Die Oberfläche ist lokalisiert; Skill-Beschreibungen und -Dokumente werden per KI automatisch in Ihre Sprache übersetzt. Code, Befehle, Pfade und Fachbegriffe bleiben im Original, maßgeblich ist das Dokument des Autors.
Skills entdecken
Produktivität · SKILL.md

evaluation

evaluation

Run VOC-style AP and mAP evaluation for matching ground-truth and detection-result folders.

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill-Dokumentation

GitHub

name: evaluation description: "Run VOC-style AP and mAP evaluation for matching ground-truth and detection-result folders." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Evaluation

Use this sub-skill when the task is to compute VOC-style AP/mAP from already-prepared evaluator text files. It is for metric execution, output interpretation, class filtering, per-class IoU thresholds, and optional visualization artifacts.

Load When

  • The user has a ground-truth/ folder and a detection-results/ folder with matching .txt basenames.
  • The goal is to run AP/mAP, explain AP math, inspect output.txt, or compare the effect of --ignore / --set-class-iou.
  • The user asks why an evaluation failed because files are missing, rows are malformed, optional plot/animation dependencies are absent, an output directory would be overwritten, or a class-specific IoU option is invalid.

Route Elsewhere

  • Annotation or detector-output conversion is owned by the sibling conversion sub-skill.
  • Dataset intersection checks, missing-file repair, and class lookup helpers are owned by the sibling data-validation sub-skill.
  • This sub-skill may tell the user that those steps are needed, but do not reimplement them here.

Required Workflow

  1. Confirm the two input folders already use evaluator text format and have matching image ids by basename.
  2. Read references/data-formats.md for row schemas, difficult-object behavior, ignored-class behavior, IoU thresholding, and AP/mAP math.
  3. Read references/cli-reference.md before invoking the bundled script. Prefer the safe wrapper in scripts/run_map_evaluation.py; it requires explicit input/output paths and disables plots/animation by default.
  4. Run evaluation with an explicit output directory. Use --overwrite only after deciding that deleting the previous output directory is safe.
  5. Interpret output.txt and summary.json; if plots or animation were requested, inspect the generated optional artifacts.
  6. If the run fails, use references/troubleshooting.md and route conversion or dataset repair requests to the appropriate sibling sub-skill.

Common Commands

python scripts/run_map_evaluation.py \
  --ground-truth-dir path/to/ground-truth \
  --detection-results-dir path/to/detection-results \
  --output-dir path/to/map-output \
  --quiet
python scripts/run_map_evaluation.py \
  --ground-truth-dir path/to/ground-truth \
  --detection-results-dir path/to/detection-results \
  --output-dir path/to/map-output \
  --ignore difficult_class unused_class \
  --set-class-iou person 0.7 car 0.6 \
  --overwrite \
  --quiet

References

  • references/workflows.md — end-to-end evaluation workflow, output interpretation, optional visualization guidance, and provenance note.
  • references/data-formats.md — required file layout, GT/DR row schemas, difficult rows, ignore handling, IoU/AP/mAP math.
  • references/cli-reference.md — bundled wrapper flags and source-compatible flag meanings.
  • references/troubleshooting.md — recovery for missing files, malformed rows, optional dependencies, output overwrite, IoU override, and ignored-class issues.
Gespeicherte Skills