onstrates the following:
1. The definition's functionality employing HumanUI for the custom user interface.
2. Color based segmentation in manual and auto modes.
3. The evaluation of the definition's ability to handle different point cloud data sets.
This definition performs color based segmentation in two modes.
A manual mode, that implements the Delta-E CIE 2000 color difference formula, for targeted feature detection. An auto mode, that employs a simple RGB Color Range algorithm for quicker preliminary results.
RGB to XYZ to CIELab conversion and Delta-E scripts were based on Colormine's project code from github. Results have been compared and verified with the results of http://colormine.org/color-converter and http://colormine.org/delta-e-calculator/Cie2000.
Each stored class is charted and can be accessed through the UI, as shown at 2:30, where Delta-E CIE 2000, in CieLab color space, output results were found to be in perceptive conformity with human eyes, far superior to the preliminary RGB implementation.
Initial definition versions could process highly subsampled clouds in acceptable timings. Further research showed that employing the multithread processing of Volvox components, bundling the Delta E formula with the RGB to CIE lab color conversion script, per color segmentation calculations for a one million points point cloud would go down from 23 (c# script component) and 8 (vb script component) seconds to approx. 1 second (volvox script cloud component), thus allowing the segmentation of less subsampled point clouds.
I would like to thank Heumann A. and Zwierzycki M. who provided direct support with HumanUI and Volvox. Also Grasshopper3d forum users Maher S. and Segeren P., who contributed with Rhino viewport manipulation scripts.
More on Volvox:
http://papers.cumincad.org/cgi-bin/works/Show?_id=ecaade2016_171&sort=DEFAULT&search=ecaade%20volvox&hits=2629
http://www.food4rhino.com/app/volvox
http://duraark.eu/
HumanUI:
http://www.food4rhino.com/app/human-ui?page=1&ufh=&etx=
ColorMine:
https://github.com/THEjoezack/ColorMine…
Introduzione a Grasshopper", il primo manuale su Grasshopper.
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I corsi PLUG IT nascono dalla volontà di promuovere le nuove tecnologie digitali di supporto alla progettazione e condividere il know-how maturato attraverso ricerca, collaborazione con i più importanti studi di architettura e pubblicazioni internazionali.
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Verranno introdotte le nozioni base di Grasshopper approfondendo le metodologie della progettazione parametrica e le tecniche di modellazione algoritmica per la generazione di forme complesse. Il corso è rivolto a studenti e professionisti con esperienza minima nella modellazione 3D e si articolerà in lezioni teoriche ed esercitazioni.
. Argomenti trattati:
- Introduzione alla progettazione parametrica: teoria, esempi, casi studio - Grasshopper: concetti base, logica algoritmica, interfaccia grafica - Nozioni fondamentali: componenti, connessioni, data flow
- Funzioni matematiche e logiche, serie, gestione dei dati - Analisi e definizione di curve e superfici
- Definizione di griglie e pattern complessi - Trasformazioni geometriche, paneling - Attrattori, image sampler
- Data tree: gestione di dati complessi - Digital fabrication: teoria ed esempi - Nesting: scomposizione di oggetti tridimensionali in sezioni piane per macchine CNC
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Verrà rilasciato un attestato finale.
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Ulteriori info e programma completo su: www.arturotedeschi.com e su www.edizionilepenseur.it…
ies+ Kinect Basics+ Video Effects+ DirectX 11 Rendering+ Projection Mapping on Moving Objects+ Controlling flying copters+ Brainwave analysis+ Folding & cutting paper+ Multi-touch gesture recognition+ Multiscreen Setups+ Physics based interactions+ Transformations+ vvvv and the Arduino+ Motor Control+ Industrial robots for creative applications+ Visualizing dance with Motion Bank+ IRIS – Interactive Realtime Image Synthesizer+ vvvv.js+ more online– Symposium & Exhibition –‘The Rules – Examining code as shapeable cosmoplastic material’+ Memo Akten+ Rainer Kohlberger+ Geoffrey Lillemon+ Kyle McDonald+ Julian Oliver+ Rafael Rozendaal+ Elliot Woods+ Patrizia Kommerell & Gabriel Shalom+ Philipp Kleinmichel+ Joanne McNeil+ Andrew Goffey+ Alex McLean+ more artworks from our Open Call still to be announced– Happenings –Let's meet and feel the vibes of 'Creative Coders'+ CreativeApplications.net Panel-Discussion+ Consultation hour with Memo Akten+ A/V Performance Daniel Schwarz & Edisonnoside+ LiveCoding Performance by Alex McLean+ vvvv keynote+ Visitors presentation 'Patcher Kucha'+ Consultation hour Hackerspace Frankfurt+ and final party with a Guy Called Gerald+ Geoffrey Lillemon Artist Talk & Screening+ more online–Venue –Frankfurter Kunstverein…
difference consists of.
