text-spotting
Use this sub-skill when a task names BAText, ABCNet, BezierAlign, scene text, text spotting, OCR recognition, lexicons, dictionaries, text evaluation, or Bezier control-point annotations in AdelaiDet.
Use this route for
- Choosing and editing BAText/ABCNet configs.
- Preparing text datasets and Bezier/control-point annotations.
- Understanding
BezierAlign,TextEvaluator, custom dictionaries, and lexicons. - Running text-model demos after setup succeeds.
- Debugging missing recognized strings, evaluator failures, rapidfuzz issues, or text visualization problems.
Do not use this route for
- General installation and CUDA extension failures. Use
../setup-build/SKILL.md. - Non-text FCOS/BlendMask/CondInst training. Use
../train-eval/SKILL.md. - General COCO/PIC/LVIS conversion unrelated to text. Use
../data-prep/SKILL.md. - Checkpoint/ONNX conversion. Use
../export-convert/SKILL.md.
Read first
references/text-workflows.mdfor BAText/ABCNet config, training, demo, and evaluation flow.references/text-data-and-eval.mdfor annotation fields, dictionaries, lexicons, and evaluator caveats.../../references/api-reference.mdfor verified BezierAlign/TextEvaluator surfaces.
Typical workflow
-
Confirm setup with CUDA ops:
bashpython ../../scripts/check_install.py --cuda-ops -
Choose a
configs/BAText/YAML and inspectMODEL.BATEXTkeys. -
Validate text dataset annotations through
data-prepif files are custom. -
For training/eval, use
train-evallaunch wrappers and add text-specific overrides. -
For visualization, use
demo-visualizewrappers with the text config/weights. -
Interpret recognition/evaluation results here, not in generic detection routes.
Decision points
rapidfuzz.string_metricerror: pinrapidfuzz<3in setup.- BezierAlign op failure: return to
setup-build; text pooling depends onadet._C. - Boxes draw but text is blank/wrong: check dictionary/lexicon config and annotation transcription fields.
- Dataset lacks Bezier points: route to
data-prep; box-only COCO annotations are insufficient for text recognition. - Evaluation protocol disagreement: identify the target benchmark lexicon/protocol before comparing numbers.


