sndflo 0.1: Visual sound programming in SuperCollider

SuperCollider is an open source project for real-time audio synthesis and algorithmic composition.
It is split into two parts; an interpreter (sclang) implementing the SuperCollider language and the audio synthesis server (scsynth).
The server has an directed acyclic graph of nodes which it executes to produce the audio output (paper|book on internals). It is essentially a dataflow runtime, specialized for the problem domain of real-time audio processing. The client controls the server through OSC messages which manipulates this graph. Typically the client is some SuperCollider code in the sclang interpreter, but one can also use Clojure, Python or other clients. It is in many ways quite similar to the Flowhub visual IDE (a FBP protocol client) and runtimes like NoFlo, imgflo and MicroFlo.
So we decided to make SuperCollider a runtime too: sndflo.

flowhub-runtimes-withsndflo

Growing list of runtimes that Flowhub can target

We used SuperCollider for Piksels & Lines Orchestra, a audio performance system which hooked into graphics applications like GIMP, Inkscape, MyPaint, Scribus – and sonified the users actions in the application. A lot of time was spent wrestling with SuperCollider, due to the number of new concepts and myriad of ways to do things, and
lack of (well documented) best practices.
There is also a tendency to favor very short, expressive constructs (often opaque). An extreme example, here is an album of SuperCollider pieces composed with <140 characters (+ an analysis of some of them).

On the contrary sndflo is very focused and opinionated. It exposes Synths as components, which are be wired together using Busses (edges in the graph), allowing to build audio effect pipelines. There are several known issues and limitations, but it has now reached a minimally useful state. Creating Synths components (the individual effects) as a visual graph of UGen (primitives like Sin,Cos,Min,Max,LowPass) components is also within scope and planned for next release.

Simple substrative audio synthesis using sawwave and low-pass filter

Simple substrative audio synthesis using sawwave and low-pass filter

The sndflo runtime is itself written in SuperCollider, as an extension. This is to make it easier for those familiar with SuperCollider to understand the code, and to facilitate integration with existing SuperCollider code and tools. For instance setting up a audio pipeline visually using Flowhub+sndflo, then using the Event/Pattern/Stream system in SuperCollider to create an algorithmic composition that drives this pipeline.
Because a web browser cannot talk OSC (UDP/TCP) and SuperCollider does not talk WebSocket a node.js wrapper converts messages on the FBP protocol between JSON over WebSocket to JSON over OSC.

sndflo also implements the remote runtime part of the FBP protocol, which allows seamless interconnection between runtimes. One can export ports in one runtime, and then use it as a component in another runtime, communicating over one of the supported transports (typically JSON over WebSocket).

YouTube demo video

In above example sndflo runs on a Raspberry Pi, and is then used as a component in a NoFlo browser runtime to providing a web interface, both programmed with Flowhub. We could in the same way wire up another FBP runtime, for instance use MicroFlo on Arduino to integrate some physical sensors into the system.
Pretty handy for embedded systems, interactive art installations, internet-of-things or other heterogenous systems.

imgflo 0.2, The Grid launched

When I announced the first release of the imgflo project in April, it was perhaps difficult to see what exactly it was useful for and why we are developing it. This has changed now as 3 weeks ago we launched The Grid, our AI-based web publishing platform. We are on a bold mission to have “websites build themselves”; because until posting to personal websites becomes easier and more rewarding than posting to social media, content on the web will continue to pile up in closed silos.

thegrid-5k-join

To help solve this problem we built several open source technologies:

NoFlo: for creating highly testable, component-based, distributed software.
Flowhub: for visually and interactively building programs and extensions.
GSS: for building constraint-based, responsive layouts
And of course imgflo: for on-demand server-side image processing.

In total over 100k lines of code, and around 5000 commits over the last 12 months. Some of the stack is expained in more detail in a recent interview with Libre Graphics World.

imgflo on The Grid

thegrid.io launch site is of course built with The Grid. In the particular layout filter used, the look & feel is driven largely by the content. Colors for text captions are extracted from tweets and social media posts, and the featured images are largely unfiltered. Other Grid layout filters may style all provided content, including images, towards a uniform look specified by a color scheme. Or a layout filter may mix-and-match content- versus style-driven design.

