="android.permission.WRITE_EXTERNAL_STORAGE" /> <uses-permission android:name="android.permission.READ_EXTERNAL_STORAGE" />
<application
<meta-data
android:name="com.huawei.hms.ml.DEPENDENCY"
android:value="ocr"/>
</application>
Use case
Huawei ML kit’s Image Classification API provides many different use cases, however we will take very simple gallery image classification as example.
Imageclassification.js
Imageclassification.js is a java script file which we will keep under “src” folder of the project to have the navigation stack from the launch page.
We will re-direct to “Classify” tab from here to showcase the image classification capabilities.
More details, you can check https://forums.developer.huawei.com/forumPortal/en/topic/0203430657683920058
Introduction
Augmented Reality is increasing every day in different areas like shopping, Games, Education etc. AR Engine provides a mesh with more than 4,000 vertices and 7,000 triangles to precisely outline face contours, and enhance the overall user experience.
Today I will develop a demo application and try to explain this features and what it provides in more detail.
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AR Engine Services
Augmented reality (AR) is an interactive experience of a real-world environment where the objects reside in the real world are enhanced by computer-generated perceptual information, sometimes across multiple sensory modalities, including visual, auditory, haptic, somatosensory and olfactory.
It provide basic AR capabilities such as motion tracking, environment tracking, body tracking, and face tracking.
Restrictions
The current version of Huawei AR Engine supports only Huawei devices. So, you need a Huawei phone that supports Huawei AR Engine, you can see the supported devices below.
AR Engine Process
The following figure shows the general process of using the Huawei AR Engine SDK.
Flutter setup
Refer this URL to setup Flutter.
Software Requirements
1. Android Studio 3.X
2. JDK 1.8 and later
3. SDK Platform 24 and later
4. Gradle 4.6 and later
5. Ensure that the AR Engine server APK have been downloaded from AppGallery and installed on the device. To do so, search for HUAWEI AR Engine in Huawei AppGallery.
Steps to integrate service
1. We need to register as a developer account in AppGallery Connect
2. Create an app by referring to Creating a Project and Creating an App in the Project
3. Set the data storage location based on current location
4. Generating a Signing Certificate Fingerprint.
5. Configuring the Signing Certificate Fingerprint.
6. Get your agconnect-services.json file to the app root directory.
Development Process
Create Application in Android Studio.
1. Create Flutter project.
2. App level gradle dependencies. Choose inside project Android > app > build.gradle.
Code:
apply plugin: 'com.android.application'
apply plugin: 'com.huawei.agconnect'
Root level gradle dependencies
Code:
maven {url 'https://developer.huawei.com/repo/'}
classpath 'com.huawei.agconnect:agcp:1.4.1.300'
Add the below permissions in Android Manifest file.
Code:
<manifest xlmns:android...>
...
<uses-permission android:name="android.permission.CAMERA" />
<application ...
</manifest>
3. Add HMS AR Engine kit plugin download using below URL.
https://developer.huawei.com/consum...y-V1/flutter-sdk-download-0000001059096444-V1
4. On your Flutter project directory find and open your pubspec.yaml file and add library to dependencies to download the package from pub.dev. Or if you downloaded the package from the HUAWEI Developer website, specify the library path on your local device. For both ways, after running pub get command, the plugin will be ready to use.
Code:
name: arDemo
description: A new Flutter application.
publish_to: 'none' # Remove this line if you wish to publish to pub.dev
version: 1.0.0+1
environment:
sdk: ">=2.7.0 <3.0.0"
dependencies:
flutter:
sdk: flutter
huawei_ar:
path: ../huawei_ar/
dev_dependencies:
flutter_test:
sdk: flutter
flutter:
uses-material-design: true
5. We can check the plugins under External Libraries directory.
6. Open main.dart file to create UI and business logics.
More details, you can check https://forums.developer.huawei.com/forumPortal/en/topic/0202460753111420009
Introduction
In this article, I will be integrating Huawei Ads Kit in an Application. I will be using Banner Ads. Banner Ads are rectangular ad images located at the top, middle or bottom of an application’s layout that are automatically refreshed at intervals and guides to the advertiser’s page when clicked.
