Dataset Card
FoodSeg103
A public computer-vision dataset of 7,118 images with 40,275 annotations across 103 classes, annotated as polygon.
Pictograph Research · a custom license · Public · Updated 2026-08-08
Overview
This dataset holds 7,118 images annotated as polygon across 103 classes. The most common auto-detected tags are eating, cooking, plate, bread, salad, sandwich. It is ready to fork, export in a dozen formats, or train a model from.
At a glance
| Metric | Value |
|---|---|
| Images | 7,118 |
| Annotations | 40,275 |
| Classes | 103 |
| Annotation types | polygon |
| Folders | 2 |
| Storage | Standard |
| Visibility | Public |
What's in these images
Tags auto-detected across the dataset, most common first.
| Tag | Category | Images |
|---|---|---|
| eating | Attributes | 5,652 |
| cooking | Attributes | 3,110 |
| plate | Objects | 2,615 |
| bread | Objects | 881 |
| salad | Objects | 833 |
| sandwich | Objects | 740 |
| cake | Objects | 668 |
| broccoli | Objects | 533 |
| fish | Objects | 533 |
| strawberry | Objects | 398 |
| burger | Objects | 394 |
| carrot | Objects | 380 |
| pasta | Objects | 350 |
| corn | Objects | 292 |
| top-down view | Attributes | 281 |
Use this dataset
from pictograph import Client, Dataset
client = Client() # reads PICTOGRAPH_API_KEY
dataset: Dataset = client.datasets.get("FoodSeg103")
print(dataset.image_count, dataset.annotation_count)- Fork it into your own workspace with one click from its page.
- Pull it with the Pictograph SDK (shown above) or the CLI.
- Export to COCO, YOLO, Darwin V7, Pascal VOC, and more.
- Train a model directly from an export.
License
Released under a custom license.
Custom License Other
Annotations and benchmark code: Apache License 2.0 (the FoodSeg103 authors). Images: curated from the Recipe1M dataset (MIT CSAIL, im2recipe) and subject to Recipe1M terms of use - non-commercial research/educational use, registration-gated, redistribution not granted. Attribute both FoodSeg103 (Wu et al., ACM MM 2021) and Recipe1M (Marin et al.).
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