What an amazing time at the Canadian Largest Makeathon: MakeUofT (https://ieee.utoronto.ca/makeuoft/). The event, people and ideas are great. And now it’s time to share some of the materials used during my session
How a PoC at home can scale to Enterprise Level using Custom Vision APIs
It all started with a DIY project to use Computer Vision for security cameras at home. A custom Machine Learning model is the core component used to analyze pictures to detect people, animals and more in a house environment. The AI processing is performed at the edge, in dedicated hardware and the collected information is stored in the cloud.
The same idea can be applied to several CCTV scenarios, like parking lots, train stations, malls and more. However, moving this into enterprise scale brings a set of challenges, which are going to be described and explained in this session.
These are the slides I’ve used
And the source code is available here
In the source code you can find the console and Windows 10 app samples I’ve coded live and also the exported images of my custom vision demo project in windows, linux and raspberry pi flavors. The 3rd one is where I spent some time updating the original linux one to work on the small device.
And as usual a couple of interesting links
- Custom Vision
- Custom Vision Documentation
- Taking a Look at Computer Vision’s Object Detection
- Deploying Docker Containers On A Raspberry Pi Device
- Custom Vision + Azure IoT Edge on a Raspberry Pi 3
- Raspberry Pi Visual Studio Code: Installing VS Code on Raspbian
Greetings @ Toronto