CloudAnalyzer CLI
FreeStreamline point cloud quality assessment and processing.
Free · Opens the source repo
What CloudAnalyzer CLI does
The CloudAnalyzer CLI skill provides a command-line interface specifically designed for interacting with the CloudAnalyzer platform. This tool is tailored for developers and researchers working with point cloud data, offering a comprehensive set of commands that facilitate various quality assurance tasks. With 27 commands organized into 8 functional groups, users can efficiently evaluate, process, and visualize point cloud outputs, enhancing their workflow in mapping, localization, and perception tasks.
Users can perform point cloud evaluations using metrics like Chamfer distance and F1 scores, compare multiple point clouds, and execute batch evaluations to streamline their analysis. The skill also supports trajectory evaluations, allowing users to assess estimated versus reference trajectories with a range of options to customize their evaluations. Furthermore, the config-driven quality gates enable users to automate their QA processes based on predefined criteria, making it easier to maintain high standards in their projects.
In addition to evaluation capabilities, the CloudAnalyzer CLI skill includes commands for point cloud processing, such as downsampling, filtering, and format conversion. This versatility makes it a valuable tool for developers looking to manipulate point cloud data efficiently. The visualization commands also allow users to inspect point clouds interactively or export inspection results for further analysis. Overall, this skill is ideal for those involved in projects that require rigorous point cloud quality assessment and manipulation.
When to use it
Use this skill when you need to perform quality assurance on point cloud data or manage trajectory evaluations in your projects.
When not to use it
This skill may not be suitable for users who require a graphical user interface or those who do not work with point cloud data.
What you can build with it
Quality Assurance for Mapping Projects
Use the CloudAnalyzer CLI to evaluate point clouds generated from mapping applications, ensuring high accuracy and quality.
Batch Evaluating Trajectories
Run batch evaluations of multiple trajectory files to assess their accuracy against reference data, streamlining your analysis.
Processing Point Clouds for Machine Learning
Prepare point clouds for machine learning applications by downsampling and filtering data using the CLI commands.
How to install CloudAnalyzer CLI
View source1. Install with the skills CLI
npx skills add hkuds/cli-anything/skills --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by hkudscli-anything-cloudanalyzer
Agent-friendly command-line harness for CloudAnalyzer — a QA platform for mapping, localization, and perception point cloud outputs.
27 commands across 8 groups.
Installation
pip install cli-anything-cloudanalyzer
Prerequisites:
- Python 3.10+
- CloudAnalyzer:
pip install cloudanalyzer
Global Options
cli-anything-cloudanalyzer [--project FILE] [--json] COMMAND [ARGS]...
| Option | Description |
|---|---|
-p, --project TEXT | Path to project JSON file |
--json | Output results as JSON (for agent consumption) |
Command Groups
1. evaluate — Point Cloud Evaluation (6 commands)
evaluate run
Evaluate a point cloud against a reference (Chamfer, F1, AUC, Hausdorff).
cli-anything-cloudanalyzer evaluate run source.pcd reference.pcd
cli-anything-cloudanalyzer --json evaluate run source.pcd reference.pcd
Options: --plot TEXT, --threshold FLOAT
evaluate compare
Compare two point clouds with optional registration.
cli-anything-cloudanalyzer evaluate compare src.pcd tgt.pcd --register gicp
Options: --register TEXT (icp/gicp/none)
evaluate diff
Quick distance statistics between two point clouds.
cli-anything-cloudanalyzer evaluate diff a.pcd b.pcd --threshold 0.1
evaluate batch
Batch evaluation of multiple point clouds against a reference.
cli-anything-cloudanalyzer --json evaluate batch results/ reference.pcd --min-auc 0.95
Options: --min-auc FLOAT, --max-chamfer FLOAT
evaluate ground
Evaluate ground segmentation quality (precision, recall, F1, IoU).
cli-anything-cloudanalyzer --json evaluate ground est_ground.pcd est_ng.pcd ref_ground.pcd ref_ng.pcd --min-f1 0.9
Options: --voxel-size FLOAT, --min-precision FLOAT, --min-recall FLOAT, --min-f1 FLOAT, --min-iou FLOAT
evaluate pipeline
Filter, downsample, evaluate in one command.
cli-anything-cloudanalyzer evaluate pipeline input.pcd reference.pcd -o output.pcd
2. trajectory — Trajectory Evaluation (3 commands)
trajectory evaluate
Evaluate estimated vs reference trajectory (ATE, RPE, drift, lateral, longitudinal).
