name: dataset-annotation
description: "Pseudo-label image folders with GroundingDINO detections, optional
COCO export, and annotated-image review while keeping optional dataset tooling
explicit."
disable-model-invocation: true
metadata:
disco-role: operating
license: Apache 2.0
Dataset Annotation
Use this sub-skill when the task is to pseudo-label a folder of images with GroundingDINO, inspect annotated review images, or export detections as a COCO-style dataset.
Route first
- For one image, direct API inference, token spans, or prompt debugging, use
../inference/.
- For COCO AP or benchmark evaluation, use
../evaluation/.
- For Gradio, notebooks, Grounded-SAM, or image-editing integrations, use
../integrations/.
What this covers
- Folder pseudo-labeling with
image_directory, text_prompt, box_threshold, text_threshold, weights_path, config_path, and optional subsample controls.
- Optional COCO export and annotated-image review outputs without launching a GUI by default.
- Safe handling for optional
fiftyone and Typer-style workflow dependencies; the bundled helper uses argparse, not Typer.
- Conversion from GroundingDINO normalized
cxcywh predictions into FiftyOne relative xywh detections.
Bundled helper
From this sub-skill directory, start with:
python scripts/grounding_dino_pseudolabel.py --help
Minimal non-GUI COCO export example:
python scripts/grounding_dino_pseudolabel.py \
--image-directory ./images \
--text-prompt "bus . car ." \
--config-path ./GroundingDINO_SwinT_OGC.py \
--weights-path ./groundingdino_swint_ogc.pth \
--export-coco \
--draw-labels \
--output-dir ./pseudolabel-output \
--subsample 25
The helper never downloads checkpoints or datasets. Provide an existing config file and checkpoint, and pass --view only when a local FiftyOne GUI/server is intended.
References
- Workflow and commands:
references/pseudolabel-workflow.md
- Detection and export formats:
references/data-formats.md
- Failure modes and recovery:
references/troubleshooting.md