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map

Evaluate detector outputs with VOC-style AP/mAP, convert annotations into evaluator text, and inspect or repair GT/DR file sets.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

name: map description: "Evaluate detector outputs with VOC-style AP/mAP, convert annotations into evaluator text, and inspect or repair GT/DR file sets." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

mAP

Use this repo skill for the Cartucho/mAP evaluation workflow: evaluate detector outputs, convert source annotations into the evaluator format, or check whether ground-truth and detection-result folders are ready to run.

Start here

  • If you already have evaluator-ready .txt files for ground-truth/ and detection-results/, go to sub-skills/evaluation/SKILL.md.
  • If you need to convert VOC XML, YOLO, darkflow JSON, darknet result.txt, or keras-yolo3 annotations, go to sub-skills/conversion/SKILL.md.
  • If you need to find classes or check/repair matching filenames before evaluation, go to sub-skills/data-validation/SKILL.md.

Minimum runtime

  • Python 3.11 or newer.
  • numpy for evaluation.
  • Optional: matplotlib for plots and opencv-python for animation.

Route map

Evaluation

Read sub-skills/evaluation/SKILL.md when the user asks for AP, mAP, precision/recall, IoU thresholds, ignored classes, output interpretation, or optional plots/animation.

Bundled helper:

  • sub-skills/evaluation/scripts/run_map_evaluation.py

Conversion

Read sub-skills/conversion/SKILL.md when the user needs source annotations or detector outputs transformed into evaluator .txt files.

Bundled helper:

  • sub-skills/conversion/scripts/convert_annotations.py

Data validation

Read sub-skills/data-validation/SKILL.md when the user needs to find a class, compare GT/DR basenames, or safely repair file-set mismatches before evaluation.

Bundled helper:

  • sub-skills/data-validation/scripts/check_map_inputs.py

Recommended order

  1. Validate the file sets with data-validation.
  2. Convert any non-evaluator formats with conversion.
  3. Run AP/mAP with evaluation.

That order keeps the workflow explicit and avoids chasing metric errors that are actually data-layout problems.

What not to do here

  • Do not open the original repository checkout as a runtime dependency.
  • Do not run the legacy mutating scripts from the source repository; use the bundled helpers in this generated skill tree instead.
  • Do not use this root router for metric math details, conversion row schemas, or repair steps. Those belong in the sub-skills and their references.

References

  • references/repo-overview.md — quick map of the repo workflows and file-layout assumptions.
  • references/troubleshooting.md — cross-cutting symptoms that decide whether to route to evaluation, conversion, or data-validation.
  • references/repo-provenance.md — source commit, branch, dirty-state summary, and evidence paths.
  • references/repo-routing-metadata.json — structured metadata for the managed repo-skills router.
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