#Data-driven #GenerativeDesgin #C# #Grasshopper #DataVisualization
Generative Structure
; generating building and plant structure
Office for Urbanization + Certain Measures | 2019
Supervisors: Charles Waldheim, Andrew Witt
Role: Machine Training, Data Visualization
Tools: Rhino, Grasshopper(C#), pix2pix
Publication: 50 New Town (in progress)
This work presents collaborative design research examining Chinese agrarian village block typologies,
augmented through computational processes and artificial intelligence (AI) classifications.
# Building Structure: How it works
For 18 building typology, from 18 different 10km x 10km region
![](https://freight.cargo.site/t/original/i/18d17e2e40c12751c0f2fd767f7c29268a2cd65a21543619b613e92143665cc1/Portfolio_SCL7.jpg)
- We trained the model to detect certain typologies using pix2pix.
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We got the extracted boundaries of detected buildings matched with the trained typology.
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We generated about 100 deep structures associated with each typology for training use.
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We trained another model with the generated deep structure.
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We got the generated deep structure from the extracted boundaries (from the 2nd process).
# Building Structure: Visualization
The generated deep structure elements were arranged according to their orientation and size.
![](https://freight.cargo.site/t/original/i/6b82a1d60b12ccbb4fa75bb1f74ba7b6ebcb8b6fcb18a4488b56721495f67f77/Portfolio_SCL5.jpg)
# Plant Structure: How it works
The growth pattern became their language, and we interpreted 50 new towns with this logic. 3d tree models were generated based on their specific growth pattern.
With C# in Grasshopper, I built a 3D tree model generator that takes a few variables for the leaf shape and their attached pattern.
![](https://freight.cargo.site/t/original/i/c0109a5abc4aaa411a738504d22a2f69f7bc44e11ebe0464a188758e5e7ae49b/Portfolio_SCL10.jpg)
![](https://freight.cargo.site/t/original/i/f427985971ac467c9f64689bf0650022f2fd027d5c6de51a546ad74852070bf1/gh.jpg)
![](https://freight.cargo.site/t/original/i/6e9997ee7a0240df44e35eeb86136677abd1a9302f9a1b24aa0b806bcd79ef14/190628_signature-01.png)
![](https://freight.cargo.site/t/original/i/8788b234228fc0696b6b6bcff17d51e750e2b8585611dd12904f224770a844e2/190628_signature-02.png)
![](https://freight.cargo.site/t/original/i/f72a59432875ead35f5fab85b871f7372e0f4974bc6a20480268056002f87dab/190628_signature-03.png)
![](https://freight.cargo.site/t/original/i/58d7df79e766b419af89b7965795b57d79691965be896a951336b87d933a094b/190628_signature-04.png)
# Plant Structure: 3d models
![](https://freight.cargo.site/t/original/i/1fb50b473f8f1a51d4df1f6c8d77f2316f98774566c8f0a6d7c03575b82f84a7/Portfolio_SCL9.jpg)
![](https://freight.cargo.site/t/original/i/e7077f499dd4e8c5ac85d639e21ba2c453a4af859c1f18ff2ba9861b9d6fd67f/Portfolio_SCL11.jpg)