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
5 maintainers
Release files for winmltools 0.1.0.5072
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| winmltools-0.1.0.5072-py2.py3-none-any.whl | Python 2, Python 3 | none | any | Details |
Release files / winmltools-0.1.0.5072-py2.py3-none-any.whl
| Download URL | winmltools-0.1.0.5072-py2.py3-none-any.whl |
|---|---|
| Size | 20.1 kB |
| Tags | Python 2 Python 3 |
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