#Point set reconstruction rhino for mac how to#
#Point set reconstruction rhino for mac software#
#Point set reconstruction rhino for mac windows#

#Point set reconstruction rhino for mac windows#

I was using CloudCompare for Mac, but I also have Windows PC, so I tried it on the PC, and now I see that the FBX option is there. If I understand you correctly, there is no way to extract the texture layer as a JPEG or image file that I could project onto that STL? It looks great in Cloud Compare with the Poisson applied so clearly it's hiding in the data somewhere.

#Point set reconstruction rhino for mac software#

They do still bulge out on the back and bottom, and I haven't tried removing them with the Density scalar field, yet, but I did export the form as an STL to my 3D editing software and it opened (only 2.2 million faces, which is fine), and the bulging parts are not hard to remove there by selecting and deleting them. Then when I ran the Poisson Reconstruction, the closing triangles were on the back and bottom of the form, instead of covering the front - and the form resolved really nicely. With just that small piece, I realized that when I ran the Compute Normals that the texture projection was on the bottom instead of the top of the landscape, so I tried the invert normals function, which fixed that so the colors were on the correct side. I tried just working on a small segment of the file. You should also compute the normals before subsampling the cloud. However you'll need to compute normals first (should be easy for a landscape cloud, you should get good results with the '+Z' direction as preferred direction to orient the normals). Otherwise there's the PoissonRecon plugin (see. Otherwise, if you can live without the colors, you can indeed use the Delaunay 2.5D tool to generate a mesh easily (but it's quite sensitive to the point cloud noise). Note that the FBX or PLY formats are able to store per-vertex colors.

#Point set reconstruction rhino for mac how to#

Therefore I won't see how to achieve your goal. However CloudCompare can't convert per-vertex colors to textures.

The real issue is that OBJ files can't store per-vertex colors, and the only way to color them is to associate them to texture images. Well, before the sad news, you can indeed reduce the number of points easily with the 'Edit > Subsample' tool (either with the 'distance' or the 'random' modes - see. I don't mind slicing the file first to get smaller chunks as a first step for any of these processes (if they will work), but is there a way to slice it so I can match the chunks up precisely later? Also, since the landscape is so large, it does not have to be resolved down to a tiny measurement for my purposes, so if there is something I can do about that when I'm opening the file, let me know. I found an old article that says how to do mesh point clouds in Meshlab there but the first step, Poisson Disk Sampling, just hangs. If I don't apply the Delaunay 2.5 and export it, I can open it in Meshlab but it's just the 17M vertices and no faces, and I wasn't sure what to do next. Here's what I've tried:Īpplying the Delaunay 2.5 in CloudCompare to the unedited scan creates 34M faces which is way more than my hard drive can handle.

Is there a resource already online somewhere that I can follow? The file I am experimenting with has 17M vertices, although there are sections around the periphery I would be happy to eliminate as they are unnecessary. An OBJ file is ideal, and I'd like to keep the color information. I haven't found a direct way to do it though. las LIDAR scan of a large landscape form to a mesh that is editable in 3D editing software.

From looking around online, it looks as if CloudCompare could be used to translate a.