arm_clouds's Introduction

`arm_clouds`

A simple module for convenient usage of both NumPy and PyTorch point clouds. Functionality includes:

Visualization in Plotly, Open3D, and Rerun with one function call.
Tracks and enforces consistency between XYZ and (optional) RGB PyTorch data type and device.
Methods for (un)normalization of RGB values.

Installation

To install arm_clouds, clone the repository and install with pip install -e ..

Usage

This repo includes classes for both single point clouds (PointCloud) and point cloud lists (PointCloudList).

`PointCloud` Usage

An example PointCloud:

# Your XYZ and RGB data
xyz = torch.rand(3, 100)
rgb = torch.rand(3, 100)  # optional

pc = PointCloud(xyz, rgb)

# One-call-visualization. Can also visualize in rerun and open3d.
pc.visualize_plotly()

`PointCloudList` Usage

You can initialize a PointCloudList from a NumPy array or PyTorch tensor of all point clouds:

xyz = np.random.rand(100, 3, 25)
pcl = PointCloudList(xyz)
pcl.visualize_plotly()

Or if you're dealing with point clouds with different numbers of points:

pcl = PointCloudList()

# If you haven't already created a `PointCloud` from the raw data:
for xyz, rgb in zip(xyzs, rgbs):
    pcl.append_create_cloud(xyz, rgb)

# If you already have your data in the `PointCloud` format, you can do:
for pc in point_cloud_python_list:
    pcl.append(pc)
# But if you already have multiple `PointCloud` objects in a raw Python list,
# you can directly initialize the `PointCloudList`:
pcl = PointCloudList(point_cloud_python_list)