Identify the physical unit behind each image
Record image ID, part or batch ID, capture time, camera or station, and view when available. Separate image counts from distinct physical-part counts. Multiple near-identical frames can inflate the apparent size of a collection. Report missing parent IDs instead of inferring relationships that the records cannot support.
Describe how labels were obtained
Keep the class taxonomy and its version with the collection. Distinguish labels observed during inspection, labels assigned later, and labels inferred from another system. Record reviewer roles, disagreement handling, and unknown or ambiguous cases. Do not present an unreviewed machine-generated label as a confirmed physical defect.
Measure coverage at the level of the task
Show counts for normal examples, each defect class, capture station, lighting condition, and time period where known. Indicate whether a count refers to images or parts. Rare-defect enrichment can help test a particular failure mode, but it does not reproduce the operating prevalence of that defect. State that limitation in the sample notes.
Split related images together
Ask the evaluator which grouping avoids overlap for its intended task. Keeping all views of a physical part together is a useful starting point; batch or time grouping may also matter. Record the grouping rule and unresolved identity gaps. Compare both metadata and obvious duplicates before claiming that evaluation subsets are independent.
Review visible context and deliver label geometry
Flag faces, badges, serial numbers, customer identifiers, and restricted facility context for appropriate review. Document bounding-box coordinate conventions or mask formats, image orientation, and any resizing applied. Check that annotations still align after transformations and keep transformed files linked to the original version.
Inspection image review sheet
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