Core ML is an Apple framework that allows developers to easily integrate machine learning (ML) models into apps. Core ML is available on iOS, iPadOS, watchOS, macOS, and tvOS. Core ML introduces a public file format (.mlmodel) for a broad set of ML methods including deep neural networks (convolutional and recurrent), tree ensembles (boosted trees, random forest, decision trees), and generalized linear models. Core ML models can be directly integrated into apps within Xcode.
coremltools is a python package for creating, examining, and testing models in
the .mlmodel format. In particular, it can be used to:
- Convert trained models from popular machine learning tools into Core ML format (.mlmodel).
- Write models to Core ML format with a simple API.
- Making predictions using the Core ML framework (on select platforms) to verify conversion.
The method for installing coremltools follows the
standard python package installation steps.
Once you have set up a python environment, run:
pip install -U coremltools
The package documentation contains more details on how to use coremltools.
coremltools has the following dependencies:
- numpy (1.10.0+)
- protobuf (3.1.0+)
In addition, it has the following soft dependencies that are only needed when you are converting models of these formats:
- Keras (1.2.2, 2.0.4+) with corresponding TensorFlow version
- XGBoost (0.7+)
- scikit-learn (0.17+)
- LIBSVM
Copyright (c) 2018, Apple Inc. All rights reserved.
Use of this source code is governed by the 3-Clause BSD License that can be found in the LICENSE.txt file.