Forem: HarmonyOS Developers

Create Your First ArkTS Application

HarmonyOS Developers — Tue, 01 Jul 2025 02:03:39 +0000

About this course:

How to Create Your First ArkTS Application.

Comprises the following four sections:

Preparations,
Create a new ArkTS Project,
Write the code,
Build and run the hap in your device.

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Migrating Projects To HarmonyOS NEXT

HarmonyOS Developers — Mon, 30 Jun 2025 02:37:39 +0000

About this course:

Migrating Projects To HarmonyOS NEXT.

Comprises the following six sections:

Prerequisites,
Create Project,
Start Migration,
Code Modification Case,
Verification,
and Summary.

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HarmonyOS Security Architecture and Key Technologies

HarmonyOS Developers — Fri, 27 Jun 2025 07:40:51 +0000

About this course：

HarmonyOS Security Architecture and Key Technologies.

Comprises the following three sections:

HarmonyOS Security Design and Architecture;
Key Technologies for App Security Development;
HarmonyOS Privacy Protection.

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Health Service Kit Integration and Development

HarmonyOS Developers — Thu, 26 Jun 2025 02:22:37 +0000

About this course:

Health Service Kit Integration and Development.

Comprises the following four sections:
About Health Service Kit,
Getting Started,
Developing Your App,
and Summary.

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Wear Engine Development

HarmonyOS Developers — Wed, 25 Jun 2025 02:54:09 +0000

About this course:

Wear Engine Integration and Development.

Comprises the following four sections:

About Wear Engine,
Phone App Development,
HarmonyOS Wearable App Development,
and Summary.

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ArkUI Development Practice (HarmonyOS World)

HarmonyOS Developers — Tue, 24 Jun 2025 08:29:09 +0000

About this course:

ArkUI Development Practice (HarmonyOS World). Comprises the following four sections: Objectives, Concepts, Hands-on Training, and Summary.

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Basic ArkTS Syntax

HarmonyOS Developers — Mon, 23 Jun 2025 09:38:37 +0000

About this course:

Basic ArkTS Syntax.

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HUAWEI DevEco Kit Features

HarmonyOS Developers — Fri, 20 Jun 2025 09:07:52 +0000

About this course：

HUAWEI DevEco Kit Features.

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💻What is HarmonyOS Next? How is it Different from Android?

HarmonyOS Developers — Tue, 17 Jun 2025 07:51:32 +0000

What is HarmonyOS Next?

Introduction

The platforms that support mobile continue to change along with the mobile ecosystem. Huawei’s next-generation operating system, HarmonyOS NEXT, was formally introduced in 2023. It was developed from the ground up and is not dependent on the Android Open Source Project (AOSP). Although HarmonyOS NEXT expands upon the original HarmonyOS idea, it represents a significant strategic and technological change.
This article will cover what HarmonyOS Next is and how it is different from Android.

🌐 What is HarmonyOS NEXT?

Smartphones, wearables, tablets, smart TVs, and Internet of Things devices can all enjoy a smooth experience with Huawei’s entirely independent operating system, HarmonyOS NEXT.
HarmonyOS NEXT is not based on Android like earlier HarmonyOS versions, which still maintained some compatibility with Android apps. It brings with it a new programming language, a new app runtime, and an ecosystem that is completely exclusive to Huawei services and hardware.
🔍 Let’s see the key differences between HarmonyOS Next and Android on the table;

HarmonyOS Next — Android

Why Was HarmonyOS NEXT Created?

In response to geopolitical limitations and technological aspirations, Huawei has developed HarmonyOS NEXT. The corporation wants to create an ecosystem that is completely under its control, highly connected, and secure.
Technically, HarmonyOS NEXT makes it possible for:

Avoiding Android’s compatibility layers improved performance.
Improved privacy and security with Huawei’s in-house services and APIs
Features that are distributed, such as cross-device app flows (phone ↔ watch ↔ tablet) Through the eyes of developers; For developers, especially those with an Android background, HarmonyOS NEXT offers a fresh yet familiar experience. Its modular architecture, declarative UI style, and use of ViewModel and state management will feel intuitive. At the same time, it introduces new concepts like ArkTS (a TypeScript-based language), ArkUI (a built-in stateful UI framework), and updated models for navigation, permissions, and distributed interactions.

What About Android?

Android is a widely used platform globally, known for its flexibility, power, and large developer community. HarmonyOS NEXT represents a different approach that focuses on Huawei’s ecosystem and aims to provide a more controlled, integrated, and seamless digital experience. As a developer, embracing both platforms can expand your career opportunities, help you adapt to regional market needs, and ensure you’re prepared for a future with increasingly diverse mobile ecosystems.

