---

name: dataset-pipelines description: "Route Hierarchical-Localization benchmark and dataset-specific pipelines, layouts, prerequisites, and safe dry-run planning without accidental downloads or benchmark-scale runs." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Dataset Pipelines

Use this sub-skill when the task is about a dataset-specific hloc workflow, benchmark routing, output-folder planning, or a safe no-run checklist.

Route here

• Aachen Day-Night v1.0 and v1.1.
• InLoc notebook workflow.
• SfM demo workflow.
• 4Seasons, 7Scenes, CMU, Cambridge, and RobotCar.
• Output-folder conventions, pair-file placement, and dry-run planning.

Route away

• Low-level feature, retrieval, match-file, or HDF5 details go to feature-retrieval or mapping-localization.
• Custom extractor or matcher implementation goes to custom-interop.
• Full benchmark execution or downloads are never implied by a planning-only request.

Bundled guidance

• references/dataset-pipelines.md
• references/troubleshooting.md
• scripts/list_pipeline_entrypoints.py

Safe planning rules

1. Confirm the dataset root, required archives, pair files, and calibration assets before any run.
2. If a required dataset download or benchmark asset is missing, stop at a plan-only response.
3. Use the output roots and per-scene or per-sequence folder conventions from the reference table.
4. Treat 4Seasons as destructive unless you are working on a copy of the dataset.
5. Prefer the bundled entrypoint lister and --help command templates when deciding what to run next.