cli-anything-cloudanalyzer --json trajectory evaluate est.csv gt.csv --max-ate 0.5 --max-lateral 0.3
Options: --max-ate FLOAT, --max-rpe FLOAT, --max-drift FLOAT, --min-coverage FLOAT, --max-lateral FLOAT, --max-longitudinal FLOAT, --align-origin, --align-rigid
trajectory batch
Batch trajectory evaluation.
cli-anything-cloudanalyzer trajectory batch runs/ --reference-dir gt/ --max-drift 1.0
trajectory run-evaluate
Integrated map + trajectory evaluation.
cli-anything-cloudanalyzer trajectory run-evaluate map.pcd map_ref.pcd traj.csv traj_ref.csv
Options: --min-auc FLOAT, --max-ate FLOAT
3. check — Config-Driven Quality Gate (2 commands)
check run
Run unified QA from a config file.
cli-anything-cloudanalyzer --json check run cloudanalyzer.yaml
Options: --output-json TEXT
check init
Generate a starter config file.
cli-anything-cloudanalyzer check init cloudanalyzer.yaml --profile integrated
Options: --profile TEXT (mapping/localization/perception/integrated), --force
4. baseline — Baseline Evolution (3 commands)
baseline decision
Decide whether to promote, keep, or reject a candidate baseline.
cli-anything-cloudanalyzer --json baseline decision qa/summary.json --history-dir qa/history/
Options: --history TEXT (repeatable), --history-dir TEXT, --output-json TEXT
baseline save
Save a QA summary to the history directory.
cli-anything-cloudanalyzer baseline save qa/summary.json --history-dir qa/history/ --keep 10
Options: --history-dir TEXT, --label TEXT, --keep INTEGER
baseline list
List saved baselines.
cli-anything-cloudanalyzer --json baseline list --history-dir qa/history/
5. process — Point Cloud Processing (6 commands)
process downsample
Voxel grid downsampling.
cli-anything-cloudanalyzer process downsample cloud.pcd -o down.pcd -v 0.05
process sample
Random point sampling.
cli-anything-cloudanalyzer process sample cloud.pcd -o sampled.pcd -n 10000
process filter
Statistical outlier removal.
cli-anything-cloudanalyzer process filter cloud.pcd -o filtered.pcd
process split
Split point cloud into grid tiles (writes metadata.yaml).
cli-anything-cloudanalyzer process split large.pcd -o tiles/ -g 100
process merge
Merge multiple point clouds.
cli-anything-cloudanalyzer process merge a.pcd b.pcd -o merged.pcd
process convert
Convert between point cloud formats.
cli-anything-cloudanalyzer process convert input.las -o output.pcd
6. inspect — Visualization (3 commands)
inspect view
Open a point cloud viewer.
cli-anything-cloudanalyzer inspect view cloud.pcd
inspect web
Interactive browser inspection.
cli-anything-cloudanalyzer inspect web map.pcd ref.pcd --heatmap
inspect web-export
Export a static HTML inspection bundle.
cli-anything-cloudanalyzer inspect web-export map.pcd ref.pcd -o bundle/
7. info — Metadata (2 commands)
info show
Show point cloud metadata.
cli-anything-cloudanalyzer --json info show cloud.pcd
info version
Show CloudAnalyzer version.
8. session — Session Management (2 commands)
session new
Create a new harness project JSON file.
cli-anything-cloudanalyzer session new -o project.json -n my-run
session history
Show recent operations for the project given with -p / --project.
cli-anything-cloudanalyzer --project project.json session history --last 20
Typical Agent Workflows
Workflow 1: Evaluate and gate a point cloud
cli-anything-cloudanalyzer --json evaluate run output.pcd reference.pcd
Workflow 2: Config-driven QA pipeline
cli-anything-cloudanalyzer check init cloudanalyzer.yaml --profile integrated
cli-anything-cloudanalyzer --json check run cloudanalyzer.yaml
Workflow 3: Baseline management
cli-anything-cloudanalyzer --json check run cloudanalyzer.yaml --output-json qa/summary.json
cli-anything-cloudanalyzer baseline save qa/summary.json --history-dir qa/history/
cli-anything-cloudanalyzer --json baseline decision qa/summary.json --history-dir qa/history/
Workflow 4: Ground segmentation QA
cli-anything-cloudanalyzer --json evaluate ground \
est_ground.pcd est_ng.pcd ref_ground.pcd ref_ng.pcd --min-f1 0.9
Frequently asked questions about CloudAnalyzer CLI
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