Image Segmentation allows developers to partition a video or image into multiple segments that represent everyday things. As an example, image segmentation can help identify the outline of people walking in the street or discern the shapes of everyday things in your living room like couches and chairs.
Models Compatible with the API
Architecture Format(s) Size Input Output Benchmarks MobileNet and ICNet variants Core ML (iOS), TensorFlow Lite (Android) ~25 MB 224x224-pixel image Height and width of the mask, Number of classes the model predicts, Probability that pixel belongs to class 30 FPS on iPhone X, 10 FPS on Pixel 2
Prebuilt Models - Include our models directly in your app and use them with the API.
Customizing Models for Image Segmentation
If you have your own dataset and would like to train a custom model that is compatible with the Image Segmentation API, sign up for the Standard Plan on Fritz to access training notebooks.