Introduction This tutorial will use the PYNQ Z1 development board and Tensil’s open-source inference accelerator to show how to run machine learning (ML) models on FPGA. We will be using ResNet-20 trained on the CIFAR dataset. These steps should work for any supported ML model – currently all the common state-of-the-art convolutional neural networks are supported. Try it with your model! We’ll give detailed end-to-end coverage that is easy to follow.| k155la3.blog
Introduction This is part II of a two-part tutorial in which we will continue to learn how to build a speech controlled robot using Tensil open source machine learning (ML) acceleration framework, Digilent Arty A7-100T FPGA board, and Pololu Romi Chassis. In part I we focused on recognizing speech commands through a microphone. Part II will focus on translating commands into robot behavior and integrating with the Romi chassis. System architecture Let’s start by reviewing the system archite...| k155la3.blog