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[[File:onnx.png|thumb|right|200px|ONNX]] | |||
The Open Neural Network Exchange (ONNX){{ref|ONNX}} is an open-source artificial intelligence format for among other things representing machine learning algorithms. | The Open Neural Network Exchange (ONNX){{ref|ONNX}} is an open-source artificial intelligence format for among other things representing machine learning algorithms. | ||
[[PyTorch]] models can be exported to ONNX files and used as an input for the [[Inference Overlay]]. | [[PyTorch]] models can be exported to ONNX files and used as an input for the [[Inference Overlay]]. | ||
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|seealso= | |seealso= | ||
* [[Inference Overlay]] | * [[Inference Overlay]] | ||
* [[Region-based Convolutional Neural Network (Inference Overlay)| | * [[Region-based Convolutional Neural Network (Inference Overlay)|RCNN]] | ||
* [[PyTorch]] | * [[PyTorch]] | ||
* [[Demo Training Data Project]] | * [[Demo Training Data Project]] | ||
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}} | }} | ||
</references> | </references> | ||
|api=* [[Api session event editor neuralnetwork add]] | |||
}} | }} | ||
{{GeoDataOverview}} | {{GeoDataOverview}} | ||
Latest revision as of 08:12, 3 August 2026
The Open Neural Network Exchange (ONNX)[1] is an open-source artificial intelligence format for among other things representing machine learning algorithms. PyTorch models can be exported to ONNX files and used as an input for the Inference Overlay.
Dragging an ONNX file onto the Tygron Client Application allows you to:
- Import it as a Region-based Convolutional Neural Network (RCNN) in your project
- Import it with a new Inference Overlay. This also imports it as a new Neural Network and configures it automatically for the newly added Inference Overlay
How-to's
- How to import an ONNX file using drag and drop
- How to import an ONNX file for an Inference Overlay
- How to train your own AI model for an Inference Overlay
See also
API Endpoints
References
- ↑ ONNX ∙ Found at: https://onnx.ai/ ∙ (last visited: 2024-09-21)