---

name: labelme description: "Routes labelme image annotation, Annotation File, dataset export, AI-assisted annotation, configuration, and repository-maintenance workflows." disable-model-invocation: true metadata: disco-role: operating license: GPL 3.0

labelme

Use this skill when a task involves the labelme Python image-annotation application, its JSON Annotation Files, its YAML Config File, its conversion examples, or maintenance of the wkentaro/labelme repository.

First checks

• Install for normal use with python -m pip install labelme on Python 3.12+.
• Smoke-check an environment with scripts/check_labelme_environment.py when the task depends on the installed package, CLI, optional converters, or GUI display.
• Read references/public-interface-and-scope.md before treating any Python module as stable; labelme v7 is an application, not a general-purpose library.
• Read references/repo-provenance.md before deciding whether this skill is current for a checkout.
• For cross-cutting install, display, optional dependency, AI, or JSON load failures, start with references/troubleshooting.md.

Route by task

User task	Read next
Launch labelme, choose CLI flags, set labels/flags, use --config, inspect or validate the Config File, handle PySide6/display startup	sub-skills/cli-and-config/SKILL.md
Understand or validate labelme JSON, Shapes, Flags, Shape Flags, Groups, Mask Shapes, embedded imageData, dimensions, or rasterization behavior	sub-skills/annotation-data/SKILL.md
Convert Annotation Files to label.png, label_names.txt, VOC segmentation/object outputs, VOC bbox XML, or COCO annotations.json	sub-skills/dataset-export/SKILL.md
Use or debug AI Assist, AI Text Prompt, SAM/SAM2/SAM3/EfficientSAM/YOLO-World model choices, prompt compatibility, output shapes, suppression	sub-skills/ai-assisted-annotation/SKILL.md
Modify the labelme repository, choose tests, update changelog/docs/translations, interpret domain docs or triage labels	sub-skills/repo-development/SKILL.md

Operating model

• Use the project glossary terms precisely: an Annotation is the whole JSON bundle for one Image; a Shape is one drawn region; a Flag is image-level; a Shape Flag belongs to one Shape; a Group is shared group_id.
• Do not tell future agents to open original repo examples or tests. This skill bundles distilled references and reusable scripts for the common workflows.
• Prefer direct JSON parsing for downstream ML datasets. The package's internal modules are useful evidence but not public API promises.
• Treat real AI model download/inference as optional and network-bound. Prompt compatibility must be checked before model download or inference.
• Treat GUI tests and interactive sessions as display-dependent. CLI help, config parsing, Annotation File validation, and conversion scripts are headless.

Bundled shared scripts

• scripts/check_labelme_environment.py verifies installed package metadata, imports, CLI help, optional dependency availability, and display variables.
• scripts/labelme_json_core.py is a shared, self-contained helper library used by the bundled Annotation File and dataset export scripts; read it when adapting those scripts.

Verification and import status

This skill was produced with not import; it is a runtime candidate under the repository's skills/disco/ tree and is not installed into DisCo's managed repo-skills/ collection by this creation run. If later importing, use the verified repo-skill import protocol rather than manually editing a router.