The background texture on this section was created with imgflo, by passing the featured image through a blur graph:

thegridio-imgflo-bg-texture
https://imgflo.herokuapp.com/graph/vahj1ThiexotieMo/1ff47cef6f354fe0fbdefb…Fimages%2Fgrid-chrome.jpg&width=1300&height=768&std-dev-x=25&std-dev-y=25

It is important to note that no-one chose this exact image to be used in the particular layout section (and thus have the given image filter applied), which is why processing happens on-demand. The layout section with image inside a computer screen is available for content which has images of type “screenshot”. This property may be automatically detected by our image analytics pipeline, or manually annotated by user. The system allows describing many other such constraints, which are all taken into account when it works to create the appropriate layout for given content.

Even without considering styling, imgflo has a couple of important roles on a Grid site. Important is the ability create multiple scaled down versions to optimize download size. For this we also created a helper library called RIG, which is used to generate a set of CSS media-queries with imgflo request urls.


> rig = require 'rig-up'
> css = rig content, serverconfig, 'passthrough', parameters, ... 
 # passthrough is name of the graph to process through
 
@media (max-width: 503px) {
  .media, .background {
    background-image: url('https://imgflo.herokuapp.com/graph/apikey/6bb56129dc707894baa88d10a02a12b9/passthrough?input=https%3A%2F%2Fa.com%2Fb.png&width=400&height=225');
  }
}
@media (min-width: 504px) and (max-width: 1007px) {
  .media, .background {
    background-image: url('https://imgflo.herokuapp.com/graph/apikey/d099f7222293d335a6192d742f523bfa/passthrough?input=https%3A%2F%2Fa.com%2Fb.png&width=800&height=450');
  }
}

Processing images through imgflo also means that they are cached. So if the original image becomes unavailable, the website still has versions it can use. This can happen for instance on Twitter when people change their profile picture.
Note that while we optimize images when presented on site, we don’t touch the original image (non-destructive). This means image uploaded to The Grid has the full data & metadata preserved, unlike on some other social/web services. However, we are currently not preserving metadata in processed images.

 

imgflo 0.2

imgflo is now split into three repositories, the GEGL-based Flowhub runtime, the HTTP API server and the native dependencies. The runtime itself is plain C with glib, and could be used in non-web applications for desktop, mobile or embedded.

A major feature is that processing requests can now be authenticated, so that non-legitimate users cannot disrupt legitimate ones by overloading the server. We also use Amazon S3 for caching processed images, offloading a large portion of the work. Servicing 10k++ visits a day with a 2-dyno Heroko app has been no problem with this setup.

In imgflo-server we’ve also added support for using different processors than imgflo (which uses GEGL), in particular NoFlo with noflo-canvas. One can now build and deploy image processing pipelines using JavaScript, including all the libraries that work with the <canvas> element.

Building NoFlo image processing graph in Flowhub, then requesting from imgflo-server

Building NoFlo image processing graph in Flowhub, then requesting from imgflo-server

Full details about the changes can be found in the changelogs: server, runtime.

Scale

Flowhub provides imgflo a node-based visual & interactive IDE for developing new image filters for The Grid. It is similar to etablished tools like FilterForge, the Blender compositor,  vvvv and nuke – which many designers and visual artists are familiar with. However there are still many snags in the workflow for non-technical people. Smoothing out these is major part of the next imgflo milestone.
After that the focus will be on horizontal scalability, to handle the load as The Grid enters beta and opens to founding members in spring.

MicroFlo 0.3 & Flowhub Beta

Its been nearly 6 months since the previous release of MicroFlo, which was the first that allowed you to visually program your Arduino using NoFlo UI. While we are still just getting started, lots of things have changed since then.

Flowhub

Flowhub is the name of the officially supported, packaged and hosted version of the open source NoFlo UI. This is the IDE used for programming with MicroFlo, and a lot of work has been put into it the last couple of months. Today we released the beta version.

You can test it out for browser, node.js and microcontrollers now.

Other runtimes are in development, and you can add your own by implementing the FBP runtime protocol. For instance there are runtimes for desktop development for GNOME, image processing using GEGL, audio synthesis using SuperCollider and for Python.

Heterogenous FBP

Lightbulb idea: two microcontrollers programmed with MicroFlo used as components in a NoFlo program

Often microcontrollers act as sensors and actuators in a larger system, where embedded computers, mobile devices and servers are used to provide the data storage and processing as well as user interfaces and connectivity with other systems.

