Tutorial#
Overview#
This tutorial provides step-by-step guides for using CloudViewer.
Tutorial Structure#
Category |
Description |
|---|---|
Working with 3D geometries (Point clouds, Meshes, etc.) |
|
Interactive 3D visualization |
|
Processing pipelines (registration, integration) |
|
Complete pipeline to reconstruct a 3D scene from RGBD sequence |
|
Volumetric RGB-D reconstruction and dense RGB-D SLAM with tensor interface |
|
Sensor integration and data capture (Azure Kinect, RealSense) |
|
Advanced topics |
Getting Started#
If you’re new to CloudViewer, start here:
Installation - Install CloudViewer
Quick Start - Quick start guide
Point cloud - Your first point cloud
Visualization - Basic visualization
Complete Examples#
All tutorials include complete, runnable code examples.
Python Example:
import cloudViewer as cv3d
# Load and process
pcd = cv3d.io.read_point_cloud("bunny.pcd")
pcd_down = pcd.voxel_down_sample(0.05)
# Visualize
cv3d.visualization.draw([pcd_down], raw_mode=True)
C++ Example:
#include <cloudViewer/CloudViewer.h>
int main() {
auto pcd = cv::io::ReadPointCloud("bunny.pcd");
auto pcd_down = pcd->VoxelDownSample(0.05);
cv::visualization::DrawGeometries({pcd_down});
return 0;
}
See also
C++ documentation - C++ API Reference
Introduction - Introduction