point-clouds

来源： https://stackoverflow.com/questions/46826720/pclransac-segmentation-get-all-planes-in-cloud

来源： https://stackoverflow.com/questions/46826720/pclransac-segmentation-get-all-planes-in-cloud

问题 I've a .ply format model and trying to create a .pcd file one. After checking how .pcd format should look like and writing some code to convert it to .pcd format, my results are that the model is black colored only, instead of multi-colored like the .ply format model. In the .ply format there are 7 parameters in every point line (x,y,z,r,g,b,a) and on .pcd one it should be (x y z rgb). I'm not sure how to evaluate the rgb from the .ply file. Here's some of my .ply file data: ply format ascii

问题 I've a .ply format model and trying to create a .pcd file one. After checking how .pcd format should look like and writing some code to convert it to .pcd format, my results are that the model is black colored only, instead of multi-colored like the .ply format model. In the .ply format there are 7 parameters in every point line (x,y,z,r,g,b,a) and on .pcd one it should be (x y z rgb). I'm not sure how to evaluate the rgb from the .ply file. Here's some of my .ply file data: ply format ascii

问题 I am trying to create bounding box using dimensions mentioned in the detection annotation in this dataset (I am using the polyterrasse one) for some reason the following code works for 25 frames and then suddenly it gives me an error : IndexError: invalid index to scalar variable. frame_path=glob.glob("path/to/pointcloud/folder/*.ezd") bbox_path= glob.glob("path/to/detection/annotation/folder/*.ezd.bbox") bbox=[] cbox_dim=[] for i in range(len(bbox_path)): #convert the frame into pcd format

问题 I have a 3D scan of a rock that I have represented as a point cloud using Three.js, and I wanted to more explicitly show the features of the rock, perhaps using lighting to show depths with Three. Viewing the rock from the top, I see this: When looking closely from the side, you can see rigid features that I would like to show more closely: I am unsure in how to approach this, and was hoping for some help in showing these rock features within this visualization. For context, this is my

问题 I have a 3D scan of a rock that I have represented as a point cloud using Three.js, and I wanted to more explicitly show the features of the rock, perhaps using lighting to show depths with Three. Viewing the rock from the top, I see this: When looking closely from the side, you can see rigid features that I would like to show more closely: I am unsure in how to approach this, and was hoping for some help in showing these rock features within this visualization. For context, this is my

问题 Is there a library in python or c++ that is capable of estimating normals of point clouds in a consistent way? In a consistent way I mean that the orientation of the normals is globally preserved over the surface. For example, when I use python open3d package: downpcd.estimate_normals(search_param=o3d.geometry.KDTreeSearchParamHybrid( radius=4, max_nn=300)) I get an inconsistent results, where some of the normals point inside while the rest point outside. many thanks 回答1: If you know the

问题 I am generating a point cloud representing a rock using Three.js, but am facing a problem with visualizing its structure clearly. In the second screenshot below I would like to be able to denote the topography of the rock, like the corner (shown better in the third screenshot) of the structure, in a more explicit way, as I want to be able to maneuver around the rock and select different points. I have rocks that are more sparse (harder to see structure as points very far away) and more dense

问题 Closed. This question is off-topic. It is not currently accepting answers. Want to improve this question? Update the question so it's on-topic for Stack Overflow. Closed 2 years ago . I have a .PLY file that contains a 3D Point Cloud: I want to plot it and visualize it in Python. The .PLY file contains ONLY vertex and NOT faces. Could you indicate me a simple Python library that will take care of plotting the 3D Point Cloud? It is important to remark that I am not interested in plotting a