# Hand Keypoints

Hand Keypoints: 26,677 images with keypoints for 22 classes, including hand, wrist, thumb cmc and thumb mcp. Based on Hand Keypoints (Ultralytics). Import it into a Pictograph workspace to export COCO or YOLO-Pose, or train a model on it. Published on Pictograph by Pictograph Research.

## Overview

- Type: public computer vision dataset
- Images: 26,677
- Classes: 22
- Annotation types: keypoint
- Tasks: Keypoint detection (https://pictograph.io/explore/task/keypoint-detection)
- Owner: Pictograph Research
- License: Creative Commons Attribution-NonCommercial-ShareAlike 4.0 (https://creativecommons.org/licenses/by-nc-sa/4.0/)
- Source: Hand Keypoints (Ultralytics) (https://docs.ultralytics.com/datasets/pose/hand-keypoints/), created by Ultralytics (Rion Dsilva). Credit the original authors when you use this data.
- Stars: 2
- Page: https://pictograph.io/datasets/pictograph-research/hand-keypoints
- Hugging Face: https://huggingface.co/datasets/pictograph/hand-keypoints
- Export formats: Pictograph JSON, Darwin V7, COCO, YOLO, YOLO-OBB, YOLO-Pose, DOTA, Pascal VOC, CVAT, Datumaro, LabelMe, CSV

## Classes

- hand
- wrist
- thumb_cmc
- thumb_mcp
- thumb_ip
- thumb_tip
- index_finger_mcp
- index_finger_pip
- index_finger_dip
- index_finger_tip
- middle_finger_mcp
- middle_finger_pip
- middle_finger_dip
- middle_finger_tip
- ring_finger_mcp
- ring_finger_pip
- ring_finger_dip
- ring_finger_tip
- pinky_mcp
- pinky_pip
- pinky_dip
- pinky_tip

## Models trained on this dataset

- PG-HandPose: https://pictograph.io/models/pictograph-research/pg-handpose

## About

# Hand Keypoints

> A public keypoint dataset of 26,677 images with 551,951 keypoints on the hand skeleton (21 keypoints).

**[Pictograph Research](/org/pictograph-research)** · [CC-BY-NC-SA-4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/) · Public · Updated 2026-11-05

## Overview

This dataset holds **26,677 images** labelled with keypoints on the hand skeleton (21 keypoints), one instance per object. The most common auto-detected tags are hand, person, working, face, top-down view, sitting. It is ready to import into a workspace, export in a dozen formats, or train a model on.

## At a glance

| Metric | Value |
| :--- | ---: |
| Images | 26,677 |
| Keypoints | 551,951 |
| Skeleton | hand, 21 keypoints |
| Annotation types | keypoint |
| Folders | 2 |
| Storage | Standard |
| Visibility | Public |

## Skeleton

Each object is one instance: its keypoints share an `instance_id` and are named for their joint. A keypoint that is labelled but hidden carries `occluded: true`. The joints are in this order in every export (a COCO keypoint array follows it).

| # | Keypoint | Connects to |
| ---: | :--- | :--- |
| 0 | wrist | thumb_cmc, index_finger_mcp, pinky_mcp |
| 1 | thumb_cmc | wrist, thumb_mcp |
| 2 | thumb_mcp | thumb_cmc, thumb_ip |
| 3 | thumb_ip | thumb_mcp, thumb_tip |
| 4 | thumb_tip | thumb_ip |
| 5 | index_finger_mcp | wrist, index_finger_pip, middle_finger_mcp |
| 6 | index_finger_pip | index_finger_mcp, index_finger_dip |
| 7 | index_finger_dip | index_finger_pip, index_finger_tip |
| 8 | index_finger_tip | index_finger_dip |
| 9 | middle_finger_mcp | index_finger_mcp, middle_finger_pip, ring_finger_mcp |
| 10 | middle_finger_pip | middle_finger_mcp, middle_finger_dip |
| 11 | middle_finger_dip | middle_finger_pip, middle_finger_tip |
| 12 | middle_finger_tip | middle_finger_dip |
| 13 | ring_finger_mcp | middle_finger_mcp, ring_finger_pip, pinky_mcp |
| 14 | ring_finger_pip | ring_finger_mcp, ring_finger_dip |
| 15 | ring_finger_dip | ring_finger_pip, ring_finger_tip |
| 16 | ring_finger_tip | ring_finger_dip |
| 17 | pinky_mcp | ring_finger_mcp, wrist, pinky_pip |
| 18 | pinky_pip | pinky_mcp, pinky_dip |
| 19 | pinky_dip | pinky_pip, pinky_tip |
| 20 | pinky_tip | pinky_dip |

## What's in these images

Tags auto-detected across the dataset, most common first.

| Tag | Category | Images |
| :--- | :--- | ---: |
| hand | Objects | 21,369 |
| person | Objects | 19,862 |
| working | Attributes | 11,908 |
| face | Objects | 9,280 |
| top-down view | Attributes | 9,033 |
| sitting | Attributes | 6,983 |
| glove | Objects | 6,794 |
| eye-level view | Attributes | 6,096 |
| playing | Attributes | 5,834 |
| high angle view | Attributes | 5,706 |
| wide angle | Attributes | 4,976 |
| speaker | Objects | 4,035 |
| close-up | Attributes | 3,723 |
| child | Objects | 3,141 |
| office | Scenes | 2,824 |

## Use this dataset

```python
from pictograph import Client, Dataset

client = Client()  # reads PICTOGRAPH_API_KEY
dataset: Dataset = client.datasets.get("Hand Keypoints")
print(dataset.image_count, dataset.annotation_count)
```

- Import it into your own workspace with one click from its page.
- Pull it with the [Pictograph SDK](https://pictograph.io/docs/api-reference/datasets) (shown above) or the CLI.
- [Export](https://pictograph.io/docs/export-conversion) to COCO, YOLO, Darwin V7, Pascal VOC, and more.
- [Train a model](https://pictograph.io/docs/guides/train) directly from an export.

## License

Released under [CC-BY-NC-SA-4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/).

## Source

The images and annotations come from [Hand Keypoints (Ultralytics)](https://docs.ultralytics.com/datasets/pose/hand-keypoints/), created by Ultralytics (Rion Dsilva) and released under [CC-BY-NC-SA-4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/). Please credit the original authors when you use this data.


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