Identify hand orientation using AI
Below is a free classifier to identify hand orientation. Just upload your image, and our AI will predict which hand orientation it is - in just seconds.
Please use a close-up of one hand only
How this classifier works
To start, upload your image. Our AI tool will then predict which hand orientation it is.
This pretrained image model uses the Hands and Palms Dataset dataset and is built with 11000 samples across 4 labels, including Palmar Right, Palmar Left, Dorsal Left, or Dorsal Right.
We'll also show a confidence score (the higher the number, the more confident the AI model is of which hand orientation it is).
Whether you’re a tech-minded hand specialist, just curious, or building hand orientation detection into your application, we hope our classifier proves helpful.
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Need to identify hand orientation at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Retail: Develop more intuitive touchscreen interfaces for self-checkout kiosks. Improve customer experience and reduce checkout times in stores.
- Manufacturing: Create safer robotic assembly lines that detect worker hand positions. Prevent accidents and increase production efficiency in factories.
- Healthcare: Design more accurate gesture-controlled medical imaging systems. Allow surgeons to manipulate 3D scans without breaking sterility during procedures.
- Automotive: Improve driver monitoring systems to detect unsafe hand positions on steering wheels. Reduce accidents caused by distracted or drowsy driving.
- Gaming: Develop more immersive virtual reality experiences with precise hand tracking. Create engaging games and simulations that respond naturally to player movements.
- Security: Enhance biometric authentication systems using hand geometry and positioning. Provide more secure and convenient access control for sensitive areas.
- Accessibility: Create sign language translation tools for better communication with deaf individuals. Bridge communication gaps and promote inclusivity in various settings.