1. Overview

Welcome to Processor SDK Linux Edge AI for TDA4VM !

The SDK provides software and tools to let the users effectively balance deep learning performance with system power and cost on Texas Instrument’s processors for edge AI applications. We offer a practical embedded inference solution for next-generation vehicles, smart cameras, edge AI boxes, and autonomous machines and robots. In addition to general purpose micro processors, TDA4VM has integrated micro controllers, DSP, and accelerators for neural network, image, vision, and multimedia processing. With a few simple steps one can run high performance computer vision and deep learning demos using a live camera and display.





Fig. 1.1 Processor SDK Linux Edge AI for TDA4VM feature overview

The SDK also enables an interplay of multiple open-source components such as GStreamer, OpenVx, OpenCV and deep learning runtime such as TFLite, ONNX and Neo-AI DLR. The reference applications showcase perception based examples such as image classification, object detection and semantic segmentation in both Python and C++ variants. The SDK supports edit-build-debug cycles directly on the target and also on PC to cross compile and build the applications.


Fig. 1.2 Industry Standard Components supported in Processor SDK Linux Edge AI for TDA4VM

The SDK mainly comprises of three parts as shown in the illustration below. The Edge AI application stack is used to run analytics applications with real-time inputs/outputs. The Foundational Linux components providing OS, uBoot, kernel, filesystem, linux drivers and firmware for the remote core and hardware accelerators.


To get started with the setup click the Next button.