Pcx VS NumPy

It's a very dense point cloud from Metashape, imported into VFX graph with Keijiro's PCX - https://github.com/keijiro/Pcx

Thanks for the answer! The problem is that I don'r render the point-cloud myself, I get it already as a cloud. What 3rd party app would you recommend? Anyone of these? https://www.danielgm.net/cc/ Cloudcompare https://laspy.readthedocs.io/en/latest/index.html Laspy https://numpy.org/ https://github.com/keijiro/Pcx

Yeah I have done this with unity using this https://github.com/keijiro/Pcx .

Hi, I am not familiar with shaders (did few tutorials) and I need a disk shader for the point cloud. I used so far https://github.com/keijiro/Pcx and disk shader there is nice but doesn't work on iOS. I would like to control the disk size, and ideally it would always face a camera.

I've visualized point clouds with HL 1 in two ways ( Potree Unity and Keijiro Pcx).

Thank you! If you have a 4K camera, I would try making a video slowly walking around an area and then run it through Metashape or Meshroom. From there you can export the point cloud into Unity using this plugin: https://github.com/keijiro/Pcx

In NumPy with @, dot() or matmul():

In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication.

Data science projects often use numpy. However, numpy objects are not JSON-serializable and therefore require conversion to standard python objects in order to be saved:

numpy: A library for scientific computing in Python

Python has become a preferred language for data analysis due to its simplicity and robust library ecosystem. Among these, NumPy stands out with its efficient handling of numerical data. Let’s say you’re working with numbers for large data sets—something Python’s native data structures may find challenging. That’s where NumPy arrays come into play, making numerical computations seamless and speedy.

I was looking at all the big projects like numpy, pytorch, flask, etc.

I wish the NumPy devs would more thoroughly consider adding full fluent API support, e.g. x.sqrt().ceil(). [Issue #24081]