42K shelf photographs with 1.3M product boxes, out-of-stock gaps and planogram compliance labels.
Shelf images captured in convenience stores, supermarkets and pharmacies across six countries, annotated for three tasks at once: product detection (1.3M boxes over 900 classes), empty-gap segmentation for out-of-stock detection, and a planogram compliance flag per shelf section.
Lighting, angle, reflections and occlusion are deliberately varied and labeled, so you can measure where a model degrades instead of discovering it in the field.
| Field | Type | Description |
|---|---|---|
image_id / file_name |
string | Identifier and path in the archive |
width / height |
integer | Image dimensions in pixels |
country / store_format |
string | Where the photograph was taken |
boxes |
array | class_id, class_name and bbox per product |
gap_regions |
array | Polygons marking empty shelf space |
planogram_compliant |
boolean | Section matches the reference layout |
lighting / occlusion_level |
string | Capture conditions |
split |
string | train, validation or test |
{
"image_id": "SHELF-020931",
"file_name": "images/SHELF-020931.jpg",
"width": 3024,
"height": 4032,
"country": "ES",
"store_format": "supermarket",
"lighting": "mixed",
"occlusion_level": "medium",
"planogram_compliant": false,
"split": "train",
"boxes": [
{
"class_id": 117,
"class_name": "biscuits_200g",
"bbox": [
412,
1880,
655,
2210
]
},
{
"class_id": 342,
"class_name": "detergent_1kg",
"bbox": [
1510,
960,
1902,
1498
]
}
],
"gap_regions": [
[
[
700,
1900
],
[
980,
1900
],
[
980,
2180
],
[
700,
2180
]
]
]
}
Illustrative sample showing the structure of the data. The full dataset is delivered after purchase.
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