InspireFaceInspireFace1.2.4.d3
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Home
Get started
Get and build the SDK
Examples
  • English
  • 简体中文
GitHub
  • Introduction
  • Get started
  • Features
  • Guides

    • Architecture and lifetime
    • Model packs
    • Image inputs and coordinates
    • Sessions and tracking
    • Face analysis
    • Recognition and FeatureHub
    • Facial landmarks
    • Liveness detection
    • Face capture
    • More API recipes
  • Language and platform

    • C API
    • C++
    • Python
    • Android
    • Apple
    • iOS
    • macOS
    • HarmonyOS
  • Get and build the SDK

    • Overview and downloads
    • Source and common options
    • Linux
    • macOS
    • Android
    • iOS
    • HarmonyOS
    • NVIDIA TensorRT
    • Rockchip NPU
    • Python packaging
  • Hardware deployment

    • ARM
    • NVIDIA TensorRT
    • Rockchip NPU
    • Python on Rockchip
  • InspireCV
  • Complete examples
  • API coverage
  • Performance
  • Image processing benchmarks
  • Troubleshooting

API coverage

Find examples by feature and API. Start with the platform guide to install and initialize the SDK, then choose your API in each feature guide's code tabs.

The examples use InspireFace 1.2.4, InspireCV 1.0.2, Android Java SDK 1.2.0, and HarmonyOS ArkTS SDK 1.2.4. Objective-C and Swift use the Apple frameworks built from the 1.2.4 source revision. The table lists the operations available through each interface.

Feature examples by API

“Example” links to a guide with code for that API. “Source API” needs the newer Java source classes and a matching JNI build. A dash means that the named high-level wrapper does not expose that operation in the version above.

FeatureC APIC++AndroidPythonHarmonyOS (ArkTS)Objective-CSwift
Launch / Session / releaseExampleExampleExampleExampleExampleExampleExample
Detection / trackingExampleExampleExampleExampleExampleExampleExample
Dense landmarksExampleExampleExampleExampleExampleExampleExample
Five-point landmarksExampleExample—ExampleExampleExampleExample
Quality / mask / attributesExampleExampleExampleExampleExampleExampleExample
PoseExampleExampleQuality pathExampleExampleExampleExample
ExpressionExampleExample—ExampleExampleExampleExample
RGB liveness / actionsExampleExampleExampleExampleExampleExampleExample
Embedding / comparisonExampleExampleExampleExampleExampleExampleExample
FeatureHubExampleExampleExampleExampleExampleExampleExample
Alignment cropExampleExampleExample—ExampleExampleExample
Aligned-image extractionExampleExample——ExampleExampleExample
Similarity display conversionExampleExampleExampleExampleExampleExampleExample
Detection snapshotsExampleValue copySource APIExampleExampleExampleExample
Face captureExampleExampleSource APIExampleExampleExampleExample

The Plus passive and flash demos combine mobile capture with service-side verification. Their guide covers Android capture, progress feedback and result handling.

The code tabs share the same API selector, so choosing Python, Android, HarmonyOS (ArkTS), Objective-C or Swift also selects it in other groups that contain the same option. The complete examples include full programs to copy from the page; snippets in feature guides state which session, image or model setup they expect.

Inputs, settings and deployment

AreaEntry pointsGuide
SDK downloads and buildsPrebuilt packages, platform builds and Python native-library replacementGet and build the SDK, Python packaging
Model loading and inspectionLaunch, reload, resource-pack validation and metadataModels and builds
Images and buffersFile/bitmap input, raw RGB/BGR/YUV, stream updates, strides and rotationImage inputs
Session tuningDetector level, minimum face size, confidence, preview size, intervals and smoothingTracking
Memory and threadsBorrowed buffers, owned results, session reuse and worker teardownArchitecture
C ABIHandles, status codes and HFSessionConfigV2C API
Android deploymentAAR, assets, Gradle/ABI, CameraX and JNI pairingAndroid
Apple APIsObjective-C errors, Swift types, scoped views and complete detection examplesObjective-C and Swift
iOS deploymentDevice / simulator XCFrameworks, Xcode linkage, camera buffers and CoreMLiOS
macOS deploymentIntel / Apple Silicon frameworks, embedding, signing and native librariesmacOS
HarmonyOSHAR, ArkTS, Node-API and worker ownershipHarmonyOS
ARM CPUImage preprocessing, memory reuse and camera latencyARM deployment
NVIDIATensorRT SDK, CUDA runtime and device selectionTensorRT
RockchipSoC model packs, toolchains, RK runtime and RGARockchip, Python on Rockchip
DiagnosticsVersion, error text, runtime diagnostics and resource countersAPI recipes, Troubleshooting
PerformanceWarm-up, timing boundaries, median/p95 and queue delayPerformance

For parameter types, overloads and additional settings, refer to the headers and wrapper shipped with your SDK version.

Image processing with InspireCV

InspireCV is a standalone C++ library. Its guide covers Image I/O and operations, float images, Task transforms and tensors, error handling, repeated-frame memory reuse and optional CUDA processing. Its PixelFormat, rotation and pipeline types are separate from InspireFace's C API and FrameProcess.

For the full public interface, see InspireFace C declarations, native C++ headers, Objective-C header, Swift overlay, Python wrapper, HarmonyOS ArkTS exports and InspireCV headers. Use the headers bundled with a release as the reference for its binary.

Integration notes

  • For Android capture and snapshots, update the Java classes and JNI library together to the version used in the guide.
  • Copying a C++ face-result vector retains its geometry and tokens. Keep the corresponding frame pixels as well if you will extract features later.
  • In ArkTS, release tracking snapshots with session.releaseFaceResult() and call close() on streams, bitmaps, capture sessions and sessions when finished. Keep each wrapper object on the worker that created it.
  • The standard HarmonyOS HAR runs MNN on CPU and accepts raw image buffers. Use HarmonyOS APIs to decode files and display images.
  • Objective-C and Swift wrap the native handles. ARC owns the wrapper object; borrowed face, feature and pixel pointers still have the native lifetime limits.
  • CoreML, TensorRT, RKNN, RGA and CUDA preprocessing require their matching SDK build and runtime. Follow the target platform's deployment guide.
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Last Updated:: 9/28/26, 8:17 PM
Contributors: Jingyu
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