Now that we have completed our deep dive into using TensorFlow with a Windows Presentation Foundation (WPF) application and ML.NET, it is now time to dive into using Open Neural Network eXchange (ONNX) with ML.NET. Specifically, in this final chapter, we will review what ONNX is, in addition to creating a new example application with a pre-trained ONNX model called YOLO. This application will build on the previous chapter and show the bounding boxes of the objects that the model detects. In addition, we will close out the chapter with suggestions on improving the example, for it to either become a production-grade application or be integrated into a production application.
In this chapter, we will cover the following topics:
- Breaking down ONNX and YOLO
- Creating the ONNX object detection application
- Exploring additional production application enhancements...