Enhance Your App with Real-Time Pose Estimation
Incorporating real-time pose estimation in your applications can revolutionize user engagement and functionality. PoseTracker API provides a robust, cross-platform solution that integrates seamlessly via WebView or iFrame, making it compatible with all programming environments from native mobile apps to web applications. No SDK and useless import needed.
Technical Foundations:
PoseTracker leverages TensorFlow's MoveNet model, a state-of-the-art pose estimation model renowned for its speed and accuracy. MoveNet model enables the detection of 17 key body points in real-time from an image, making it the backbone of PoseTracker's high-performance capabilities. This integration not only enhances the precision of pose tracking but also ensures a seamless experience across various platforms, from mobile devices to web applications. More on MoveNet can be found here.
If you're interested in exploring the top human pose estimation models optimized for mobile apps in 2024, be sure to check out our guide on the best real-time pose estimation models available.
How does it work:
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What Data Does PoseTracker Provide?
- The user's skeleton is mapped based on 17 key body points detected through their camera:
- Real-time posture analysis, feedback, and repetition counting based on the provided exercise and the movements.
- More info here
Seamless Integration Across Platforms:
PoseTracker’s flexibility ensures it can be integrated into any development framework. Whether you're working with native technologies like Swift for iOS, Kotlin for Android, or web technologies such as ReactJS, or even no-code platforms like Bubble.io, FlutterFlow or outsystems, PoseTracker adapts effortlessly. This compatibility eliminates the usual integration headaches, allowing you to focus on enhancing your application’s features.
Why Choose PoseTracker?
- Stable and Flexible: PoseTracker is built on robust frameworks like TensorFlow, utilizing advanced models such as MoveNet for accurate and swift pose estimation. Our flexible architecture allows for seamless model interchangeability, enabling the integration of alternative models like PoseNet, BlazePose, or DensePose whenever advancements or specific use-case demands arise.
- Cross-Platform Compatibility: Works seamlessly within web views across all device types, ensuring a consistent user experience whether on mobile or desktop.
- Easy to Implement: Implementing PoseTracker is as simple as embedding an iFrame or adding a WebView to your project, significantly reducing development time and effort.
Getting Started:
To get started with PoseTracker, simply include our API within your project's WebView or iFrame. Here’s a brief snippet to demonstrate how easy it is to integrate:
<iframe src="https://www.posetracker.com/pose_tracker/tracking?token=YOUR_API_KEY&exercise=squat"
width="350"
height="350"
allow="camera *;">
</iframe>
Ready to take your app’s to the next level? Create your account for free to learn more about our easy-to-integrate pose estimation API and start building more engaging and personalized user experiences today.
