Perform high performance face tracking with the UltraFace face detection model. This package requires the open source NatML library to run the machine learning model. Features include:


+ Bare Metal Performance. The UltraFace predictor is implemented with NatML, which takes advantage of hardware machine learning accelerators, like CoreML on iOS and macOS, NNAPI on Android, and DirectML on Windows. View the model performance statistics on NatML Hub.


+ Extremely Easy to Use. The UltraFace predictor accepts an image and returns an array of rectangles, each corresponding to a detected face. See more on NatML Hub.


+ Cross Platform. The UltraFace predictor supports Android, iOS, macOS, and Windows alike, allowing you to develop in the Editor and deploy to device in one seamless workflow.


+ Augmented Reality. This predictor is particularly suited for augmented reality applications, where it can recognize faces in the camera view.


+ Lightweight Package. This package contains the predictor scripts, whereas the ML model will be downloaded at runtime from NatML Hub and cached onto the device, reducing the app size significantly.


Find other ML models on NatML Hub.


Join the NatSuite community on Discord.


Check out the NatML documentation.


See more NatSuite projects on GitHub.


Read the NatML blog.


Discuss NatML on Unity Forums.


Contact us at hi@natsuite.io.