Hello everyone,
I’m trying to efficiently tag my components by object name, with the help of grasshopper.
I found this picture of an assembly with its individual components taged and would hope to replicate it with grasshopper.
I don’t know if this was done manually, or how much was later edited by hand…
It seems very efficient in terms of tag placement in relationship with distance to component, as well as the joining of different lines under one tag. This makes it very legible overall.
I have absolutely no idea if my script is going in the right direction for this.
My results so far have started with just having normal leaders with camera orientation(updated by button).
Then i began making some sort of frame outside of which these tags would be placed.
This is essentially as far as I’ve got with it.
Here some partial results:
Script:
object_nametag.gh (41.8 KB)
model:
leader example assembly 01.3dm (1.3 MB)
I hope someone has had experience with this and could help out or comment.
All help is appreciated.
Best,
Gabriel
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Hi @gabriel.schugut,
Maybe you would like to use this AI drafting agent that I developed a while back :
If you want I can setup this agent for your usecase
farouk.serragedine@gmail.com
Seems you need exactly what I developed, It can perform all sort of actions labelling, dimensioning etc and the output is always human grade.
Farouk
farouk.serragedine@gmail.com
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Hi @gabriel.schugut
I have been thinking on this for a while now, always making some progress per project. My solution is however implemented on 2D projections, and fast and automated, as it needs to be computed for hundreds of drawings in a way that reguires minimal manual touch-ups.
Current implementation on 2D looks like this. Grouping of base points per vicinity, and creating a fan of leaders. Works 99% of the time, without intersections.
Looking at your example, the first thing that caughts my eye is the even distribution of labels along the perimeter box.
I think the process would entail projecting arrow end point to the perimeter (maybe closestPt), and then distributing/clustering to the divided border. After that it starts to get interesting, and more complex - how to group points, prohibit lines intersecting, etc… In the end it might be a “simple” list distribution exercise, where a list of info is distributed along the perimeter…
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