algorithmic modeling for Rhino
This is the support group for the Grasshopper plug-in
Crow - Artificial Neural Networks in Grasshopper.
Please post your questions / requests / remarks here
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Latest Activity: Oct 30, 2021
Hey first of all I want to thank you for this really exiting plug-in.My main Problem is that the output i get from the back-propagation solver and the resulting trained net is different than expected…Continue
Started by Tobias Heimig. Last reply by ViolaANakano Aug 3, 2021.
Hello,we are four students who want to develop a Grasshopper-based tool to support architects and urban planners in their decision making.Our idea for this is to forecast urban growth using…Continue
Started by Sebastian Clark Koth. Last reply by Tobias Heimig Jan 18, 2021.
Hi~~~~I found it is impossible to use Crow in grasshopper. the Rhino said :An error occured during GHA assembly loading:Path:…Continue
Started by JimmyLee871013 May 13, 2020.
Firstly， I thinking your plug-in is awesome~~~I saw your video and I think I should try this plug-in.
But the installation is failed. I tried different way to install the plug-in but all failed. I drug the files into grasshopper interface， there is no crow plug-in, I pasted files into component folder， there is no crow too.
I even tried rhino 5 but also failed. Maybe you can share us your rhino version and your computer information ？
Maybe can tell me what other plug-in which I need install in my computer？
SOG Component Input "Initial Nodes"
Hey there, thank you for this greate plug-in.
Do you have a short example or explanation for the "Initial Node" input at the SOG Component ?
Thank you very much !
Hey I just uploaded new files to food4rhino and github as a user pointed me a few bugs.
don't hesitate to ask questions here
Crow0.3 is out now. Find it on food4rhino or on
so Crow is based on artificial neural networks. These networks consist of logical nodes that propagate information, are structured in layers and are (de-)activated upon (not) exceeding a certain threshold. Lots of machine learning or so called AI techniques make use of this paradigm. Even Google's AlphaGo uses these techniques, though in a tremendously more advanced level than Crow can provide.
There are numerous books out there about this topic, that has been investigated for over 70 years! However, I found this one very enlightening:
It's basic introduction into the logic behind these networks and some of the most important advances in their development.
If you want to know more about the modern utilization of ANN and have some coding experience, you could look into Tensorflow, Google's Deep Learning API. Google, however, mainly makes use of these AI things for image classification and feature detection in images and videos. Not very useful for design, yet, but who knows what the future brings ;)
Hello , I feel interest on your Plugin , but how can I study the base to understand it ? Thanks
thanks a lot! Super cool that you use Crow. I actually didn't even test the Backpropagation component with the MNIST data set myself. Feel free to keep posting your results, I bet it's very helpful for others as well.
About the computation speed: I will try to parallelize the backpropagation component in the next release as I did in the SOG component (probably with a Boost option), to hopefully speed up computation a bit (5 to 40% depending on network topology). However, since the engine is written in C#, we probably won't get crazy high speed. But let's see...
Thanks for a Crow.
I have played with it today using MNIST data set.
Had some good results so far, still using small learning data set, because of the time it takes to compute.
Here are my results on intigers recognition:
Backpropagation Network settings:
3000 training cycles
3x sigmoid layer
10 neurons per layer each
learning rate of 1.0
Training set of 500 examples
During classifying 400 examples accuracy of 45%
With a bigger training set which is available I should have better result, but as a first try with NN I believe it works.
I'm posting my definition if anyone would like to take a look and give me any feedback.
Hello there fellow group members. This is to announce that Crow 0.2.1 was just released on Food4Rhino:
- Renamed n-dimensional SOMs to SOG (Self-Organizing Grid) to account for the calculation of higher dimensional Kohonen-Maps (conventional SOMs are limited to two dimensions)
- Added a Boost Options to SOG (right click on SOG engine to activate) to perform multi-core computation. WARNING: This only results in speed up, if neuron count >~1000 and SOG dimension is >2. Otherwise it might actually slow down computation
- Added a timing option to SOG to monitor time per cycle and total calculation time
- few minor bug fixes
Have fun playing with it. Don't hesitate to post questions / remarks here.
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