Converting TF models to CoreML, an iOS-friendly format
While TensorFlow Lite seems to be a natural choice for Android software engineers, on iOS, it doesn’t necessarily have to be the same. In 2017, when iOS 11 was released, Apple announced Core ML, a new framework that speeds up AI-related operations.
If you are fresh in machine learning on mobile, Core ML will simplify things a lot when adding a model to your app (literally drag-and-drop setup). It also comes with some domain-specific frameworks – Vision (computer vision algorithms for face, rectangles or text detection, image classification, etc.), and Natural Language.
Core ML and Vision give us a possibility to run inference process with the use of custom machine learning model. And those models may come from machine learning frameworks like TensorFlow.
In this article, we will see how to convert TensorFlow model to CoreML format and how to compare models side by side.