Microsoft ML Tool to convert machine learning models to ONNX for use with Windows Machine Learning
Project description
Introduction
WinMLTools enables you to convert models from different machine learning toolkits into ONNX for use with Windows Machine Learning. Currently the following toolkits are supported:
Apple CoreML
scikit-learn (subset of models convertible to ONNX)
LibSVM
XGBoost
Install
pip install winmltools
Dependancies
This converter package extends the functionalities of ONNXMLTools.
scikit-learn is needed to convert a scikit-learn model, coremltools for Apple CoreML.
Example
Here is a simple example to convert a CoreML model:
import winmltools import coremltools model_coreml = coremltools.utils.load_spec("image_recognition.mlmodel") model_onnx = winmltools.convert.convert_coreml(model_coreml, "Image_Reco") # Save as text winmltools.utils.save_text(model_onnx, "image_recognition.json") # Save as protobuf winmltools.utils.save_model(model_onnx, "image_recognition.onnx")
License
MIT License
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
No source distribution files available for this release.See tutorial on generating distribution archives.
Built Distribution
Close
Hashes for winmltools-0.1.0.5069-py2.py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 017fe8481864b1eed41343d0697d9a3fe336d095af7844683aff9b2ae23c496b |
|
MD5 | 9794c45fbecd05308aad5bccaddc1d99 |
|
BLAKE2b-256 | 6f9ca977ce27407a2e1dfac0b5b145e513b30f69433d1e31423a61abbbcbbf67 |