Ads Kit
Huawei Ads Kit leverages the vast user base of Huawei devices and Huawei's extensive data capabilities to provide you with the Publisher Service, helping you to monetize traffic.
HMS Ads Kit has 7 types of Ads kits. Now we can implement Banner Ads in this application.
Use Case
The Ads Kit will be used to display Banner Ads in a Banking Application which can perform basic functions such as Enter Pin, Withdraw Money, Deposit Money and Check Balance.
Requirements
1. Any operating system (MacOS, Linux and Windows).
2. Must have a Huawei phone with HMS 4.0.2.300 or later.
3. Must have a laptop or desktop with Android Studio, Jdk 1.8, SDK platform 26 and Gradle 4.6 installed.
4. Minimum API Level 21 is required.
5. Required EMUI 9.0.0 and later version devices.
Integrate HMS Dependencies
1. First register as Huawei developer and complete identity verification in Huawei developers website, refer to register a Huawei ID.
2. Create a project in android studio, refer Creating an Android Studio Project.
3. Generate a SHA-256 certificate fingerprint.
4. To generate SHA-256 certificate fingerprint. Choose View > Tool Windows > Gradle > Signingreport > SHA256 code.
Or use cmd as explained in SHA256 CODE
5. Create an App in AppGallery Connect.
6. Download the agconnect-services.json file from App information, copy and paste in android Project under app directory, as follows.
7. Enter SHA-256 certificate fingerprint and click Save, as follows.
8. Add the below maven URL in build.gradle(Project) file under the repositories of buildscript, dependencies and allprojects, refer Add Configuration.
maven { url 'http://developer.huawei.com/repo/' }
classpath 'com.huawei.agconnect:agcp:1.6.0.300'
9. Add the below plugin and dependencies in build.gradle(Module) file.
apply plugin: 'com.huawei.agconnect'
// Huawei AGC
implementation 'com.huawei.agconnect:agconnect-core:1.6.0.300'
// Ads Kit
Implementation 'com.huawei.hms:ads-lite:13.4.40.301'
10. Now Sync the gradle.
11. Add the required permission to the Manifestfile.xml file.
<uses-permission android:name="android.permission.ACCESS_NETWORK_STATE" />
<!--check wifi state-->
<uses-permission android:name="android.permission.ACCESS_WIFI_STATE" />
Development
Adding Banner view to activity_main.xml
Code:
<com.huawei.hms.ads.banner.BannerView
android:id="@+id/banner_ADview"
android:layout_width="match_parent"
android:layout_height="wrap_content"
android:layout_alignParentBottom="true"
android:layout_marginTop="10dp"
android:layout_marginBottom="10dp"
hwads:adId="@string/banner_ADid"
hwads:bannerSize="BANNER_SIZE_360_57" />
Add this code to implement Banner Ads
Code:
//Initialize the Huawei Ads SDK
HwAds.init(this)
// To get Banner view from the activity_main.xml. It will display at bottom of the page.
val bottomBannerView = findViewById<BannerView>(R.id.banner_ADview)
val adParam = AdParam.Builder().build()
bottomBannerView.adId = getString(R.string.banner_ADid)
bottomBannerView.bannerAdSize = BannerAdSize.BANNER_SIZE_SMART
bottomBannerView.loadAd(adParam)
// Call new BannerView to create a BannerView class. It will display at top of the page.
val topBannerView = BannerView(this)
topBannerView.adId = getString(R.string.banner_ADid)
topBannerView.bannerAdSize = BannerAdSize.BANNER_SIZE_SMART
topBannerView.loadAd(adParam)
val rootView = findViewById<RelativeLayout>(R.id.root_view)
rootView.addView(topBannerView)
Cloud Debugging
Use Cloud Debugging in HMS Toolkit to debug the app on a real device.
To use Cloud Debugging, you need to sign in using a HUAWEI ID, complete identity verification, and then authorize the sign-in.
Choose HMS > CloudDebugging.
You can use Available Devices. Select a device and click RUN.
Result
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"lightbox_full_screen": "Full screen",
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"lightbox_share": "Share",
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"lightbox_new_window": "New window",
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Tips and Tricks
1. Set minSDK version to 24 or later, otherwise you will get AndriodManifest merge issue.
2. Make sure you have added the agconnect-services.json file to app folder.
3. Make sure you have added SHA-256 fingerprint without fail.
4. Make sure all the dependencies are added properly.
Conclusion
In this article, we have learnt integration of Ads Kit in Banking application. It provides developers different capabilities to deliver good quality ads content to users.