App Distribution and Ecosystem

HarmonyOS NEXT apps are distributed through Huawei AppGallery, which has grown significantly in markets where Huawei devices dominate.
Huawei provides extensive development support via:
DevEco Studio (IDE similar to Android Studio)
Distributed Dev Kits
Comprehensive Documentation in English and Chinese

Conclusion

HarmonyOS NEXT is Huawei’s bold move to create a standalone, next-generation operating system with its vision for connected experiences. It presents both an opportunity and a challenge for Android developers, allowing them to use their existing skills while learning new concepts.
References

HarmonyOS NEXT - Wikipedia
Edit description
en.wikipedia.org

华为开发者联盟-HarmonyOS开发者官网，共建鸿蒙生态
华为开发者联盟是华为面向生态伙伴的开放合作平台，致力于从开发、测试、推广、变现等环节助力开发者，聚合了HarmonyOS鸿蒙、HMS Core、AGC等开放能力，方便开发者一站式获取，轻松完成应用开发。
developer.huawei.com

Keywords: Android、Huawei、Harmonyos、Mobile App Development、App Gallery

HarmonyOS Overview - 01 What Is HarmonyOS

HarmonyOS Developers — Fri, 13 Jun 2025 08:20:38 +0000

HarmonyOS Overview - 01 What Is HarmonyOS
About this course：HarmonyOS in a minute.
Read the original article:

HMS Core Release News — HMS Core 6.6.0

HarmonyOS Developers — Fri, 12 Aug 2022 09:43:00 +0000

Released the function of saving churned users as an audience to the retention analysis function. This function enables multi-dimensional examination on churned users, thus contributing to making targeted measures for winning back such users.
Changed Audience analysis to Audience insight that has two submenus: User grouping and User profiling. User grouping allows for segmenting users into different audiences according to different dimensions, and user profiling provides audience features like profiles and attributes to facilitate in-depth user analysis.
Added the Page access in each time segment report to Page analysis. The report compares the numbers of access times and users in different time segments. Such vital information gives you access to your users' product usage preferences and thus helps you seize operations opportunities.
Added the Page access in each time segment report to Page analysis. The report compares the numbers of access times and users in different time segments. Such vital information gives you access to your users' product usage preferences and thus helps you seize operations opportunities.

Learn more>>

Debuted the auto rigging capability. Auto rigging can load a preset motion to a 3D model of a biped humanoid, by using the skeleton points on the model. In this way, the capability automatically rigs and animates such a biped humanoid model, lowering the threshold of 3D animation creation and making 3D models appear more interesting.
Added the AR-based real-time guide mode. This mode accurately locates an object, provides real-time image collection guide, and detects key frames. Offering a series of steps for modeling, the mode delivers a fresh, interactive modeling experience.

Learn more>>

Offered the auto-smile capability in the fundamental capability SDK. This capability detects faces in the input image and then lightens up the faces with a smile (closed-mouth or open-mouth).
Supplemented the fundamental capability SDK with the object segmentation capability. This AI algorithm-dependent capability separates the selected object from a video, to facilitate operations like background removal and replacement.

Learn more>>

Released the interactive biometric verification service. It captures faces in real time and determines whether a face is of a real person or a face attack (like a face recapture image, face recapture video, or a face mask), by checking whether the specified actions are detected on the face. This service delivers a high-level of security, making it ideal in face recognition-based payment scenarios.
Improved the on-device translation service by supporting 12 more languages, including Croatian, Macedonian, and Urdu. Note that the following languages are not yet supported by on-device language detection: Maltese, Bosnian, Icelandic, and Georgian.

Learn more>>

Added the on-cloud REST APIs for the AI dubbing capability, which makes the capability accessible on more types of devices.
Added the asynchronous API for the audio source separation capability. On top of this, a query API was added to maintain an audio source separation task via taskId. This serves as the solution to the issue that in some scenarios, a user failed to find their previous audio source separation task when they exited and re-opened the app, because of the long time taken by an audio source separation task to complete.
Enriched on-device audio source separation with the following newly supported sound types: accompaniment, bass sound, stringed instrument sound, brass stringed instrument sound, drum sound, accompaniment with the backing vocal voice, and lead vocalist voice.

