This is a text version of this video: packagemain #5: Face Detection in Go using OpenCV and MachineBox. I found a very nice developer-friendly project MachineBox, which provides some machine learning tools inside Docker Container, including face detection, natural language understanding and few more. And it has SDK in Go, so we will build a program which will detect my face. We will also use OpenCV to capture video from Web camera, it also has Go bindings. MachineBox can be installed very easily by running Docker container.

Companies are trying to understand the content of their videos, automatically and at very large scale. So far, Machine Box boxes were built for images, but today we are introducing Videobox: a simple and effective way to bring video support to Facebox, Tagbox and Nudebox. Machine Box puts state of the art machine learning capabilities into Docker containers so developers can easily incorporate natural language processing, facial detection, image recognition, and more into their own apps, very quickly. The boxes are built for scale, so when your app really takes off just add more boxes horizontally, to infinity and beyond. Videobox is a new box (Docker container) that runs videos through other Machine Box services.

With Facebox, using a simple http API, you can do face detection and recognition in your own data. Facebox can also be taught to recognise any number of people. To recognise people you have to invoke /facebox/teach with a name,id and an image with a single face on it. You only need one photo per person. After you've taught Facebox with the people you want it to recognize, you can start recognising faces by invoking the /facebox/check endpoint.