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Introduction

ONNXMLTools enables you to convert models from different machine learning toolkits into ONNX. Currently the following toolkits are supported:

• Apple CoreML
• scikit-learn (subset of models convertible to ONNX)

(To convert ONNX model to CoreML, see onnx-coreml)

Getting Started

Clone this repository on your local machine.

Install

You can install latest release of ONNXMLTools from pypi:

pip install onnxmltools

or install from source:

pip install git+https://github.com/onnx/onnxmltools

Note:If you choose to install onnxmltools from its source code, you must set an environment variable ONNX_ML=1 before installing onnx package.

Dependencies

This package uses ONNX, NumPy, and ProtoBuf. If you are converting a model from scikit-learn or Apple Core ML you need the following packages installed respectively:

1. scikit-learn
2. CoreMLTools

Example

Here is a simple example to convert a CoreML model:

import onnxmltools
import coremltools

model_coreml = coremltools.utils.load_spec('image_recognition.mlmodel')
model_onnx = onnxmltools.convert_coreml(model_coreml, 'Image_Reco')

# Save as text
onnxmltools.utils.save_text(model_onnx, 'image_recognition.json')

# Save as protobuf
onnxmltools.utils.save_model(model_onnx, 'image_recognition.onnx')

License

MIT License

Acknowledgments

The initial version of this package was developed by the following engineers and data scientists at Microsoft during winter 2017: Zeeshan Ahmed, Wei-Sheng Chin, Aidan Crook, Xavier Dupre, Costin Eseanu, Tom Finley, Lixin Gong, Scott Inglis, Pei Jiang, Ivan Matantsev, Prabhat Roy, M. Zeeshan Siddiqui, Shouheng Yi, Shauheen Zahirazami, Yiwen Zhu.