Learn more>>

Added two activity record data types: apnea training and apnea testing in diving, and supported the free diving record data type on the cloud-side service, giving access to the records of more activity types.
Added the sampling data type of the maximum oxygen uptake to the device-side service. Each data record indicates the maximum oxygen uptake in a period. This sampling data type can be used as an indicator of aerobic capacity.
Added the open atomic sampling statistical data type of location to the cloud-side service. This type of data records the GPS location of a user at a certain time point, which is ideal for recording data of an outdoor sport like mountain hiking and running.
Opened the activity record segment statistical data type on the cloud-side service. Activity records now can be collected by time segment, to better satisfy requirements on analysis of activity records.
Added the subscription of scenario-based events and supported the subscription of total step goal events. These fresh features help users set their running/walking goals and receive push messages notifying them of their goals.

Learn more>>

Released the HDR Vivid SDK that provides video processing features like opto-electronic transfer function (OETF), tone mapping, and HDR2SDR. This SDK helps you immerse your users with high-definition videos that get rid of overexposure and have clear details even in dark parts of video frames.
Added the capability for killing the WisePlayer process. This capability frees resources occupied by WisePlayer after the video playback ends, to prevent WisePlayer from occupying resources for too long.
Added the capability to obtain the list of video source thumbnails that cover each frame of the video source — frame by frame, time point by time point — when a user slowly drags the video progress bar, to improve video watching experience.
Added the capability to accurately play video via dragging on the progress bar. This capability can locate the time point on the progress bar, to avoid the inaccurate location issue caused by using the key frame for playback location.

Learn more>>

Added the 3D fluid simulation component. This component allows you to set the boundaries and volume of fluid (VOF), to create interactive liquid sloshing.
Introduced the dynamic diffuse global illumination (DDGI) plugin. This plugin can create diffuse global illumination in real time when the object position or light source in the scene changes. In this way, the plugin delivers a more natural-looking rendering effect.

Learn more>>

For the hms-mapkit-demo sample code: Added the MapsInitializer.initialize API that is used to initialize the Map SDK before it can be used.
Added the public layer (precipitation map) in the enhanced SDK.

Go to GitHub >>

For the hms-sitekit-demo sample code: Updated the Gson version to 2.9.0 and optimized the internal memory. Go to GitHub >>

For the hms-game-demo sample code: Added the configuration of removing the dependency installation boost of HMS Core (APK), and supported HUAWEI Vision.

Go to GitHub >>

Made necessary updates to other kits. Learn more >>

How I Created a Smart Video Clip Extractor

Jackson — Fri, 12 Aug 2022 02:20:43 +0000

Travel and life vlogs are popular among app users: Those videos are telling, covering all the most attractive parts in a journey or a day. To create such a video first requires great editing efforts to cut out the trivial and meaningless segments in the original video, which used to be a thing of video editing pros.

This is no longer the case. Now we have an array of intelligent mobile apps that can help us automatically extract highlights from a video, so we can focus more on spicing up the video by adding special effects, for example. I opted to use the highlight capability from Video Editor Kit to create my own vlog editor.

How It Works

This capability assesses how appealing video frames are and then extracts the most suitable ones. To this end, it is said that the capability takes into consideration the video properties most concerned by users, a conclusion that is drawn from survey and experience assessment from users. On the basis of this, the highlight capability develops a comprehensive frame assessment scheme that covers various aspects. For example:

Aesthetics evaluation. This aspect is a data set built upon composition, lighting, color, and more, which is the essential part of the capability.

Tags and facial expressions. They represent the frames that are detected and likely to be extracted by the highlight capability, such as frames that contain people, animals, and laughter.

Frame quality and camera movement mode. The capability discards low-quality frames that are blurry, out-of-focus, overexposed, or shaky, to ensure such frames will not impact the quality of the finished video. Amazingly, despite all of these, the highlight capability is able to complete the extraction process in just 2 seconds.

See for yourself how the finished video by the highlight capability compares with the original video.

Backing Technology

The highlight capability stands out from the crowd by adopting models and a frame assessment scheme that are iteratively optimized. Technically and specifically speaking:

The capability introduces AMediaCodec for hardware decoding and Open Graphics Library (OpenGL) for rendering frames and automatically adjusting the frame dimensions according to the screen dimensions. The capability algorithm uses multiple neural network models. In this way, the capability checks the device model where it runs and then automatically chooses to run on NPU, CPU, or GPU. Consequently, the capability delivers a higher running performance.

To provide the extraction result more quickly, the highlight capability uses the two-stage algorithm of sparse sampling to dense sampling, checks how content distributed among numerous videos, and adopts the frame buffer. All these contribute to a higher efficiency of determining the most attractive video frames. To ensure high performance of the algorithm, the capability adopts the thread pool scheduling and producer-consumer model, to ensure that the video decoder and models can run at the same time.

