I have Sonos speakers in my flat. In combination with Spotify, this allows me to play just about whatever music I want, in whichever rooms of the flat, simply by opening the Sonos app on my phone and searching for the artist. The biggest challenge is deciding what to listen to.

I also have a record player in my flat, and a number of vinyl records, in nice sleeves with nice cover art. Even though putting on a record is much less convenient than opening Sonos on my phone, I still get a lot from having them around - primarily the ability to wonder over and flick through a big pile of album art to help decide what I want to listen to: something which is lost by music streaming services.

I had an idea for how I could combine the two; keep the convenience and low cost of music streaming, but also retain a physical presence for my music collection (in my case a pile of records).

The solution is built using a webcam and some Python code (using SimpleCV, SoCo libraries) - take a look at it in action:

Click permalink below to get to the code...

A project of mine requires some image processing and OCR, which has led me into the interesting world of computer vision.

My initial research led me pretty quickly to OpenCV which is used by google among others for all things computer vision. However, this seemed a bit overkill for my use case, and with a steeper learning curve than I was willing to start with, so I decided to start from scratch first to build my knowledge.

After playing around in R and using tools like tesseract and imagemagick, and trying some different cutting, projection and learning techniques, I finally came across the library I had been looking for - SimpleCV is a python library, which is designed to be easy to use, and has wrappers for the big libraries like opencv and tesseract. I also recommend the ebook which doesn't take too long to read, but gets you up to speed quickly with the major fundamentals of computer vision (and how to use them...).

See this video for some demonstrations:

I've been using the library for a while now, in particular the blob extract and feature extraction elements, in order to create features to feed a scikit-learn based svm model, with very good results.

Click permalink below for some advice on how to set up a computer vision rig with SimpleCV.