Dataset Card
TACO
A public computer-vision dataset of 1,500 images with 4,784 annotations across 60 classes, annotated as bounding box and polygon.
Pictograph Research · CC-BY-4.0 · Public · Updated 2026-08-08
Overview
This dataset holds 1,500 images annotated as bounding box and polygon across 60 classes. The most common auto-detected tags are grass, sidewalk, sand, gravel, bush, eye-level view. It is ready to fork, export in a dozen formats, or train a model from.
At a glance
| Metric | Value |
|---|---|
| Images | 1,500 |
| Annotations | 4,784 |
| Classes | 60 |
| Annotation types | bounding box, polygon |
| Folders | 1 |
| Storage | Standard |
| Visibility | Public |
What's in these images
Tags auto-detected across the dataset, most common first.
| Tag | Category | Images |
|---|---|---|
| grass | Objects | 517 |
| sidewalk | Objects | 462 |
| sand | Attributes | 414 |
| gravel | Attributes | 404 |
| bush | Objects | 381 |
| eye-level view | Attributes | 366 |
| top-down view | Attributes | 348 |
| bottle | Objects | 315 |
| concrete | Attributes | 310 |
| beach | Scenes | 305 |
| shadow | Attributes | 244 |
| frisbee | Objects | 211 |
| ruins | Objects | 203 |
| field | Scenes | 192 |
| water | Attributes | 191 |
Use this dataset
from pictograph import Client, Dataset
client = Client() # reads PICTOGRAPH_API_KEY
dataset: Dataset = client.datasets.get("TACO")
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 CC-BY-4.0.
Creative Commons Attribution 4.0 Data / content
Allows any use, including commercial, as long as appropriate credit is given. A common choice for datasets.
Read the full Creative Commons Attribution 4.0 →More from Pictograph Research
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