With MicroFlo 0.3 one can visually create a microcontroller program, and then export ports on this program to make the entire microcontroller available as a component in NoFlo on node.js. This allows to seamlessly create programs which combine microcontrollers and embedded computers.
We made use of this functionality when we created an interactive table that shows the status of the Ingress virtual reality game.

Platform support

Lunchbox electronics: Some boards that can run MicroFlo

MicroFlo has worked on AVR-based Arduinos from day 1, but it was always the goal to not be specific to Arduino. Therefore I’m happy to say that there are now basic platform implementations for:

  • AVR-based Arduino and derivatives
  • Atmel AVR8 (without using Arduino)
  • mbed LPC1768 (ARM Cortex M3)
  • Texas Instruments Tiva-C (ARM Cortex M4)
  • Embedded Linux (RPi, BeagleBone Black)

Basic bring-up up of new platform can be done in a couple of days, and components which do not use platform-dependent libraries can be used immediately. The goal is to be portable enough that you can pick up whatever capable device you find in your parts-bin, prototype your initial code there – then move the program over to a more ideal device if/when appropriate.
If you have particular platforms you’d like to see supported, leave a note.

Simulation & Automated testing

Automated testing in the embedded world using C/C++ is very painful compared to that of recent web technologies. CoffeScript (or JavaScript) in combination with a modern BDD framework like Mocha makes for simple and beautiful tests.

These tests are ran in a simulator which implements the MicroFlo I/O backend (C++) in JavaScript using a Node.js addon. Unfortunately there are not many good open source instruction-level simulators for the platforms MicroFlo support, so the platform backends can only be tested once we support on-device testing.

Automated testing is a critical piece to making sure that MicroFlo is not only a fun and rewarding way to create microcontroller programs, but also an excellent way to make industrial quality devices.

Easier to get started

A Chrome app is slightly less intimidating for users than a terminal

MicroFlo now ships a Chrome app, used to let Flowhub communicate with the MicroFlo runtime running on device over serial/USB/Bluetooth. This means  it is no longer neccesary to run node.js in a terminal, removing a usability issue in getting started.

In the future, this functionality will be baked into the Flowhub Chrome app itself. With time component code editing, building the firmware and flashing the device will also be available there, making Flowhub a true integrated development environment for MicroFlo.

 

 

 

imgflo 0.1: An image processing server and Flowhub runtime

At TheGrid we are in need for a flexible service for doing server-side image processing. So after some discussion at LGM in Leipzig, I started writing one based on GEGL, the image processing library that will power the upcoming GIMP 2.10 release. The library provides a demand-driven graph-based API , with a ton of operations included and support for GPU processing using OpenCL.

Runtime

For creating image processing pipelines for the server, imgflo acts as a runtime for Flowhub, our open source visual programming IDE. It adds to the existing NoFlo browser, Node.js and MicroFlo microcontroller runtime targets, all possible thanks to the runtime-agnostic protocol.

The preview is live and changes whenever changes are made to the graph. This allows to quickly experiment and develop new graphs.

Server

As a server, imgflo provides a simple HTTP API where you specify the input image as an URL, the graph to process it through and any parameters exposed on that graph.

Requests being made to the imgflo server HTTP API on demo page

Processed images are cached, so that subsequent request on the same url just returns the image out of the cache.
The git repository includes configuration and build setup for Heroku, so deploying an instance is a 5 minute job.

Next

imgflo 0.1 is now minimally useful as image processing server, but there are many more enhancements on the todo list. Scalability and integration with NoFlo are two big topics, as as expanding the pool of available operations and graphs. Porting filters from GIMP to GEGL is a way of helping with the latter.

Additionally it would be interesting to provide a way of using imgflo with GIMP. First of all one could use graphs made with Flowhub via GEGL meta-operations. A more crazy idea is to integrate directly,  using Flowhub as a companion node-based editor.

 

 

Going to Libre Graphics Meeting 2014

LGM2014 will happen April 2-5th in Leipzig, Germany and this will be my fifth year attending. In fact LGM 2010 in Brussels was my first international conference ever, and convinced me that I wanted to make open source professionally.

I’m very excited about this years program, because once again we have managed to combine bleeding edge developments in open source software for graphics and visuals, with a wide range of connecting fields: open hardware, design, art activism, free cultural works, research and education.

