The COCO keypoint format: 17 keypoints, order, and skeleton.
Everything you need to read or write COCO person-keypoint annotations: the exact keypoint order, the official skeleton pairs, what the visibility flags mean, and worked JSON examples. Bookmark-grade; no scrolling through a tutorial to find the list.
Keypoint order
The keypoints array is 0-based, but the skeleton pairs reference 1-based ids — the most common off-by-one in pose tooling. Both are listed. “Left” always means the subject’s left, which appears on the viewer’s right in a front-facing image.
| Array index (0-based) | Skeleton id (1-based) | Name | Side |
|---|---|---|---|
| 0 | 1 | nose | — |
| 1 | 2 | left_eye | left |
| 2 | 3 | right_eye | right |
| 3 | 4 | left_ear | left |
| 4 | 5 | right_ear | right |
| 5 | 6 | left_shoulder | left |
| 6 | 7 | right_shoulder | right |
| 7 | 8 | left_elbow | left |
| 8 | 9 | right_elbow | right |
| 9 | 10 | left_wrist | left |
| 10 | 11 | right_wrist | right |
| 11 | 12 | left_hip | left |
| 12 | 13 | right_hip | right |
| 13 | 14 | left_knee | left |
| 14 | 15 | right_knee | right |
| 15 | 16 | left_ankle | left |
| 16 | 17 | right_ankle | right |
Numbered with 1-based skeleton ids
The official 19 skeleton pairs
Each pair connects two keypoints by their 1-based ids. This is the canonical list from the COCO annotations, verbatim:
"skeleton": [ [16,14], [14,12], [17,15], [15,13], [12,13], [6,12], [7,13], [6,7], [6,8], [7,9], [8,10], [9,11], [2,3], [1,2], [1,3], [2,4], [3,5], [4,6], [5,7] ]
What v = 0, 1, 2 mean
Keypoints are stored as flat [x1, y1, v1, x2, y2, v2, …] triplets — 51 numbers for a person. The third value of each triplet is the visibility flag:
v = 0
Not labeled
x and y are 0; the point was not annotated at all.
v = 1
Labeled, not visible
The point has coordinates but is occluded (e.g. a hip under a coat).
v = 2
Labeled and visible
The point is annotated and visible in the image.
num_keypoints on the annotation counts the labeled points — those with v > 0.
The category and annotation JSON
The category declares the names and skeleton; each annotation carries the triplets. A minimal, valid pair:
// categories[]
{
"id": 1,
"name": "person",
"supercategory": "person",
"keypoints": [
"nose", "left_eye", "right_eye",
"left_ear", "right_ear",
"left_shoulder", "right_shoulder",
"left_elbow", "right_elbow",
"left_wrist", "right_wrist",
"left_hip", "right_hip",
"left_knee", "right_knee",
"left_ankle", "right_ankle"
],
"skeleton": [
[16,14],[14,12],[17,15],[15,13],
[12,13],[6,12],[7,13],[6,7],
[6,8],[7,9],[8,10],[9,11],
[2,3],[1,2],[1,3],[2,4],
[3,5],[4,6],[5,7]
]
}// annotations[]
{
"id": 42,
"image_id": 7,
"category_id": 1,
"num_keypoints": 3,
"keypoints": [
412, 143, 2, // nose: visible
431, 128, 2, // left_eye: visible
398, 129, 1, // right_eye: occluded
0, 0, 0, // left_ear: not labeled
// … one [x, y, v] triplet per
// keypoint, 17 in total
],
"bbox": [372, 94, 118, 340],
"iscrowd": 0,
"area": 40120
}Skip the conversion scripts.
DataTorch speaks this format natively: define the keypoints and skeleton on a label, annotate point-by-point in the browser with a live skeleton overlay, and import or export COCO keypoints — visibility flags included.
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