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name: open3d-ml description: "Guides Open3D-ML installation, dataset workflows, config-driven training, visualization, and backend-specific troubleshooting." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

Open3D-ML

Use this skill for Open3D-ML point-cloud workflows: installing the package, loading datasets, building config-driven pipelines, inspecting predictions, and handling the optional TensorFlow, CUDA, GUI, or OpenVINO paths.

Start here

1. If the package does not import yet, read references/troubleshooting.md and route to sub-skills/install-and-inspect/.
2. If you need dataset folders, split handling, or custom data layouts, route to sub-skills/datasets-and-preprocessing/.
3. If you need model selection, config-driven training, or inference, route to sub-skills/training-and-pipelines/.
4. If you need point-cloud inspection, bounding boxes, TensorBoard summaries, or OpenVINO wrapping, route to sub-skills/visualization-and-extensions/.

Quick install guidance

A conservative CPU inspection path is enough for many checks:

python -m pip install open3d 'torch==2.2.*+cpu' 'torchvision==0.17.*+cpu' \
  addict numpy<2 pyyaml tensorboard

If you are using a local Open3D-ML checkout with an external Open3D wheel, set OPEN3D_ML_ROOT to the checkout root before importing open3d.ml.*.

Minimal smoke checks

Use the bundled helper when you want a safe status report:

python scripts/check_install.py --framework torch
python scripts/check_install.py --framework torch --config path/to/config.yml

If you only need to inspect config files without launching a workflow, use:

python scripts/inspect_configs.py path/to/config-or-directory

Route map

• install-and-inspect: importability, backend compatibility, and startup failure recovery.
• datasets-and-preprocessing: dataset constructors, split names, custom point-cloud layouts, and layout validation.
• training-and-pipelines: config loading, registry lookup, model selection, and semantic-segmentation/object-detection workflows.
• visualization-and-extensions: Visualizer, label LUTs, bounding boxes, TensorBoard summaries, and OpenVINO guidance.

What this skill is good at

• Finding the right Open3D-ML class or config shape for a 3D workflow.
• Explaining the difference between dataset layout, pipeline configuration, and visualization output.
• Helping you choose a CPU smoke path versus an optional backend-specific path.

What to read when you need more detail

• references/model-overview.md for the top-level task and model map.
• references/troubleshooting.md for cross-cutting failure families.
• The nearest sub-skill references for workflow-specific details.

Provenance

Read references/repo-provenance.md before deciding whether this skill still matches the current checkout, and refresh the skill if the repo state has moved.