Personally, I especially look forward to:

  • Richard Hughes: Building an OpenHardware Spectrograph for Color Profiling in Linux
  • Johannes Hanika: Wavelets for image processing
  • Manuel Quiñones: GEGL is not GIMP – creating graphic applications with GEGL (workshop)
  • Libre Graphics Magazine: Beating the drums, Why we made gender an issue

I am also hosting a BoF session on visual programming of libre graphics tools. Curious to see what comes out of that.

If you are interested in open source and graphics, don’t miss Libre Graphics Meeting.
Register now (it’s free and open for all)!

Can’t go to LGM, but would still like to contribute? Please consider donating to our travel fund.

I would like to thank the GIMP project for sponsoring my trip to LGM2014.

MicroFlo 0.2.0, visual Arduino programming

Two months after MicroFlo 0.1.0, another important milestone has been reached. This release brings a basic visual programming environment and initial support for all major desktop platforms (Win/OSX/Linux). The project is still very much experimental, but it is now starting to demonstrate potential advantages over traditional Arduino programming.

Official release notes and announcement here.

The start of something visual

The “Hello World” adopted from Arduino, a program that blinks the built-in LED a couple of times per second. Pressing Play (>) uploads the program to the Arduino using MicroFlo.

The IDE shown is NoFlo UI, a visual programming environment which can also be used to program JavaScript for the browser and Node.js using the NoFlo runtime. This project is developed by Henri Bergius and rest of the NoFlo team. For more details about the NoFlo IDE project, check their latest update and follow their Kickstarter project.

Talk

At Piksel 2013 in Bergen, I also presented MicroFlo for the first time, to an audience of mostly new media and experimental sound artists. The talk goes into detail about the motivations behind the project, from the quite practical to the more philosophical considerations. Not my most coherent talk, but it gives some insight.

Link

Next

For the next milestone, MicroFlo 0.3, several things are already planned. Focus is mostly on practical improvements to the system, but I also hope to complete prototype support for “heterogeneous FBP”: Allowing to program systems consisting of both host computer and microcontroller programs in a unified manner using NoFlo+MicroFlo.

I am also planning a MicroFlo workshop at Bitraf some time in December and to demo the project at Maker Faire Oslo.

In the meantime, you can get started with MicroFlo for Arduino by following this tutorial. Feedback and contributions welcomed!

MicroFlo 0.1.0, and an Arduino powered fridge

Lately I’ve been playing with microcontrollers again; Atmel AVRs with and without Arduino boards. I’ve make a couple of tiny projects myself, helped an artist friend do interactive works and helped to integrated a microcontroller it in an embedded product at work. With Arduino, one does not have to worry about interrupts, registers and custom hardware programmers to get things done using a microcontroller. This has opened the door for many more people that pre-Arduino. But the Arduino language is just a collection of C++ classes and functions, users are still left with telling the microcontroller how to do things; “first do this, then this, then this…”.

I think always having to work on such a a low level limits what people make with Arduino, both in who’s able to use it and what current users are able to achive. So, I created a new experimental project: MicroFlo. It has a couple of goals, the two first being the most important:

People should not need to understand text-based, C style programming to be able to program microcontrollers. But those that do know it should be able to use that knowledge, and be able to mix-and-match it with higher-level paradims within a single program.

It should be possible to verify correctness of a microcontroller program in an automated way, and ideally in a hardware-independent manner.

Inspired by NoFlo, and designed for integration with it, MicroFlo implements Flow-based programming (FBP). In FBP, a program is constructed by connecting a set of independent components. Each component has in-ports and out-ports, and can only communicate with eachother through these. The connections can be defined using programatically, using a declarative text language,  or using a visual editor. 2D/3D artists will recognise this the concept from node compositors like in Blender, sound artists from applications like Reaktor.

Current status: A fridge

I have an old used fridge, by the looks of it made in the GDR some time before I was born. Not long after I got it, the thermostat broke and the cooler would not turn off. Instead of throwing it away and getting a new one, which would be the cool and practical* thing to do, I decided to fix it. Using an Arduino and MicroFlo.
* especially considering that it is several months since it broke…

A fridge is a simple system, something that should be simple for hobbyists to create. So it was a decent first usecase to test the framework on. Principially, such a system looks something like this:

 

The thermostat decides whether to turn the cooler on or off, and the cooler switch realizes this decision. There are many alternative methods of implemening each of these two components. I used a DS1820 digital thermometer IC to read temperature, and a hacked NEXA remote controlled relay for the switch.
All the logic, including temperature threshold is done in software on an Arduino Uno.

