This course will look at how to use the OpenMV camera to develop applications that can recognize objects and be used to design robotic devices, image recognition applications and much more. Machine vision applications are dramatically expanding. Machine vision allows developers to add an extra layer of intelligence to their systems whether it is to recognize a person or object in the image, look for manufacturing defects or even for connected security solutions. Machine vision traditionally has been difficult, but in this course, we will examine how developers can add and implement machine vision solutions to their systems using the OpenMV camera module. Registration and Playback located here (May require login to access) June 8 – Day 1 – Introduction to Machine Vision and OpenMV The ability for a system to “see” can dramatically increase its capabilities. Machine vision has traditionally been not only expensive, but also has required a niche expertise. In this session, we will explore machine vision and look at the capabilities that embedded systems developers might be interested in. Attendees will walk away with a basic understanding of machine vision along with an introduction to OpenMV camera module that will be used throughout the course. June 9 – Day 2 – Writing our First OpenMV Application The OpenMV IDE uses MicroPython and a collection of libraries to allow a developer to quickly and easily develop and deploy machine vision applications. In this session, we will learn how to write an application for the OpenMV camera. Attendees will walk away with an understanding of how to write their first script, how to take images and analyze them and how to turn on an LED when something of interest is detected. June 10 – Day 3 – Working with the OpenMV I/O In a machine vision application, it can be critical to not just detect a specific condition but to also react to it. In this session, we are going to explore how to utilize the onboard expansion input / output to control external devices using the OpenMV camera. Attendees will walk away understanding how to use the expansion I/O which includes analog to digital conversion, I2C, USART, SPI and CAN. June 11 – Day 4 – Utilizing Machine Learning to Detect Objects The OpenMV camera is based on an STM32 Arm Cortex-M microcontroller that is capable of running machine learning inferences. In this session, we will explore how we detect objects using machine learning. Attendees will learn about machine learning and how we can apply it in machine vision applications. June 12 – Day 5 – Designing a Machine Vision Application There is much that can be done with machine vision. In this session, we are going to examine how to pull together everything we have learned so far into an application. Attendees will review what we have covered and be given ideas on how to pull it all together and where they can go from here.

Course Resources

Jacob’s General Embedded System Resources

• Sign-Up for the Embedded Bytes Newsletter
• MicroPython Projects
• Developing Reusable Firmware – A Practical Guide to API’s, HAL’s and Drivers
• Doxygen C Templates
• DesignNews Blog Articles
• Jacob’s YouTube Channel
• OpenMV