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I try do achieve something simple. In AppDelegate I need var vertices: [SCNVector3] = []. In @IBAction func getVertices(_ sender: Any) I can read file and assign new value to vertices. Simple and works. But when I try to pass value to SwiftUI View I have problems. If I define

I have been trying to understand pcl::CropBoX filter and that's why have been experimenting with that. However, while doing so, I came across this issue:

1. I'm creating a Point Cloud having a cube shape
2. Visualizing it
3. Cropping the original Point Cloud using pcl::CropBox filter
4. Trying to visualize cropped Point Cloud

But, in the visualizer, for step 4, I could see only a blank screen!

Here is my code, main.cpp:

I'm new to PCL (point cloud library) and I was trying to build a simple point cloud visualization code I found on their website in Visual Studio 2019. When I tried to build it, it gives me errors on the header files found in the PCL folder.

I downloaded PCL 1.6 and there are 3rd party header files included. I checked if I correctly included the necessary directories needed to build the code, nothing was missing. I'm not sure how to approach the errors since they are caused by the header files included in the PCL library. Any help would be greatly appreciated.

P.S. I'm sorry for the long code and error message. This is my first time posting a problem here.

Below is the simple point cloud visualization code I found in the PCl website:

I have two point cloud, which I want to visualise in the same window.

I have a Point Cloud Library function that detects the largest plane in a point cloud. This works great. Now I would like to extend this functionality to segment out every planar surface in the cloud and copy those points to a new cloud (for example, a scene with a sphere on the floor of a room would give me back the floor and walls, but not the sphere, as it is not planar). How can i extend the below code to get all the planes, not just the largest one? (runtime is a factor here, so i would prefer not to just run this same code in a loop, stripping out the new largest plane each time)

Thank you.

I am working on a region growing algorithm in python for unstructured point clouds. I try to implement the algorithm according to http://pointclouds.org/documentation/tutorials/region_growing_segmentation.php#region-growing-segmentation and SEGMENTATION OF POINT CLOUDS USING SMOOTHNESS CONSTRAINT.
Using the same point cloud, I fail to reproduce the results with the pcl implementation, though all the steps and the parameters seem to be the same. My implementation yields 217 regions, whereas pcl's one gets 24 (oversegemented). The point cloud can be found:

https://github.com/scrox/region-growing/blob/master/test.txt

What causes this significant difference? I also welcome performance improvements on my python code.

I am using the tutorial codes of two projects from the PCL page. One is to save a pointcloud, the other is to visualize (it's frustrating that both don't exist in a simple project, unbelievable).

This is how I save the cloud:

I am performing a region growing segmentation of a point cloud I have of my room via PCL point cloud library. The colored cloud looks like the following:

As you can see most of the clusters look according to the surface. However, when i show each cluster separatedly, these are some of the results:

Clearly the clusters are not the same as in the colored cloud, but I dont understand why. I am using this code to store the clusters into separated point clouds:

I'm new to Point Cloud library (PCL) and have limited C++ knowledge about how pointers work. While we can load a file from a file and visualize it (using this tutorial), how can we read it from a HTTP URL?