Reference
Ads Kit: Documentation
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Introduction
In this article, I will be integrating Huawei Push Kit in an Application.
Push Kit
Push notifications offers a great way to increase your application’s user engagement and boost your retention rates by sending meaningful messages or by informing users about your application. Push Kit supports two types of messages: notification messages and data messages. You can send notifications and data messages to your users from your server using the Push Kit APIs or directly from the AppGallery Push Kit Console.
Requirements
1. Any operating system (MacOS, Linux and Windows).
2. Must have a Huawei phone with HMS 4.0.2.300 or later.
3. Must have a laptop or desktop with Android Studio, Jdk 1.8, SDK platform 26 and Gradle 4.6 installed.
4. Minimum API Level 21 is required.
5. Required EMUI 9.0.0 and later version devices.
Integrate HMS Dependencies
1. First register as Huawei developer and complete identity verification in Huawei developers website, refer to register a Huawei ID.
2. Create a project in android studio, refer Creating an Android Studio Project.
3. Generate a SHA-256 certificate fingerprint.
4. To generate SHA-256 certificate fingerprint. Choose View > Tool Windows > Gradle > Signingreport > SHA256 code.
Or use cmd as explained in SHA256 CODE
5. Create an App in AppGallery Connect.
6. Download the agconnect-services.json file from App information, copy and paste in android Project under app directory.
7. Enter SHA-256 certificate fingerprint and click Save.
8. Click Manage APIs tab and enable Push Kit.
9. Add the below maven URL in build.gradle(Project) file under the repositories of buildscript, dependencies and allprojects, refer Add Configuration.
Code:
maven { url 'http://developer.huawei.com/repo/' }
classpath 'com.huawei.agconnect:agcp:1.6.0.300'
10. Add the below plugin and dependencies in build.gradle(Module) file.
Code:
apply plugin: id 'com.huawei.agconnect'
//Huawei AGC
Code:
implementation 'com.huawei.agconnect:agconnect-core:1.6.0.300'
// Huawei Push Kit
Code:
implementation 'com.huawei.hms:push:6.3.0.302'
11. Now Sync the gradle.
12. Add the required permission to the Manifestfile.xml file.
Code:
// Push Kit
<uses-permission android:name="android.permission.INTERNET" />
<service
android:name=".PushService"
android:exported="false">
<intent-filter>
<action android:name="com.huawei.push.action.MESSAGING_EVENT" />
</intent-filter>
</service>
Sometimes adding everything manually can be burden. Let’s use Configuration Wizard for the setup.
Configuration Wizard
Now, we will help how to use configuration wizard of HMS Toolkit to automatically complete necessary configuration for development preparations.
Watch this video to understand how to use the configuration Wizard.
Once all the items are passed, you are good to go.
Integrating Push Kit Through Coding Assistant
Navigate to HMS > Coding Assistant, and select Push Kit in the kit list. The following figure shows all the scenarios of Push Kit.
Completing the Code by Dragging and Dropping Scenario Cards.
Select a scenario card for development, for example, Send notification message-Open home pages of corresponding apps, and drag and drop the card to the code area to generate the code for obtaining a push token
Using a Tool to Send Messages
On the toolbar of the Push Kit card, select Message Test to test whether the server can push messages to the device.
Click Get APP ID and APP SECRET. The tool automatically reads the app ID and app secret from AppGallery Connect. Click Next.
On the page that is displayed, set parameters as prompted or based on the following table.
After the setting, click Send.
Result
After successful message sending, you will receive a notification message on your device.
Tips and Tricks
1. Set minSDK version to 24 or later, otherwise you will get AndriodManifest merge issue.
2. Make sure you have added the agconnect-services.json file to app folder.
3. Make sure you have added SHA-256 fingerprint without fail.
4. Make sure all the dependencies are added properly.
Conclusion
In this article, we have learnt integration of Push Kit in application. It will guide you to increase your application’s user engagement and boost your retention rates by sending meaningful messages or by informing users about your application.
Reference
Push Kit: Documentation
Push Kit: Training Video