Automatically convert auto-annotation outputs to Label Studio format and write to t_dm_annotation_results table, enabling seamless editing in the annotation editor.
New file:
- runtime/python-executor/datamate/annotation_result_converter.py
* 4 converters for different annotation types:
- convert_text_classification → choices type
- convert_ner → labels (span) type
- convert_relation_extraction → labels + relation type
- convert_object_detection → rectanglelabels type
* convert_annotation() dispatcher (auto-detects task_type)
* generate_label_config_xml() for dynamic XML generation
* Pipeline introspection utilities
* Label Studio ID generation logic
Modified file:
- runtime/python-executor/datamate/auto_annotation_worker.py
* Preserve file_id through processing loop (line 918)
* Collect file_results as (file_id, annotations) pairs
* New _create_labeling_project_with_annotations() function:
- Creates labeling project linked to source dataset
- Snapshots all files
- Converts results to Label Studio format
- Writes to t_dm_annotation_results in single transaction
* label_config XML stored in t_dm_labeling_projects.configuration
Key features:
- Supports 4 annotation types: text classification, NER, relation extraction, object detection
- Deterministic region IDs for entity references in relation extraction
- Pixel to percentage conversion for object detection
- XML escaping handled by xml.etree.ElementTree
- Partial results preserved on task stop
Users can now view and edit auto-annotation results seamlessly in the annotation editor.