The code below for the cooler switch would have been simpler (a oneliner, left as excersise for the reader) if I instead had used a active high relay directly on the mains (illegal if not a certified electrician). Or alternatively reverse-engineered the 433Mhz protocol used.

 

MicroFlo code for the fridge, in the .FBP domain specific language (examples/fridge.fbp)
# Thermostat
timer(Timer) OUT -> TRIGGER thermometer(ReadDallasTemperature)
thermometer() OUT -> IN hysteresis(HysteresisLatch)

# On/Off switch
hysteresis() OUT -> IN switch(BreakBeforeMake)
switch() OUT1 -> IN ia(InvertBoolean) OUT -> IN turnOn(DigitalWrite)
switch() OUT2 -> IN ic(InvertBoolean) OUT -> IN turnOff(DigitalWrite)
# Feedback cycle to switch required for syncronizing break-before-make logic
turnOn() OUT -> IN ib(InvertBoolean) OUT -> MONITOR1 switch()
turnOff() OUT -> IN id(InvertBoolean) OUT -> MONITOR2 switch()

# Config
‘5000’ -> INTERVAL timer() # milliseconds
‘2’ -> LOWTHRESHOLD hysteresis() # Celcius
‘5’ -> HIGHTHRESHOLD hysteresis() # Celcius
‘[“0x28”, “0xAF”, “0x1C”, “0xB2”, “0x04”, “0x00”, “0x00”, “0x33”]’ -> ADDRESS thermometer()
board(ArduinoUno) PIN9 -> PIN thermometer()
board() PIN12 -> PIN turnOff()
board() PIN11 -> PIN turnOn()

Is the above solution nicer than using the Arduino IDE and writing in C++? At the moment maybe not significantly so. But it does prove that this kind of high-level dynamic programming model is feasible to implement also on devices with 2kB RAM and 32kB program memory. And it is a starting point for more interesting exploration.

Next steps

I will continue to experiment with using MicroFlo for new projects, to develop more components and test/validate the architecture and programming model. I also need to read through all of the canonical book on FBP by J. Paul Morrison.

Some bigger things that I want to add include:

  • Ability to introspect the graph running on the device, in particular the packets moving between components.
  • Automated testing (of the framework, individual components and application graphs)  using  JavaScript BDD test frameworks like Mocha or Vows.
  • Ability to change graphs at runtime,  and then persist it to EEPROM so it will be loaded on next reset.

And eventually: Allowing to manipulate and monitor running graphs visually, using the NoFlo development environment. See bug #1.

Curious still? Check out the code, and ask on the FBP mailing list if you have any questions!

Libre Graphics Meeting 2013: We want you

Are you interested in the overlap between technology, art and design; and free, open, libre tools that join these domain? Do you use Libre Graphics software like GIMP, Blender, Krita, Inkscape, Scribus, MyPaint (and similar), and want to meet the people behind them?
Are you a developer of free and open source software in the areas of photography, graphics, page layout, design, publishing, typography, animation or video?

Come to the 8th annual Libre Graphics Meeting, from Wednesday 10th to Saturday 13th April in Madrid, Spain!

Registration is open (no attendance fee, sponsorship possible), and presentation & workshop proposals are accepted until 15th of February (2 weeks from today!).

Improved drawing performance in MyPaint brush engine

A first set of performance improvements for the brush engine has just landed in MyPaint master. The goals for this work for me were, in priority: a) Making sure that moving to a GEGL backend in MyPaint does not reduce performance, b) Improve performance when integrating the MyPaint brush engine in other applications, and lastly c) Improving the performance in MyPaint itself.

TL;DR: * Users of the soon-to-be-released MyPaint 1.1 should experience about 15% faster drawing of strokes for medium to big brushes. * Switching to the GEGL based backed for MyPaint 1.2 is now both feasible and highly desirable from a performance perspective.


Optimizations

The optimizations are implemented through three complimentary strategies:

1. Deferred data access to minimize fetching and updating of tiles

All dab drawing operations that happen as a result of a motion update event are queued up. When the brush engine has calculated where all dabs should go, tiles are fetched, all dabs drawn and the tiles updated. This in contrast to before where each dab drawing operation would fetch and update tiles.

