81–90 of 135 posts
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If down the line this model could create 3D model from 2D images that would be very neat way to pay less for war gaming models
Already done. Cults generally has stls of 40k models before release. Its just a matter of finding them.
Neat, but I don't really see the utility. The time consuming part of CAD drawing comes from figuring out the correct dimensions of each feature, spacing, sizing, tolerances, etc., and constraining the drawing in a way so that it's easy to tweak later on- which this doesn't do at all. Maybe you could draw a 2d sketch of what you want then generate it, but you'd still have to do the hard part.
So why $work-1 spent so much time on this was quite logical. When you have point clouds generated from crappy head mounted cameras, you get models that are very complex.
for example, if you look at a point cloud of an Ikea LACK (https://www.ikea.com/gb/en/p/lack-nest-of-tables-set-of-2-wh...) It will be massively complex. this means that when you want to perform nay kind of interaction with it, its computationally difficult (https://www.researchgate.net/publication/221064696/figure/fi...)
So an active area of research is point cloud to "CAD" model (ie simplyfied, where a LACK tabl would be ~40 triangles rather than 400k)
One of those ways is to say "oh this pointcloud looks like a table, lets generate a bunch of hypothesis tables and see if they fit." One way to do that is to have a model that understands parametric CAD, and can create a number of tables with parameters that can be adjusted until it fits.
A perhaps easier way is to take a point cloud, get an image model trained on CAD models to draw models, in 2d imagery, then use something like this to get an actual model out.
Its not efficient, but it might work.
There are also lots of other cases, like automatic plagiarism, which are less good.
I wanted to see how well it performed on real pictures of parts or hand-drawn drawings, but when I tried setting up the docker image, immediately ran into all kinds of dependencies not being installed. The examples make me suspect it doesn't work well beyond images that were generated from CAD in the first place.
> docker image, immediately ran into all kinds of dependencies not being installed Ironically the former is engineered to avoid the latter.
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Gaussian splats and neural radiance fields already exist.
I dont know how that solves this. How do you get STLs out of gausian splats?
Neat, but I don't really see the utility. The time consuming part of CAD drawing comes from figuring out the correct dimensions of each feature, spacing, sizing, tolerances, etc., and constraining the drawing in a way so that it's easy to tweak later on- which this doesn't do at all. Maybe you could draw a 2d sketch of what you want then generate it, but you'd still have to do the hard part.
So I would really appreciate a good AI/LLM tool that I can feed my sketch and parameters and it can save me hours of searching web and watching tutorials on how to extrude a circle over a curve
BTW, any existing AI tools work really well with OpenSCAD, so if you want a parametrized model that can be made out of simple shapes, I highly recommend this flow
I spent a few hours trying to get this to work, and I couldn’t get it to produce usable results on anything except the training data, even with very simple drawings. I noticed in the GitHub that they mention it is only around 60% reliable even on their own training data, but the image shown on the front page feels pretty misleading. I made 10 images that were very similar in complexity to the examples shown, and even…
Neat, but I don't really see the utility. The time consuming part of CAD drawing comes from figuring out the correct dimensions of each feature, spacing, sizing, tolerances, etc., and constraining the drawing in a way so that it's easy to tweak later on- which this doesn't do at all. Maybe you could draw a 2d sketch of what you want then generate it, but you'd still have to do the hard part.
I think this is true under assumption that you know the CAD tool well. From my recent experience (I have a 3D printer), I regularly find myself in a situation where I know what I want to do, I can do measurements and I can make a sketch on a paper. Yet, making it a proper 3D model in something like FreeCAD is super tedious. I know OpenSCAD relatively well, but when it comes to something more complex I struggle a lot.…
I think this is possible, but the ‘trick’ would be translating your instructions in English into some kind of language that the CAD software understands.
I’m on a bunch of 3D printing forums, and everyone tries to describe what the finished product would LOOK like. They end up making PICTURES when what they really want is a STL file.
Two dimensions are easier to visualize then three, so let’s put it this way:
If you wanted to turn “English” into “a 2D image that’s dimensionally accurate”, you’d want to translate from “English” to “SVG.”
SVG is dimensionally accurate. JPG isn’t. The file format itself has no concept of “dimensions” only “pixels.”
Neat, but I don't really see the utility. The time consuming part of CAD drawing comes from figuring out the correct dimensions of each feature, spacing, sizing, tolerances, etc., and constraining the drawing in a way so that it's easy to tweak later on- which this doesn't do at all. Maybe you could draw a 2d sketch of what you want then generate it, but you'd still have to do the hard part.
Good question! So why $work-1 spent so much time on this was quite logical. When you have point clouds generated from crappy head mounted cameras, you get models that are very complex. for example, if you look at a point cloud of an Ikea LACK ( https://www.ikea.com/gb/en/p/lack-nest-of-tables-set-of-2-wh... ) It will be massively complex. this means that when you want to perform nay kind of interaction with it, its c…
Basically leverage the randomness to create many variations, then select the most accurate variation automatically.
Terribly wasteful of time and processing power, but so is using GPU time to make pretty pictures randomly.
