---

name: datasets description: "Use supervision DetectionDataset and ClassificationDataset for loading, splitting, merging, converting, and exporting datasets." disable-model-invocation: true metadata: disco-role: operating license: MIT

Datasets

Use this sub-skill when a task centers on supervision dataset containers or format conversion. It covers DetectionDataset and ClassificationDataset in supervision 0.31.0.dev0 on Python >=3.10.

Trigger here

• Load detection datasets with DetectionDataset.from_yolo, from_coco, from_pascal_voc, from_labelme, or from_createml.
• Export detection datasets with as_yolo, as_coco, as_pascal_voc, as_labelme, or as_createml.
• Split, merge, iterate, visualize, augment, or convert detection datasets.
• Load or export classification folder-structure datasets with ClassificationDataset.from_folder_structure or as_folder_structure.
• Diagnose dataset path safety, duplicate image collisions, class-id/name remapping, CLASS_NAME_DATA_FIELD, ORIENTED_BOX_COORDINATES, mask polygon/RLE behavior, or progress flags.

Route away

• Evaluation metrics after predictions: use metrics.
• Primitive image/video/file helpers, OpenCV backend selection, or plotting grids: use media-utils.
• Detections construction, framework adapters, filtering, zones, slicers, sinks, or low-level detection internals: use detection-and-zones.
• Styling annotated images beyond quick dataset inspection: use annotators.

Start with these references

• Data formats for exact layouts, loader/exporter methods, class-id conventions, masks, OBBs, and classification folders.
• Workflows for load/split/merge/convert/export and common dataset-processing recipes.
• Troubleshooting for unsafe paths, COCO category indexing, class remapping, duplicate images, masks/RLE, shape constraints, progress flags, and dataset API version pinning.

Operating rules

1. Prefer public APIs exported from supervision as sv.DetectionDataset, sv.ClassificationDataset, sv.Detections, and sv.Classifications.
2. Treat dataset image storage as path-first. Passing a dict of in-memory images still works but is deprecated; use list-of-paths unless a user already owns arrays and accepts the deprecation.
3. Assume detection dataset annotations are Detections keyed by the same image paths as the dataset image list. Constructor validation rejects key mismatches, non-integer class_id, and class ids outside dataset.classes.
4. After constructing or merging a DetectionDataset, rely on detections.data["class_name"] only as metadata derived from classes and class_id; do not hand-edit it without also keeping class_id aligned.
5. For conversion work, name source and target formats, required directories or JSON/YAML/XML files, whether masks are required, whether YOLO OBB mode is required, and whether progress bars are acceptable.