---
license: apache-2.0
pretty_name: "Keypoint Detection Demo"
task_categories:
  - keypoint-detection
tags:
  - computer-vision
  - pictograph
annotations_creators:
  - expert-generated
size_categories:
  - n<1K
source_datasets:
  - original
configs:
  - config_name: default
    data_files:
      - split: train
        path: "train/*"
---

# Keypoint Detection Demo

> 60 images and 360 annotations across 6 classes, annotated as keypoint.

**[View on Pictograph](https://pictograph.io/datasets/pictograph/keypoint-detection-demo)** · [Pictograph](https://pictograph.io/org/pictograph) · [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0)

## About

**Keypoint Detection Demo** is a computer-vision dataset curated and annotated on [Pictograph](https://pictograph.io/datasets/pictograph/keypoint-detection-demo). On Pictograph you can browse every annotated image, fork it into your own workspace in one click, export it in a dozen formats, or train a model on it directly.

## At a glance

| Metric | Value |
| :--- | ---: |
| Images | 60 |
| Annotations | 360 |
| Classes | 6 |
| Annotation types | keypoint |
| Splits | train |

## Dataset structure

This dataset uses the Hugging Face `imagefolder` layout: each split directory holds the images plus a `metadata.jsonl` that links every image to its annotations by `file_name`.

| Field | Description |
| :--- | :--- |
| `file_name` | Path to the image within the split directory. |
| `objects.bbox` | Bounding boxes as `[x, y, width, height]` (pixels). |
| `objects.categories` | Integer class index per box (matches the class list below). |
| `objects.category_names` | Human class name per box. |
| `keypoints` | Keypoint instances (COCO-pose): object `category` plus a flat `[x, y, v, ...]` array aligned to `node_names`. |

## Use it

```python
from datasets import load_dataset

ds = load_dataset("pictograph/keypoint-detection-demo")
print(ds)
```

Prefer a full annotation editor, one-click fork, multi-format export, and one-click training? [Open this dataset on Pictograph](https://pictograph.io/datasets/pictograph/keypoint-detection-demo).

## Classes

Class index matches `objects.categories` in `metadata.jsonl`.

| # | Class | Annotations |
| ---: | :--- | ---: |
| 0 | head | 60 |
| 1 | torso | 60 |
| 2 | l_hand | 60 |
| 3 | r_hand | 60 |
| 4 | l_foot | 60 |
| 5 | r_foot | 60 |

## License

Released under [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0).

---

*Published from [Pictograph](https://pictograph.io/datasets/pictograph/keypoint-detection-demo) - annotate, train, and deploy from one API.*