Automating scanning film with the help of Lego, a Raspberry Pi and a little machine learning

Tips & Techniques

There are a lot of options out there for scanning film these days, but there’s just something about building a device yourself. This one from Benjamin Bezine does so using Lego and a Raspberry Pi. What makes this solution a little special, though, is that it uses machine learning and vision AI in order to determine the edges of frames, so you don’t need to sit and operate it manually or worry about the number of turns changing as roll thickens and thins out or counting sprockets.

It’s called RoboScan, and Benjamin’s been working on it for a while now (it’s his “lockdown project”) but he’s not finished yet! It’s an open-source project and he’s been uploading the code to GitHub. Only 80 images were used to “train” the Raspberry Pi so that it knows what to look for, but it seems that it’s very effective with just that limited set.

RoboScan uses a backlight behind the film in order to provide even illumination across the frame, and when it detects that a complete frame is in the correct position, it tells the DSLR or mirrorless camera to which it’s attached to shoot a photo. The camera you choose to use should be compatible with libgphoto2, but that is a large list of cameras.

The first version was a proof of concept, Benjamin writes, but was far too sensitive, imprecise and had too many manual operations that could introduce user error. So now it uses machine learning to detect when a photo is correctly framed in front of the backlight using a Google Coral TPU. The whole thing is controlled by the web, and you’re even able to add metadata.

It’s a very cool project and a great use of Lego and AI. Fantastic if you’ve got a whole load of film you need to scan in and don’t want to have to do it manually!

If you want to have a go at building your own or just find out more about RoboScan, you can find the full Lego model with a complete parts list over on Mecabricks and the source code can be downloaded from GitHub.

[via Raspberry Pi]

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