Converts Machine Learning models to ONNX for use in Windows ML
Project description
Introduction
WinMLTools enables you to convert models from different machine learning toolkits into ONNX for use with Windows ML. Currently the following toolkits are supported:
Apple Core ML
scikit-learn (subset of models convertible to ONNX)
xgboost
libSVM
RevoScalePy
Keras
Install
pip install winmltools
Dependancies
scikit-learn is needed to convert a scikit-learn model, coremltools for Apple Core ML.
Example
Here is a simple example to convert a Core ML 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
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
File details
Details for the file winmltools-1.2.0.803-py2.py3-none-any.whl.
File metadata
- Download URL: winmltools-1.2.0.803-py2.py3-none-any.whl
- Upload date:
- Size: 22.8 kB
- Tags: Python 2, Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.18.4 setuptools/39.0.1 requests-toolbelt/0.8.0 tqdm/4.24.0 CPython/3.6.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 3f0a4841c0dfa4ec59b49da70aae196565b1716aceace0c474267d383deecb77 |
|
| MD5 | e915b2fdb1a7e654fc39631bba504eec |
|
| BLAKE2b-256 | 76acd0108acf4a513971904460b81dfac11987c5e2f9f20e98d9ed7fc1e6adb4 |
