pictograph/hand-keypoints

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About

Hand Keypoints is a computer-vision dataset from Hand Keypoints (Ultralytics), hosted on Pictograph. The most common detected objects are hand, person, face, glove, speaker, child. On Pictograph you can browse every annotated image, import 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	26,677
Keypoints	551,951
Skeleton	hand, 21 keypoints
Annotation types	keypoint
Splits	train, validation

Quick start

Load it in one line with the datasets library, then read each record's COCO-pose keypoint instances:

from datasets import load_dataset

ds = load_dataset("pictograph/hand-keypoints", split="train")
example = ds[0]
image = example["image"]                  # a PIL image

# one entry per object instance (COCO-pose)
for inst in example["keypoints"]:
    names = inst["node_names"]            # e.g. ["wrist", "thumb_cmc", "thumb_mcp", ...]
    flat = inst["keypoints"]              # [x, y, v, x, y, v, ...] aligned to names
    joints = {
        names[i]: (flat[3 * i], flat[3 * i + 1], flat[3 * i + 2])
        for i in range(len(names))
    }
    print(inst["category"], joints)       # v: 0 unlabelled, 1 occluded, 2 visible

Prefer a full annotation editor, one-click import, multi-format export, and one-click training? Open this dataset on Pictograph.

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 (the skeleton below); v is 0 unlabelled, 1 occluded, 2 visible. Each instance's box in objects encloses its keypoints.

Data instance

One record (each keypoints entry is one object instance; keypoints is a flat [x, y, v, ...] array of 21 keypoints aligned to node_names, v: 0 unlabelled, 1 occluded, 2 visible):

{
  "image": <PIL.Image (RGB)>,
  "objects": {"bbox": [[172.0, 96.0, 140.0, 310.0]], "categories": [0], "category_names": ["hand"]},
  "keypoints": [
    {
      "category": "hand", "category_id": 0, "num_keypoints": 21,
      "node_names": ["wrist", "thumb_cmc", "thumb_mcp", ...],
      "keypoints": [201.0, 148.0, 2.0, 188.0, 146.0, 1.0, 0.0, 0.0, 0.0, ...]
    }
  ]
}

Classes

Class index matches objects.categories and each keypoint instance's category_id.

#	Class	Keypoints
0	hand	21

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

License

Released under Creative Commons Attribution-NonCommercial-ShareAlike 4.0. When you use this data, please credit Ultralytics (Rion Dsilva).

Source and attribution

The images and annotations come from Hand Keypoints (Ultralytics), created by Ultralytics (Rion Dsilva) and released under Creative Commons Attribution-NonCommercial-ShareAlike 4.0. We are grateful to the original authors. If you use this data, please cite the original source above.

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