alwaysAI makes building and deploying Computer Vision Apps Easy

At alwaysAI we have the singular mission of making the process of building and deploying computer vision apps to edge devices as easy as possible. That includes training your model, building your app, and deploying your app to edge devices such as the Raspberry Pi, Jetson Nano, and many others. alwaysAI apps are built in Python and can run natively on Mac and Windows, and in our containerized edge runtime environment optimized...

The code for this tutorial is available here: https://github.com/alwaysai/video-streamer

The Raspberry Pi 3B+ and the Raspberry Pi 4 are ubiquitous among the hobbyist community of developers. They are reliable, easy to use single-board computers (SBCs) that are very affordable, making it easy to get your edge computer vision project up and running!

Detecting pedestrians and bicyclists in a cityscape scene is a crucial part of autonomous driving applications. Autonomous vehicles need to determine how far away pedestrians and bicyclists are, as well as what their intentions are. A simple way to detect people and bicycles is to use Object Detection. However, in this case we need much more detailed information about the exact locations of the pedestrians and bicyclists than Object Detection can provide, so we’ll use a technique called...

Detecting people can be an important part of applications across many industries. Common use cases include security applications that track who’s coming and going, as well as safety systems designed to keep people out of harm’s way.