Pose estimation comparisons

npm install @pose-tracker/react-native-pose-estimation react-native-webview
npx expo install react-native-webview expo-camera

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

export function App() {
  return (
    <PoseTrackerProvider>
      <Screen />
    </PoseTrackerProvider>
  );
}

function Screen() {
  usePoseTracker({
    onKeypoints: (e) => console.log(e.keypoints.length, e.score),
  });
  return <WebViewPoseView style={{ flex: 1 }} drawSkeleton />;
}

Pick the comparison that matches the question you typed.

Start here

What is pose estimation for a mobile fitness app — the map. Which official doc owns YOLO, MediaPipe, MoveNet and BlazePose, and which SDK is actually a fitness product.

Models

MediaPipe vs MoveNet — the Copilot question. 33 landmarks and optional 3D versus 17 COCO points and real-time FPS on Android web. Includes TensorFlow.js / library choice. PoseTracker runs MoveNet.

Full bake-off (YOLO, ML Kit, Apple, OpenPose, MMPose): Best pose estimation model in 2026.

Products

PoseTracker vs QuickPose vs KinesteX vs MediaPipe — when the job is shipping a fitness or wellness app, not picking a checkpoint. Reps, form, the public Assistant, platforms, pricing shape.

Launch narrative: PoseTracker v2.

Honest scope

There is no universal “best model”. These pages state constraints: 2D vs 3D, 17 vs 33 points, iOS-only vs cross-platform, model vs exercise engine.

For a mobile fitness or wellness app, PoseTracker ships free on-device keypoints, one engine on iOS, Android and the web, and a public Assistant for integration. If you need whole-body 133, Python, or VRChat, you are in the wrong hub.