Deep Learning Toolbox Converter for ONNX Model Format

Import and export ONNX™ models within MATLAB for interoperability with other deep learning frameworks

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Actualizada17 Aug 2022

Import and export ONNX™ (Open Neural Network Exchange) models within MATLAB for interoperability with other deep learning frameworks. ONNX enables models to be trained in one framework and transferred to another for inference.

Opening the onnxconverter.mlpkginstall file from your operating system or from within MATLAB will initiate the installation process for the release you have.
This mlpkginstall file is functional for R2018a and beyond.

Usage example:
%% Export to ONNX model format
net = squeezenet; % Pretrained Model to be exported
filename = 'squeezenet.onnx';
exportONNXNetwork(net,filename);

%% Import the network that was exported
net2 = importONNXNetwork('squeezenet.onnx', 'OutputLayerType', 'classification');

% Compare the predictions of the two networks on a random input image
img = rand(net.Layers(1).InputSize);
y = predict(net, img);
y2 = predict(net2,img);

max(abs(y-y2))

To import an ONNX network in MATLAB, please refer:
//www.tianjin-qmedu.com/help/deeplearning/ref/importonnxnetwork.html

To export an ONNX network from MATLAB, please refer:
//www.tianjin-qmedu.com/help/nnet/ref/exportonnxnetwork.html

Compatibilidad con la versión de MATLAB
Se creó con R2018a
Compatible con la versión R2018a a la R2022a
Compatibilidad con las plataformas
Windows macOS Linux

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