PoseTracker is a real-time pose estimation SDK and API for fitness and rehab apps. It runs MoveNet on-device on React Native, iOS, Android and the web. Keypoints are free. An optional API key adds rep counting, joint angles and a form score.

Guide: https://www.posetracker.com/news/react-native-pose-estimation-expo

Docs: https://docs.posetracker.com/quickstart

PoseTracker React Native — Light (online) Human Pose Estimation SDK

⭐ Star us on GitHub: Movelytics/react-native-pose-estimation-light — it helps other React Native and Expo developers find the SDK.

Try it on your phone (no Xcode / Android Studio):

1. Install Expo Go
2. Open the Expo Snack → Run on device
3. Scan the QR — live pose estimation, no API key

Steps and QR: https://docs.posetracker.com/try-expo-go

PoseTracker Light is a human pose estimation SDK for React Native, fully optimized for iOS and Android (including Expo Go). Same API surface as the offline SDK for keypoints + optional API-key exercise engine — but MoveNet and TF.js load from the network each WebView boot, so the npm package stays tiny.

Offline vs Light — which package?

	Offline (bundled)	Light (this package)
npm	@pose-tracker/react-native-pose-estimation	@pose-tracker/react-native-pose-estimation-light
GitHub	react-native-pose-estimation	react-native-pose-estimation-light
Packed tarball	~9.9 MB	~206 kB (~48× smaller)
Unpacked	~14.7 MB	~779 kB
MoveNet / TF.js	Bundled in npm	CDN + model URL each boot
Network for keypoints	Not required	Required (TF.js + model)
Expo Go	Yes	Yes
API surface	Keypoints free; paid engine with API key	Same

Choose offline when you need pose without a network, or want zero model download at session start.
Choose light when app install / OTA size matters and devices are online.

Full comparison: LIGHT_SDK.md.

Agents: shared UX/API/bugfixes → mirror to offline (or ask first). See DUAL_SDK_CHANGES.md.

Install

npm install @pose-tracker/react-native-pose-estimation-light react-native-webview
# Expo:
npx expo install react-native-webview expo-camera

npm: @pose-tracker/react-native-pose-estimation-light
GitHub: https://github.com/Movelytics/react-native-pose-estimation-light
Offline sibling: @pose-tracker/react-native-pose-estimation

Required: host app must declare camera permissions — see PERMISSIONS.md.

Media inputs (v0.2): camera (default), uploaded video, still image — host picks the file. See MEDIA_SOURCES.md and https://docs.posetracker.com/media-sources.

Quick start (keypoints — needs network, no API key)

import {
  PoseTrackerProvider,
  WebViewPoseView,
  usePoseTracker,
} from '@pose-tracker/react-native-pose-estimation-light';

function App() {
  return (
    <PoseTrackerProvider
      options={{
        model: 'movenet', // Docs API parity (default)
        // modelUrl: 'https://…/model.json', // optional override
      }}
    >
      <CameraScreen />
    </PoseTrackerProvider>
  );
}

function CameraScreen() {
  usePoseTracker({
    onKeypoints: (e) => {
      console.log(e.keypoints.length, e.score);
    },
  });

  return (
    <WebViewPoseView
      style={{ flex: 1 }}
      drawSkeleton
      loadingText="AI Loading"
      coldStart="full"
      // Default source="camera". Host-picked file:
      // source="image" sourceUri={fileUri}
      // source="video" sourceUri={fileUri}
    />
  );
}

Default model URL

https://app.posetracker.com/scripts/tmp_model_to_remove.json

Same MoveNet SinglePose Lightning topology as the PoseTracker Front tracking product. Weight shards are relative neighbors (group1-shard1of2.bin, …). TF.js loads from jsDelivr (@tensorflow/*@4.22.0) unless you override tfjsCdnBase / tfjsVersion.

WebView baseUrl

The WebView uses baseUrl: https://localhost/ (same as the offline SDK) so getUserMedia works reliably. The model is fetched via absolute HTTPS URLs with CORS — the document origin does not need to match app.posetracker.com.

