Convert ONNX (Open Neural Network Exchange)models into Apple CoreML format.
Project description
This tool converts ONNX models to Apple CoreML format.
Installation
pip install -U onnx-coremlDependencies
click
numpy
coremltools (0.6.3+)
onnx (0.2.1+)
How to use
Using this library you can implement converter for your models. To implement converters you should use single function “convert” from onnx_coreml:
from onnx_coreml import convertThis function is simple enough to be self-describing:
def convert(model,
mode=None,
image_input_names=[],
preprocessing_args={},
image_output_names=[],
deprocessing_args={},
class_labels=None,
predicted_feature_name='classLabel')Parameters
Returns
model: A coreml model.
CLI
Also you can use command-line script for simplicity:
convert-onnx-to-coreml [OPTIONS] ONNX_MODEL
Currently supported
Models
Models from https://github.com/onnx/models are supported and tested.
Operators
List of ONNX operators that can be converted into their CoreML equivalent:
Conv
Relu
Reshape
Transpose
MaxPool
AveragePool
FC
BatchNormalization
Add
Sum
Mul
LeakyRelu
Concat
GlobalAveragePool
GlobalMaxPool
Softmax
Gemm
LRN
Some of operators are partially compatible because CoreML doesn’t support broadcasting, gemm for arbitrary tensors, etc.
License
Copyright (c) 2017 Prisma Labs, Inc. All rights reserved.
Use of this source code is governed by the MIT License that can be found in the LICENSE.txt file.
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Source Distributions
Built Distribution
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