Mano
URL: https://github.com/smarques/Mano
A simple Processing 3 sketch to detect finger distance and send OSC messages to Wekinator
This Processing sketch uses the Leap Motion sensor (https://www.leapmotion.com/) to detect the distance from each finger (thumb tip to thumb tip etc) and sends each distance via OSC to Wekinator (http://www.wekinator.org/)
This could be used to create a virtual instrument interface, that uses the two hands to control different sound parameters.
There is two versions, in respective folders
ManoClassification helps training a supervised learning system in wekinator, and allows you to set classes from your sketch.
ManoRegression is for training continous outputs.
The max folder includes a max mso patch. It currently listens to OSC on 12001 for incoming data but that's easily changed.
Possible improvements: add more features (hand palm distance), detect gestures
How to compile: You need to have processing 3 installed, with the following Processing libraries:
- Leap Motion Processing (get it at https://github.com/nok/leap-motion-processing)
- Oscp5 (get it from the Processing library manager) Then open the sketch in processing and choose File | Export Application
If this does not work for you email me at sergio.marchesini@gmail.com and I will provide a binary for your system.
How to run it: Just run the sketch or the executable for your system. When Leap Motion sees both hands the screen will show a histogram of hand distances. Anytime you see it then it means OSC data is being sent. The inputs in wekinator will be obviously 5 The parameters are named in wekinator like: thumb_delta, index_delta, middle_delta, ring_delta, pinky_delta
You might want to use wekinator input helper to smooth the data.
Wekinator, and the WekinatorProxy class are courtesy of Rebecca Fiebrink https://github.com/fiebrink1