Data Sheet 1_An annotated cucumber leaf image dataset for detection of visible damage and abnormal color symptoms in complex cultivation environments.csv

The two phenotype labels are operationally non-exclusive: 215 affected images contain both classes, and 116 contain at least one positive-area cross-class box overlap. These labels describe observable phenotypes and do not provide pathogen, disease-species, cultivar, or causal diagnoses. The release supplies bounding boxes, not pixel-level masks; it therefore supports image classification, object detection, and rectangular region localization, but not conventional supervised segmentation.

A complete decoder, structure, coordinate, exact-hash, filename, and coarse perceptual-hash audit confirmed one-to-one affected image-label pairing and valid five-field rows, while identifying 42 boundary-crossing boxes in 36 files, 19 byte-identical pairs, and three additional high-similarity candidate pairs. The intentionally balanced final folders are a curated sample and must not be interpreted as natural prevalence.

The dataset is publicly available in Mendeley Data, version 1, under CC BY 4.0 at doi.org/10.17632/mb3vnhpk8z.1.</p>