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name: dataset-tools description: "Guide SAHI COCO dataset creation, slicing, filtering, conversion, evaluation, error analysis, and visualization workflows." disable-model-invocation: true metadata: disco-role: operating license: MIT

Dataset Tools

Use this sub-skill when a task is about SAHI dataset operations rather than model construction or per-image prediction. It covers COCO-style dataset creation, loading, slicing, filtering, merging, train/validation splitting, YOLO export, COCO evaluation/error analysis, and FiftyOne visualization.

Route here for

• Building or loading COCO datasets with Coco, CocoImage, CocoAnnotation, CocoPrediction, and category definitions.
• Slicing a COCO dataset with sahi.slicing.slice_coco or sahi coco slice.
• Remapping/filtering categories, clipping boxes to image dimensions, keeping or dropping negative images, subsampling/upsampling, merging datasets, and train/validation splitting.
• Exporting COCO datasets to YOLO/Ultralytics layout with sahi coco yolo or the Coco export helpers.
• Running COCO evaluation, error-analysis plots, or FiftyOne visualization when optional dependencies are available.

Route away

• Per-image prediction, sliced inference, model loading, or detector backend setup: use the sliced-inference and model-integrations sibling sub-skills.
• Low-level conversion between SAHI prediction/result objects and annotation objects: use the annotations-and-results sibling sub-skill.

Operating references

1. Read COCO CLI and API for SAHI dataset APIs, CLI commands, required optional dependencies, and workflow recipes.
2. Read Data formats and output layouts before writing or consuming COCO JSON, sliced datasets, YOLO exports, COCO result JSON, evaluation outputs, or FiftyOne inputs.
3. Read Troubleshooting when loading fails, categories do not match, negative samples disappear, boxes are clipped or invalid, evaluation dependencies are missing, FiftyOne does not launch, or YOLO symlinks fail.
4. For a dependency-light local sanity check, run python scripts/coco_fixture_smoke.py from this sub-skill directory. The script creates only temporary files and does not require pycocotools, FiftyOne, network access, model weights, or training.

Minimal decision checklist

• Confirm whether the task needs API usage, CLI usage, or both.
• Confirm the image directory that images[*].file_name resolves against.
• Decide whether images without annotations must be preserved (ignore_negative_samples=False) or excluded.
• Decide whether category IDs must be remapped before splitting or YOLO export.
• Treat pycocotools and FiftyOne as optional: guard those workflows and provide a fallback JSON validation path when they are unavailable.