I am Petra, part of a Swiss startup specialized on 3D scanning (our app is called MAVO 3D).
MAVO 3D is built around the mission to make the whole workflow easier, which includes getting point clouds out of the scanner and into tools like Speckle.
We were very excited to see E57 import support, and went right into testing it.
However, we’re running into a huge problem with current file size limitations. Point clouds (and their meshed versions) are predestined to accumulate a lot of data very quickly to create a high-resolution 3D model.
For example, a regular 2-room apartment captures around 5GB data. Which is way beyond the size limitations in Speckle.
Now we need your help.
We would like to learn, if there is a real demand for such a point cloud to Speckle workflow.
Are you working with point clouds in Speckle?
What are your current workflows or workarounds?
If not, what’s holding you back, what would you want / need?
The 5GB file you’re trying to upload. Is this “raw” scan data that you’ve captured from a 3D scanner? or has the file been post-processed/downsampled to normalise the density of points?
Hi @Jedd
The 5GB project was more an example for a small scan. Usually the files are getting bigger, especially if users are scanning larger buildings in one session.
The data is normalized per default with our scanner. We could downsample the point density to a certain degree, but it would not solve the base issue with size limitation for bigger projects.
Speckle’s file uploads are currently limited to 1GB. We don’t currently intend on raising this limit for the general Speckle plans.
However, we do have some host app plugins that are capable of sending e57 point clouds.
Using Rhino3d with our connector should be quite capable of sending multi-gig point clouds. Our Revit connector also has some support for point clouds.
Of course, this does requires you have access to said applications.