---

name: dataset-export description: "Guides headless conversion of labelme Annotation Files into label PNGs, VOC semantic or instance datasets, VOC bounding boxes, and COCO annotations." disable-model-invocation: true metadata: disco-role: operating license: GPL 3.0

Dataset Export

Use this route when the input is a directory or file of labelme Annotation Files and the output should be a training-data format or a sanity-checked label PNG.

Choose an export

• One JSON to image/class-label artifacts: scripts/export_labelme_json.py.
• Semantic or instance VOC segmentation: scripts/labelme_export_voc.py.
• Rectangle-only VOC detection XML: scripts/labelme_export_bbox_voc.py.
• Instance COCO JSON: scripts/labelme_export_coco.py.
• Inspect a label PNG's dtype, shape, or values: scripts/inspect_label_png.py.

Safe workflow

1. Validate representative Annotation Files with ../annotation-data/scripts/validate_labelme_json.py.
2. Prepare a labels file. For VOC/COCO examples, the first entries are __ignore__ (id -1) and _background_ (id 0); actual classes follow.
3. Use a new output directory. The VOC/COCO directory exporters refuse to overwrite an existing directory; export_labelme_json.py follows the tutorial helper and can reuse its output directory, so pass a fresh --out when avoiding clobbering matters.
4. Run the converter's --help, then run it against a tiny or copied input.
5. Inspect class_names.txt, a label PNG, image dimensions, and the generated annotation JSON/XML before using the result for training.
6. Read references/troubleshooting.md for optional dependencies and label vocabulary failures.

Format ownership

• label.png stores class ids; label_names.txt maps ids to names.
• VOC segmentation emits SegmentationClass, and optionally SegmentationObject, plus optional NumPy and visualization outputs.
• VOC bbox export keeps only rectangle Shapes; other Shape types are skipped.
• COCO groups Shapes by (label, group_id) for instance masks and emits polygon segmentations, area, bbox, and category ids.
• Video annotation is handled as a directory of frame Annotation Files; use the same semantic/instance VOC path, not a special video codec.

References and scripts

• Read references/workflows.md for copyable commands and expected layouts.
• Read references/conversion-reference.md for label ids, shape support, and optional dependencies.
• Read references/troubleshooting.md for validation and export recovery.
• All linked scripts are bundled under this skill and do not require the original repository checkout.

Route low-level JSON repair to ../annotation-data/SKILL.md, CLI/session setup to ../cli-and-config/SKILL.md, AI-generated Shapes to ../ai-assisted-annotation/SKILL.md, and source changes to ../repo-development/SKILL.md.