Add dataset card + metadata for Hand Keypoints

.gitattributes

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 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
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+train/metadata.jsonl filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+license: cc-by-nc-sa-4.0
+pretty_name: "Hand Keypoints"
+task_categories:
+  - keypoint-detection
+tags:
+  - computer-vision
+  - hand
+  - person
+  - face
+  - glove
+  - speaker
+  - child
+  - stop-sign
+  - ant
+  - watch
+  - key
+  - pose-estimation
+  - keypoints
+  - pictograph
+annotations_creators:
+  - machine-generated
+size_categories:
+  - 10K<n<100K
+source_datasets:
+  - original
+configs:
+  - config_name: default
+    data_files:
+      - split: train
+        path: "train/**/*"
+      - split: validation
+        path: "valid/**/*"
+---
+
+[![Hand Keypoints - annotated computer-vision dataset on Pictograph](https://storage.googleapis.com/pictograph-assets/hf/heroes/hand-keypoints.png)](https://pictograph.io/datasets/pictograph-research/hand-keypoints)
+
+[![Open in](https://img.shields.io/badge/Open_in-Pictograph-2c5aa0)](https://pictograph.io/datasets/pictograph-research/hand-keypoints) ![task](https://img.shields.io/badge/task-keypoint_detection-1a4480) ![images](https://img.shields.io/badge/images-26,677-555) [![license](https://img.shields.io/badge/license-cc--by--nc--sa--4.0-3cb44b)](https://creativecommons.org/licenses/by-nc-sa/4.0/)
+
+**[View on Pictograph](https://pictograph.io/datasets/pictograph-research/hand-keypoints)** · [Pictograph Research](https://pictograph.io/org/pictograph-research) · [Creative Commons Attribution-NonCommercial-ShareAlike 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/)
+
+## About
+
+**Hand Keypoints** is a computer-vision dataset from [Hand Keypoints (Ultralytics)](https://docs.ultralytics.com/datasets/pose/hand-keypoints/), hosted on [Pictograph](https://pictograph.io/datasets/pictograph-research/hand-keypoints). 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:
+
+```python
+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](https://pictograph.io/datasets/pictograph-research/hand-keypoints).
+
+## 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):
+
+```python
+{
+  "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](https://creativecommons.org/licenses/by-nc-sa/4.0/). When you use this data, please credit **Ultralytics (Rion Dsilva)**.
+
+## Source and attribution
+
+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 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.
+
+---
+
+*Published from [Pictograph](https://pictograph.io/datasets/pictograph-research/hand-keypoints) - annotate, train, and deploy from one API.*
+

train/metadata.jsonl

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