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Convert H5 To ONNX

Description

This VI uses the keras2onnx Python utility to perform the conversion. It allows seamless transition from TensorFlow to ONNX format for interoperability and deployment. Optionally, the converted model can be opened in Netron for visualization.

Input parameters

 

Open Netron : boolean, indicating whether to automatically open the resulting ONNX file in Netron after conversion. If true opens in Netron else conversion only.
H5 Model Path : path, path to the input .h5 model file (typically exported from TensorFlow or Keras). The file must contain a valid Keras model structure and weights.
ONNX Model Path : path, path to the destination .onnx file where the converted model will be saved.

 

Output parameters

 

Β standard output : string, text output from the underlying Python process. Can include logs, conversion info, or warnings.
Β standard error : string, text output capturing any error messages from the Python process, useful for debugging failed conversions.

 

Example

All these exemples are snippets PNG, you can drop these Snippet onto the block diagram and get the depicted code added to your VI (Do not forget to install Deep Learning library to run it).
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