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Models supported by LSTM
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David PAGNON 2024-01-23 09:58:02 +01:00 committed by GitHub
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@ -435,8 +435,15 @@ Output:\
> _**Use the Stanford LSTM model to estimate the position of 47 virtual markers.**_\
> _**N.B.:**_ You can visualize your resulting filtered 3D coordinates with my (experimental) [Maya-Mocap tool](https://github.com/davidpagnon/Maya-Mocap)
_**Note that results are surprisingly not necessarily better after marker augmentation.**_\
_**Note that inverse kinematic results are not necessarily better after marker augmentation.**_
**Make sure that `participant_height` is correct in your `Config.toml` file.** `participant_mass` is mostly optional.\
Only works with models estimating at least the following keypoints (e.g., not COCO):
``` python
["Neck", "RShoulder", "LShoulder", "RHip", "LHip", "RKnee", "LKnee",
"RAnkle", "LAnkle", "RHeel", "LHeel", "RSmallToe", "LSmallToe",
"RBigToe", "LBigToe", "RElbow", "LElbow", "RWrist", "LWrist"]
```
Will not work properly if missing values are not interpolated (i.e., if there are Nan value in the .trc file).