* fix(dataset): make COCO annotation/image ids chainable across splits (#768)
Exporting train/valid/test splits with DetectionDataset.as_coco
previously restarted image_id and annotation_id at 1 for every split,
producing three JSON files whose ids collided and could not be safely
merged into a single COCO collection.
Adds optional starting_image_id and starting_annotation_id parameters
to save_coco_annotations and DetectionDataset.as_coco (default 1 to
preserve existing behavior) and returns a (next_image_id,
next_annotation_id) tuple so callers can feed the result of one
export straight into the next:
next_image, next_ann = train.as_coco(annotations_path="train.json")
next_image, next_ann = valid.as_coco(
annotations_path="valid.json",
starting_image_id=next_image,
starting_annotation_id=next_ann,
)
test.as_coco(
annotations_path="test.json",
starting_image_id=next_image,
starting_annotation_id=next_ann,
)
The images-only branch of as_coco (annotations_path=None) round-trips
the starting ids unchanged so chaining still works there.
Adds 4 regression tests covering defaults, custom starting ids,
end-to-end three-split chaining with global uniqueness assertions,
and the images-only round-trip.
* docs: address review polish on COCO id-chaining
* fix(dataset): align save_coco_annotations approximation_percentage default to 0.0
* docs(dataset): add one-line summary to save_coco_annotations docstring
* docs: add changelog entry for COCO id chaining (PR #2267)
* docs(dataset): document file_name uniqueness limitation in save_coco_annotations
* feat(dataset): validate starting_image_id and starting_annotation_id >= 1
* docs(dataset): add Example section to save_coco_annotations docstring
* docs(dataset): unpack final as_coco return value in chaining example
* test(dataset): add COCO chaining tests and fix test helper for zero detections
---------
Co-authored-by: Jirka Borovec <6035284+Borda@users.noreply.github.com>
Co-authored-by: Claude Code <noreply@anthropic.com>
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