An Evolutionary Solver/Genetic Algorithm is an implementation of Metaheuristics. Metaheuristics tend to be flexible solvers, applicable to a wide variety of problems, fairly easy to implement, but slow. Other examples of Metaheuristic algorithms would be Random Search, Scatter Search, Simulated Annealing and do on. These algorithms are often modelled on physical or biological processes.
Simulated Annealing for example simulates the physical process of annealing (who'd have thunk it), which is basically the slow cooling of a material which allows it to settle into a crystalline lattice, i.e. a low energy distribution of all the atoms. I'm currently adding an SA solver to Galapagos, and in fact just yesterday managed to get the first successful run: http://www.youtube.com/watch?v=VWtYLv-4oP0
Metaheuristics are especially useful for those cases where little is known about the problem ahead of time. If the problem search-space is mathematically well defined (differentiable, especially), then you can use more targeted algorithms such as the Newton-Raphson method, Pareto-search or Uphill search. You can still use these methods on non-differentiable search-spaces, but it involves sampling the local region to death to get an estimate of the differential. This can be a very costly enterprise, especially in high dimensional search-spaces. In a two-dimensional search-space you'll need 3 to get a lame estimate and 4 to get a halfway decent estimate and 8 to get a good estimate. In three-dimensional search space you already need 26 samples, and the number of samples grows exponentially with higher dimensions.
If you have a specific problem you're trying to solve, Metaheuristics are probably not the best solution, even though they may be easiest to program. Rhino uses something akin to Newton-Raphson for certain problems and that's fast enough to run in real-time.
Divide-and-Conquer algorithms are also quite popular. Sometimes they are called Binary-Search or Tree-Search algorithms as well. Their basic premise is to sample the search-space at a few intervals (but enough to capture the needed detail), then find two neighbours with promising values and sample again in between these two. Then repeat. Each new iteration typically doubles accuracy, which is great because then you only need ~30 ~40 iterations to get an answer as good as possible with double-precision floating point accuracy. However not all problems lend themselves well to this sort of search and in higher dimensions it starts getting slow with disconcerting alacrity.
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David Rutten
david@mcneel.com
Poprad, Slovakia…
Added by David Rutten at 1:54am on August 15, 2011
ted (in the old scheme, all inputs were always taken into account) and it's more obvious what happens to the data just by looking at an image. Also, it clears out the component menu and it's easier to add more functionality later on without creating too much confusion.
Interpolate will 'sample' the data at equally spaced intervals. Let's say you have a list of 8 fruits, as I used in my example. What happens if you interpolate this list using 4 samples? Well, the first and last sample are always centered on the first and last items in the original list. The in between samples are distributed at equidistant intervals:
So you'd end up with a list containing {Lemon, Bergamot, Mandarin, Tangerine}. If you interpolate this list using 12 equally spaced samples, it will look like this:
and it results in a list containing {Lemon, Lime, Lime, Bergamot, Grapefruit, Grapefruit, Orange, Orange, Mandarin, Rangpur, Rangpur, Tangerine}. Of course interpolating a list may result in weird sampled intervals because of the rounding of sample parameter to list indices.
Interpolation does not sample in between values. It will not return a value that is 30% Grapefruit and 70% Orange. This kind of interpolation is only possible on a subset of data types (numbers, vectors, points, colours etc.) but these components must operate on all data types. I added a specific interpolation component as well, that performs numeric sampling using 4 possible interpolation functions, but this is a wholly different kind of interpolation.
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David Rutten
david@mcneel.com
Poprad, Slovakia…
strictly with code (BTW: did you crossed Rubicon?).
1. See this: Imagine a curve (say a "rail") that is divided N times and then circles are created with random radii. Circle control points (9, that is) are sampled (obviously) into a DataTree where branches are the rail divisions. Let's call the control points: "start" seed points.
2. Imagine a capability ... that stores all these (the original "seed" control points) into a "parameter" and then each time that a change occurs to them (varying the x/y, on a per point on a per branch on a per plane basis[that provides the Z]) stores the "modified point" into the parameter (at the same index with the old: meaning "deleting" the old) ... and then some other code gets that data and makes curves and lofts them. Reset means: sample again the original "seed" points into that "parameter". Closing are reopening the definition has no effect: the lofted stuff is derived from the (internalized, so to speak) modified points (from the "parameter").
3. A variety of "automation" is available: for instance if you jump from branch to branch and from item to item the value of the selected point is inquired and the sliders that control the new x/y are "set" to 0,0 (meaning no change - yet) values. There's mo "store" mode: it works automatically as far as you modify points or you hit the reset button
4. This does that (only achievable with code):
5. Obviously points can been replaced with anything ... and thus ... we can individually modify items in collections ... and forget for ever attractor points and all that (OK where appropriate, he he).
