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39 lines
1.2 KiB
Markdown
39 lines
1.2 KiB
Markdown
---
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title: API Basics
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parent: Tutorials
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nav_order: 1
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---
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# ONNX Runtime Inferencing: API Basics
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{: .no_toc }
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These tutorials demonstrate basic inferencing with ONNX Runtime with each language API.
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## Contents
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{: .no_toc }
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* TOC placeholder
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{:toc}
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## Python
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* [Scikit-learn Logistic Regression](https://microsoft.github.io/onnxruntime/python/tutorial.html)
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* [Image recognition (Resnet50)](https://github.com/onnx/onnx-docker/blob/master/onnx-ecosystem/inference_demos/resnet50_modelzoo_onnxruntime_inference.ipynb)
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## C++
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* [Number recognition (MNIST)](../tutorials/mnist_cpp.html)
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* [Image classification (Squeezenet)](https://github.com/microsoft/onnxruntime/blob/master/csharp/test/Microsoft.ML.OnnxRuntime.EndToEndTests.Capi/CXX_Api_Sample.cpp)
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## C
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* [Image classification (Squeezenet)](https://github.com/microsoft/onnxruntime/blob/master/csharp/test/Microsoft.ML.OnnxRuntime.EndToEndTests.Capi/C_Api_Sample.cpp)
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## C#
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* [Object detection (Faster RCNN)](../tutorials/fasterrcnn_csharp.html)
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* [Image recognition (ResNet50 v2)](../tutorials/resnet50_csharp.html)
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## Java
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* [Number recognition (MNIST)](../tutorials/mnist_java.html)
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## JavaScript
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* [ONNX Runtime JavaScript examples](https://github.com/microsoft/onnxruntime-inference-examples/tree/main/js)
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