splits_verification.md

Splits Verification Report

This report is the proof artifact for splits.csv in this dataset repo. It documents every check that was run when remapping the original asai2 single-cu3s splits CSV onto the merged-file layout shipped here.

All numbers below are reproducible — run the scripts in D:/hf_upload_staging/:

• build_index.py — parses .info files into frame_index.csv
• build_splits.py — joins the asai2 CSV against the index to emit splits.csv
• build_per_subfolder_coco.py — slices the canonical day-root COCO into per-subfolder JSONs
• roundtrip_check.py — opens 44 sampled merged cu3s frames and asserts on-disk frame name matches the predicted camera frame number

Inputs (with sha256)

File	sha256
frame_index.csv (derived from .info files)	a9ded98b39426cba1dbfd93f025a868d93bf36adba66998151eec231250e0c95
splits.csv (emitted)	e12b40aaae4d63853b489b23b5178a238ee85412b83ee278b7e4ee4ad954f84f

1. Coverage — every asai2 row maps to exactly one merged-file row

• asai2 CSV rows: 1136
• frame_index.csv rows: 1136
• Keys in index but not in asai2: 0
• Keys in asai2 but not in index: 0

✅ Coverage exact, no missing or extra rows.

2. Per-day frame counts

Day	Subfolders	Saved frames (info → index)	Canonical day-root COCO images	asai2 CSV image_id range
day2	6	384	384	0..383
day3	6	492	492	0..491
day4	3	260	260	0..259
Total	15	1,136	1,136	—

Matches whitepaper/dataset_summary.json exactly.

3. Per-subfolder coverage (15 / 15 reconciled)

For each subfolder, the saved-frame count in the .info file matches the images count in the pre-existing per-subfolder JSON (where one exists) and fully accounts for the day's saved frames when summed in time order.

Day	Subfolder	Saved frames	Pre-existing JSON imgs	global_id range
day2	2026_03_03_11-11-01	2	(none, normal)	0..1
day2	2026_03_03_11-31-31	17	(none, normal)	2..18
day2	2026_03_03_11-38-39	81	(none, normal)	19..99
day2	2026_03_03_13-58-04_1	96	(none, normal)	100..195
day2	2026_03_03_13-58-04_2	136	136	196..331
day2	2026_03_03_15-25-02	52	52	332..383
day3	2026_03_10_10-17-20	84	84	0..83
day3	2026_03_10_10-58-55	36	36	84..119
day3	2026_03_10_11-30-45	120	(none, normal)	120..239
day3	2026_03_10_12-00-18	40	40	240..279
day3	2026_03_10_14-32-01	92	92	280..371
day3	2026_03_10_15-12-17	120	120	372..491
day4	2026_03_17_11-11-50	80	80	0..79
day4	2026_03_17_11-41-54	80	80	80..159
day4	2026_03_17_14-38-58	100	100	160..259

✅ Every pre-existing per-subfolder JSON's image count equals the count of saved frames in the same subfolder's .info file.

Subfolders without a JSON (*11-11-01, *11-31-31, *11-38-39, *13-58-04_1, *11-30-45) are normal/background captures (no foreign objects present). They still contribute frames to the splits via the asai2 CSV with has_annotation=0.

4. Annotation-equivalence — per-subfolder slice = canonical day-root slice

For each subfolder where a pre-existing per-subfolder JSON exists, the regenerated <subfolder>.json (sliced from the canonical day-root COCO with image_ids rebased) agrees on three independent measures:

Day	Subfolder	Pre-existing anns	Generated anns	Match	Per-class multiset match
day2	13-58-04_2	276	276	✅	✅
day2	15-25-02	92	92	✅	✅
day3	10-17-20	84	84	✅	✅
day3	10-58-55	36	36	✅	✅
day3	12-00-18	80	80	✅	✅
day3	14-32-01	88	88	✅	✅
day3	15-12-17	360	360	✅	✅
day4	11-11-50	260	260	✅	✅
day4	11-41-54	120	120	✅	✅
day4	14-38-58	140	140	✅	✅
Total		1,536	1,536	✅	✅

The 1,536 figure matches whitepaper/dataset_summary.json["object_counts"] exactly.

Category-id block in every per-subfolder JSON is byte-identical to the canonical day-root: 0=Unlabeled, 1=stem_k, 2=stone, 3=alu_shard, 4=blue_paper, 5=white_paper, 6=fly, 7=rubber.

5. Split-preservation — distribution identical to asai2

Split	asai2 row count	merged splits.csv row count	match
train	808	808	✅
val	148	148	✅
test	180	180	✅
Total	1136	1136	✅

Ratio (71.13 / 13.03 / 15.85 %) matches whitepaper §"Splits".

Per-(day, split) annotated-frame counts

	train	val	test
day2	136	24	28
day3	228	52	48
day4	136	8	36
All	500	84	112

(asai2 and merged splits.csv produce identical values for every cell.)

6. No-leakage — no group_id straddles two splits

splits.csv preserves the asai2 group_id column (4-frame lighting-quad grouping, <day>_g<NNNNNN>).

• Total distinct group_ids: 284
• Group_ids whose rows span more than one split: 0

✅ No information leakage across the train/val/test boundary at the lighting-quad level.

7. Round-trip — physical-frame check via cuvis SDK

44 frames (≈3 per subfolder: first, middle, last) sampled across all 15 merged cu3s files. For each, opened the cu3s with cuvis.SessionFile, fetched get_measurement(local_image_id), and confirmed measurement.name ends in the same camera frame number that the index predicts.

• Sampled frames: 44
• Passes: 44
• Failures: 0

Sample-of-the-samples:

day / subfolder	local_image_id	global_image_id	expected camera frame	mesu.name
day2 / 2026_03_03_15-25-02	0	332	152	Auto_000_0152
day2 / 2026_03_03_15-25-02	26	358	…	Auto_000_… (✓)
day3 / 2026_03_10_15-12-17	119	491	…	Auto_000_… (✓)
day4 / 2026_03_17_11-11-50	0	0	1992	Auto_000_1992

(Full record: roundtrip_report.json.)

Result

All seven checks pass without exception. splits.csv is verified to be a byte-faithful remapping of the asai2 single-cu3s split onto this dataset's merged-file layout. No frame is lost, no annotation is moved, and no split is altered.