I'll post 30 similar examples soon in the forthcoming mother of all threads: "GH goes (at last) interactive". Watch this space.
BTW: study the "animation" where points with index 6 are "sequentially" modified. I've added some delay in order to give you time to get the gist of the whole thingy.
best, Lord of Darkness
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you post a screenshot of what the message coming from its readMe! output looks like?2) Close your Grasshopper and Rhino.3) Download "Revo Uninstaller Pro" from here. It is free for first 30 days, which is what we need.4) Right click on the RevoUninProSetup.exe and check if the file is blocked. If it is, unblock it.5) Run the RevoUninProSetup.exe file and install "Revo Uninstaller Pro".6) Uninstall "MapWinGIS" with "Revo Uninstaller Pro". It is important that "Revo Uninstaller Pro" deletes not only files from MapWinGIS installation folder, but also all other leftovers (as registry inputs). Here is a small tutorial on how to do that. Watch it from 6:10 till the end.7) Restart your PC8) When your Windows boots up, make sure that you are logged in as Administrator!9) In your Start menu's search box type: "UAC", which will find your User Account Control Settings. Click on it, and a new window will open. Set the bar on the left to "Never notify".10) Turn off your Windows Firewall.11) Then turn off your custom Firewall (in case you have another one, besides standard Windows Firewall).12) Completely turn off your Antivirus.13) Download again the MapWinGIS-only-v4.9.4.2-x64.exe.exe file from here.14) Right click on the MapWinGIS-only-v4.9.4.2-x64.exe file and see if it is blocked. If it is, unblock it.15) Right click on MapWinGIS-only-v4.9.4.2-x64.exe file and choose: "Run as"... Administrator.16) One the installation preparation steps start, choose "Full installation". Wait for the MapWinGIS installation to finish.17) Right-click on "Rhino 5" icon and then choose: "Run as administrator".18) Open the the ironpython_admin.gh file again, and again post a screenshot of the message coming from its readMe! output.19) Drop the "Gismo Gismo" component to Grasshopper canvas. Post a screenshot of the message coming out from its readMe! output.
So we will need in total three screenshots of the readMe! output messages.
Thank you once again for being patient, and sorry for the large number of steps.…
Added by djordje to Gismo at 1:52am on April 9, 2017
point and tangent of this new curve to generate the direction for the next curve.
The problem I am running into is that sometimes the curve loops back on itself past the designated endpoint. The loop is so tight that you can't tell that it is actually looped and it just looks like the curve extends past its endpoint. Other times Interpolate Curve generates the arc opposite the desired one. Since I am generating a tangent to this curve at the end point it can obviously cause problems for the direction of the next curve.
I have been taking care of the problem by changing the number of points used in the curve, but am finding that even high numbers of points will generate errors and it is seriously undermining my confidence in the solution. Attached are images of the outputs with the only variable changing is the number of points used to construct the curves.
Any recommendations or insights are welcome.
30 Points (good output)
62 Points (seriously no bueno)
63 Points (um, no thanks)
199 Points (good output)
200 Points (wth?)
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For my project I want to make a sphere or spherical-like shape and pack it with circles of varying sizes. The circles all have to touch each other and thus on a point where three circles 'sort of' meet, there can only be three circles. This is shown in the second picture I have attached, a 2D circle packing made by Daniel Piker. So basically what I want to achieve is having the second picture projected on a 3d surface, that I can also edit. Also I would like to be able to change the size and amount of the circles that populate the surface. This means that I would be able to say 'there should be 30 circles with a radius of 2, 40 circles with a radius of 3 and 50 circles with a radius of 4, put them on this particular shape'.
As I've just started the project I haven't done so much research yet. What I have found is for example this Kangaroo definition of circle packing in 2D: http://www.grasshopper3d.com/group/kangaroo/forum/topics/circle-packing-definition?xg_source=activity
It is very beautiful and does exactly what I want to achieve, except that it is in two dimensions. I also have to say that I feel pretty confident working with both Grasshopper and Rhino, but not really with Kangaroo. I have used it a few times but not extensively.
So what I'm wondering is, how could I best approach this project? I looked into the concept of 'circle packing' and I noticed that it can be approached very mathematically. As I am an architecture student I don't know much about the math behind the geometry (although I do think it is very interesting) and thus I'm wondering if I will be able to achieve what I want to achieve. Also, do you think I could best approach the project in Kangaroo and do you think it is realistic for me to think I could finish the project? I'm just trying to see if I'm not going to try to tackle a problem that is very difficult to solve even for skilled mathematicans or something. Sorry for the long and perhaps vague read, but I would be very happy with any sort of input you might have on my problem!
Thanks in advance!
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