The Edge AI SDK provides the building blocks for customers to start development on any use cases discussed in this paper for AM68A. TI supports three ways of running a typical edge AI use case on the AM68A Starter Kit. Documentation for these three methods is found in the Edge AI sample apps section in the SDK documentation.

• Trying the out-of-box edge AI gallery application
• Developing edge AI applications using Python and C++ reference examples
• Running ‘No Code’ optimized end-to-end GStreamer applications – OpTIFlow

The following edge AI SDK packages are building blocks for DL demonstrations for AM68A:

• Image Classification: Detects top 5 classes from the ImageNet data set for a given input frame
• Object Detection: Detects and draws bounding boxes around the objects, also classifies the objects to one of the classes in COCO data set
• Semantic Segmentation: Classifies each pixel into class in ade20k data set

Along with the DL demonstrations other supported data flows are available in the Edge AI dataflows in the SDK documentation.