During the sparse sampling stage, the capability decodes and processes some (up to 15) key frames in a video. The interval between the key frames is no less than 2 seconds. During the dense sampling stage, the algorithm picks out the best key frame and then extracts frames before and after to further analyze the highlighted part of the video.

The extraction result is closely related to the key frame position. The processing result of the highlight capability will not be ideal when the sampling points are not dense enough because, for example, the video does not have enough key frames or the duration is too long (greater than 1 minute). For the capability to deliver optimal performance, it recommends that the duration of the input video be less than 60 seconds.

Let's now move on to how this capability can be integrated.

Integration Process

Preparations

Make necessary preparations before moving on to the next part. Required steps include:

i. Configure the app information in AppGallery Connect.

ii. Integrate the SDK of HMS Core.

iii. Configure obfuscation scripts.

iv. Declare necessary permissions.

Setting up the Video Editing Project

i. Configure the app authentication information by using either an access token or API key.

Method 1: Call setAccessToken to set an access token, which is required only once during app startup.

MediaApplication.getInstance().setAccessToken("your access token");

Method 2: Call setApiKey to set an API key, which is required only once during app startup.

MediaApplication.getInstance().setApiKey("your ApiKey");

ii. Set a License ID.

This ID is used to manage the usage quotas of Video Editor Kit and must be unique.

MediaApplication.getInstance().setLicenseId("License ID");

Initialize the runtime environment of HuaweiVideoEditor.

When creating a video editing project, we first need to create an instance of HuaweiVideoEditor and initialize its runtime environment. When you exit the project, the instance shall be released.

Create an instance of HuaweiVideoEditor.

HuaweiVideoEditor editor = HuaweiVideoEditor.create(getApplicationContext());

Determine the layout of the preview area.

Such an area renders video images, and this is implemented by SurfaceView within the fundamental capability SDK. Before the area is created, we need to specify its layout.

<LinearLayout    
    android:id="@+id/video_content_layout"    
    android:layout_width="0dp"    
    android:layout_height="0dp"    
    android:background="@color/video_edit_main_bg_color"    
    android:gravity="center"    
    android:orientation="vertical" />
// Specify a preview area.
LinearLayout mSdkPreviewContainer = view.findViewById(R.id.video_content_layout);

// Design the layout of the area.
editor.setDisplay(mSdkPreviewContainer);

Initialize the runtime environment. If the license verification fails, LicenseException will be thrown.

After the HuaweiVideoEditor instance is created, it will not use any system resources, and we need to manually set the initialization time for the runtime environment. Then, the fundamental capability SDK will internally create necessary threads and timers.

try {
        editor.initEnvironment();
   } catch (LicenseException error) { 
        SmartLog.e(TAG, "initEnvironment failed: " + error.getErrorMsg());    
        finish();
        return;
   }

Integrating the Highlight Capability

// Create an object that will be processed by the highlight capability.
HVEVideoSelection hveVideoSelection = new HVEVideoSelection();
// Initialize the engine of the highlight capability.
hveVideoSelection.initVideoSelectionEngine(new HVEAIInitialCallback() {
        @Override
        public void onProgress(int progress) {
        // Callback when the initialization progress is received.
        }
        @Override
        public void onSuccess() {
            // Callback when the initialization is successful.
        }

        @Override
        public void onError(int errorCode, String errorMessage) {
            // Callback when the initialization failed.
        }
});

// After the initialization is successful, extract the highlighted video. filePath indicates the video file path, and duration indicates the desired duration for the highlighted video.
hveVideoSelection.getHighLight(filePath, duration, new HVEVideoSelectionCallback() {
        @Override
        public void onResult(long start) {
            // The highlighted video is successfully extracted.
        }
});

// Release the highlight engine.
hveVideoSelection.releaseVideoSelectionEngine();

Conclusion

The vlog has been playing a vital part in this we-media era since its appearance. In the past, there were just a handful of people who could create a vlog, because the process of picking out the most interesting part from the original video could be so demanding.

Thanks to smart mobile app technology, even video editing amateurs can now create a vlog because much of the process can be completed automatically by an app with the function of highlighted video extraction.

The highlight capability from the Video Editor Kit is one such function. This capability introduces a set of features to deliver incredible results, such as AMediaCodec, OpenGL, neural networks, a two-stage algorithm (sparse sampling to dense sampling), and more. This capability can help create either a highlighted video extractor or build a highlighted video extraction feature in an app.