The library is used to detect posture of the human body. It is
represented by a array of 17 joint points. Joint points are arranged in the
following
order.
0: 'nose', 1: 'left_eye', 2: 'right_eye', 3: 'left_ear', 4: 'right_ear',
5: 'left_shoulder', 6: 'right_shoulder', 7: 'left_elbow', 8: 'right_elbow',
9: 'left_wrist', 10 : 'right_wrist', 11: 'left_hip', 12: 'right_hip',
13: 'left_knee', 14: 'right_knee', 15: 'left_ankle', 16: 'right_ankle'This network can only detect for one person and the input of this
network is 192x192.
Note: Use a square picture
for input. To detect pictures with other size ratios, use a network with the
same input size ratio.
The following image shows the result of Movenet detection.
Figure 1. Movenet Detection Example
The following table lists the Movenet detection models supported by the Vitis AI Library.
| No | Model Name | Framework |
|---|---|---|
| 1 | movenet_ntd_pt | PyTorch |