2dhandpose

2D hand keypoint estimation weights for egocentric video, trained by Build AI.

• model.safetensors — 0.43B-parameter ViT pose backbone (Sapiens-compatible architecture) with a 42-channel heatmap head.
• Input: monocular RGB frames. Output: one heatmap per hand keypoint.

Keypoint order (42 channels)

Channels 0–20 are the right hand, 21–41 the left hand. Within each hand: five fingers (thumb, index, middle, ring, pinky), each as 4 points ordered fingertip → base (MCP), followed by the wrist.

channel	keypoint
0–3	right thumb, tip → MCP
4–7	right index, tip → MCP
8–11	right middle, tip → MCP
12–15	right ring, tip → MCP
16–19	right pinky, tip → MCP
20	right wrist
21–24	left thumb, tip → MCP
25–28	left index, tip → MCP
29–32	left middle, tip → MCP
33–36	left ring, tip → MCP
37–40	left pinky, tip → MCP
41	left wrist

Skeleton: within each finger connect the 4 points in order; connect the wrist to each finger's MCP (channels 3, 7, 11, 15, 19 for right; 24, 28, 32, 36, 40 for left).

Loading

The state dict follows the open-source Sapiens pose layout (backbone.* ViT + decode_head.* deconv/conv heatmap head) with num_keypoints = 42; any loader compatible with that code can consume it directly.