Image Labeling


If you haven’t set up the SDK yet, make sure to go through those directions first. You’ll need to add the Core library to the app before using the specific feature API or custom model. Follow iOS setup or Android setup directions.

Image Labeling In Action

With the Image Labeling feature, you can identify the contents of an image or each frame of live video. Each prediction returns a set of labels as well as a confidence score for each label. Image Labeling can recognize people, places, and things. The underlying ML model was trained on millions of images and hundreds of labels.

If you need to know what objects are in an image, and where they are, consider using Object Detection instead.

Runs On-Device

The Image Labeling feature makes predictions completely on-device. No internet connection is required to interpret images or video through this on-device model. No internet dependency means super-fast performance.

Live Video Performance

Image Labeling is designed to run on live video with a fast frame rate. Exact FPS performance varies depending on device, but it should be possible to run this feature on live video on modern mobile devices.


The image labeling model supports 1,000 labels. View the full label list.