Full tracking (API key)

Same contract as the offline SDK / web tracking URL:

<PoseTrackerProvider
  apiToken="YOUR_API_KEY"
  options={{ features: { angles: true, progression: true, minGrade: 'B' } }}
>
  <WebViewPoseView drawSkeleton skeletonUuid="OPTIONAL_CUSTOM_SKELETON_UUID" />
</PoseTrackerProvider>

External frames (your camera, our data)

Full guide, including Vision Camera and expo-camera: https://docs.posetracker.com/external-frames

Optional. Use it when your app already owns the camera (VisionCamera, a custom pipeline, a recorded file) and you only need the data. PoseTracker runs pose estimation and the exercise engine on every frame you push, and returns the same events as the camera flow: keypoints, posture/placement, counter, form score, progression. Nothing is drawn, so you render what you want.

const { warmupExternal, startExercise, processFrame } = usePoseTracker({
  onCounter: (e) => setReps(e.count), // listeners still fire
});

await warmupExternal(); // no camera permission, no getUserMedia
startExercise('squat');

// For each frame from your camera:
const { dropped, pose, events } = await processFrame({
  base64: jpegBase64, // or uri: 'file:///…' / 'data:image/jpeg;base64,…'
  width: 256,
  height: 192,
  timestampMs: Date.now(),
  mirrored: true, // front camera (default). false for the back camera.
});
if (!dropped) {
  // pose.keypoints are normalized (0..1) to the frame you sent
  // events: everything emitted for this frame (counter, posture, …)
}

• The Provider mounts a hidden 1×1 warmer after warmupExternal(). It is not needed if a <WebViewPoseView /> is already on screen. The light package still needs network for the model.
• One frame in flight at a time: an overlapping call resolves at once with { dropped: true, pose: lastPose, events: [] }. Await before pushing the next one.
• Keep the longest side of each frame at about 256 px or less. A 1080p JPEG per frame is not real-time over the bridge.
• The engine is temporal: push frames in order and keep the same session across frames.
• Don't mix the two flows. processFrame throws while the SDK camera is open.
• processFrame before warmupExternal() throws.

Cold-start

Mode	API	Camera permission
basic (default)	preload()	No — TF.js/model warm-up only
full	preload({ coldStart: 'full' })	Yes — when user expects camera

Documentation

Doc	Topic
LIGHT_SDK.md	Offline vs light, sizes, model URL
PERMISSIONS.md	Camera permission setup (required)
PRELOAD.md	Preload / warm-up / lifecycle
FEATURES.md	Plan gating, watermark, loading text
EVENTS.md	Typed events + classic onMessage

FAQ

Does it work without an API key?
Yes for keypoints — but a network is still required to load TF.js + MoveNet.

Does it support Expo Go?
Yes (react-native-webview peer).

BlazePose?
Pass model: 'blazepose' on PoseTrackerProvider options. Loads @tensorflow-models/pose-detection from jsDelivr in the WebView (lite / TF.js). Keypoints stay COCO-17. Heavier than MoveNet — expect lower FPS on mid-range Android. The offline package can run the same CDN BlazePose path but still ships unused bundled MoveNet; use light unless you need offline MoveNet.

Who sees the watermark?
Keyless and free plans. Freemium watermark now links to posetracker.com (utm_medium=react-native) via Linking.openURL. Hidden for paid plans. Set showWatermark={false} to remove it.

How does Claude or Cursor integrate this SDK?
Add the connector https://mcp.posetracker.com/api/mcp, sign in, and click Allow at https://app.posetracker.com/oauth/authorize. The agent writes the snippet on your account. Docs: https://docs.posetracker.com/ai/mcp-connector.

License

Proprietary — Movelytics SAS / PoseTracker. See LICENSE.

Third-party components (TensorFlow.js, MoveNet Lightning) are Apache 2.0 — see THIRD_PARTY_NOTICES.md.

Links

• Product: https://www.posetracker.com
• Docs: https://docs.posetracker.com
• Try on your phone: https://docs.posetracker.com/try-expo-go
• Expo Snack: https://snack.expo.dev/@fsepret/posetracker-sdk-light-demo-app
• Light demo: https://github.com/Movelytics/react-native-pose-estimation-light-demo
• Offline SDK: https://github.com/Movelytics/react-native-pose-estimation