2. Coarse grained parallelism using multi-threading via OpenMP directives

The tiles to be processed are divided evenly between processing threads (one per core). Each tile is processed completely independent of other tiles, so there is no locking or synchronization in the drawing code. The tile backing store must naturally be thread-safe and may ensure this using locks.

3. Fine grained parallelism using SSE via GCC auto-vectorization

Within each tile we attempt to make use of auto-vectorization to create the brush dab mask and do the composition of the dab onto the tile. Currently this is only implemented for a part of the mask calculation.

Results

Details of the results and how they can be reproduced is found in the original email thread.

Gains for MyPaint 1.1

Starting with the lowest priority goal, but the most relevant to users; performance impact on MyPaint right now.

Surface drawing results for existing Python-based backend

In terms of raw speed of drawing brushes to onto the underlying surface, speedups range from 20% to 50% for larger brushes (16 px+). This sets an upper boundary for the speedup perceived by the user.

Looking at the UI-enabled benchmarks of MyPaint, which is doing everything a normal application instance does, including layer compositing and rendering to screen, around 15% speedup was observed.  As the UI benchmark only tests a single brush at size=8.0px, it is possible that larger brushes will a higher speedup.

Users of the soon-to-be-released MyPaint 1.1 should experience about 15% faster drawing of strokes for medium to big brushes.

Note that the backend in use does not make use of the multi-threading introduced by (2) due to the tile store not being thread-safe and that it already had a cache to mitigate the problem fixed by (1).
Note

GEGL-based backend results, outlook for MyPaint 1.2

Surface drawing results, GEGL versus Python-based surface.
Test results by Till Hartmann on his Phenom II X6.

So in terms of raw surface rendering speed, the GEGL based backend is now significantly faster than the Python-based one. With 1 and 2 threads it is respectively up to 25% and 100% faster for big brush sizes. With 6 threads, it can be up to 4 times faster.

Switching to the GEGL based backed for MyPaint 1.2 is now both feasible and highly desirable from a performance perspective.

Note that to see UI performance increases approaching the raw surface drawing performance increase we may also need to do the layer compositing multi-threaded.

Gains in other applications

I’m trying to convince the Krita guys to update to the new version and to provide some feedback on the impact. Other consumers of the MyPaint brush engine do not tend to communicate much with us (some are proprietary).
I have strong hopes that (1) should increase their performance radically as their tile get/set cost is significantly higher than in the MyPaint case: They need to convert between the internal Krita and the MyPaint brush engine working colorspace each time. They may also be able to enable multi-threading and see speedups similar to the GEGL-based backend as a result.

Future Work

This is only lays the groundwork of better optimized MyPaint brush engine, many areas have room for improvement. For one only a small subset of the heavy code is vectorized. There may be inner loops that can be tweaked. It may be that, with a different tile access pattern compared to before, a different tile size would be more ideal. Perhaps doing the expensive calculation of the brush dab could be avoided some times by caching them… Thinking bigger, one could move all the drawing (and rendering) to the GPU.

More details on these ideas can be found here. If you are interested in working on any of it, get in touch and start hacking!

Participating in Libre Graphics Research Unit residency

Following the Piksels & Lines research meeting in June and being accepted in the call for proposals I am now taking part in the Piksel & Lines Orchestra residency, hosted by Piksel and LGRU, together with media artist and engineer Brendan Howell. Together we will further develop the Piksels & Lines Orchestra, a system that turns the traditional libre graphics tools (like MyPaint, GIMP, Inkscape, Scribus) into instruments for use in an performance setting.

A prototype of this system is to be demonstrated at Piksel X in Bergen, November 21-25th. Piksel is an annual festival where artists and developers working with free and open source software, hardware and art come together. Its diverse program will include presentations, workshops, performances, and installations.

Within the Piksels & Lines Orchestra residency we will also realize an artwork that will be performed in Madrid, April at the Future Tools Conference. This event combines Libre Graphics Meeting, an annual artist and developer meeting around free and open source graphics software with Interactivos?’13, two weeks of project-centric workshops focused on collaborative creation using open hardware and open software. The call for projects is now open, focusing on “Tools for a Read-Write World”.

Don’t miss any of these events if you are interested in the intersection and interaction between artistic works and open tools!

from more than a dozen countries