Skip to main content

Community Tools for CoreML

Project description

Core ML is an Apple framework which allows developers to simply and easily integrate machine learning (ML) models into apps running on Apple devices (including iOS, watchOS, macOS, and tvOS). Core ML introduces a public file format (.mlmodel) for a broad set of ML methods including deep neural networks (both convolutional and recurrent), tree ensembles with boosting, and generalized linear models. Models in this format can be directly integrated into apps through Xcode.

coremltools is a python package for creating, examining, and testing models in the .mlmodel format. In particular, it can be used to:

  • Convert existing models to .mlmodel format from popular machine learning tools including Keras, Caffe, scikit-learn, libsvm, and XGBoost.
  • Express models in .mlmodel format through a simple API.
  • Make predictions with an .mlmodel (on select platforms for testing purposes).

Installation

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.

Dependencies

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

License

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.

Project details


Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page