Midi Lightbox Interface/Ml-Lib

Hey there now,

I thought I’d share this. I have been working on it since I got the Organelle last month. It’s a pretty simple arduino based ldr interface but I found it really adds an expressiveness to the Organelle. In the video I’m using it with a modified version of the Quad Delay patch and the simple strings patch by msghmr. It’s in a relatively early state but it’s usable for performing (just about).

I was wondering though if anyone has tried to use these machine learning externals on the Organelle yet?


I think they could work really well with interfaces like the one in the video.

Bye,

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Wow! I have a spare Arduino board sitting around, I might give this a go! Are you running the two patches simultaneously in one new patch then?

I’m not running the two patches simultaneously, but I’m sure you could. Both patches seem pretty light on processing power.

You should totally make one. It’s really fun. Here are some tutorials:
https://www.arduino.cc/en/Tutorial/Midi
http://playground.arduino.cc/Learning/PhotoResistor

I also use the footswitch on the Organelle as a calibration tool which sets the threshold off the light, so you can use it in a number of lighting environments.

Excellent. I’ll need to pick up some photoresistors as I only have one but this looks very fun, cool for a live show.

This is cool! I’ve been wanting to play with the gesture recognition toolkit and machine learning externals.

With some fiddling I compiled the ml-lib externals for Organelle:

The documentation is a little light, do you know of any example patches to test with?

I realized sending a [help] message to any of the objects prints out useful info (attributes and methods) which is helpful. Since it is a wrapping GRT, a lot of the info here is probably useful too:

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Great. I’ll get to work trying to use them with the lightbox. I don’t know of any specific patches but I was at a talk by Ali Momeni who compiled them for Max and PureData and he had some cool patches but I can’t seem to find them anywhere. There is also a kadenze course on Machine Learning that seems pretty cool.

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