Keypoint-moseq

Latest version: v0.5.0

Safety actively analyzes 702150 Python packages for vulnerabilities to keep your Python projects secure.

Scan your dependencies

Page 2 of 6

0.4.5

Added FreiPose loader and function for saving keypoints.

Loading keypoints from FreiPose

To load keypoints output by FreiPose, use:

coordinates, confidences, bodyparts = kpms.load_keypoints(filepath_pattern, "freipose")

Note that `confidences` is set uniformly to 1, since the FreiPose scores range from <0 to >1 and therefore can't be used for modeling. Also `bodyparts` is None because these are not stored in the FreiPose output.

Initializing a config from FreiPose

Its also possible to setup a kpms config using a FreiPose config:

kpms.setup_project('test', freipose_config="path/to/skeleton_config.cfg.json")

The FreiPose config will be used to populate "bodyparts", "use_bodyparts" and "skeleton" in the kpms config. In some cases, the FreiPose skeleton may use a pair of keypoints to define one end of a limb. In FreiPose, this is used to indicate a limb midpoint. Since the same option is not available in kpms, the first bodypart in the pair is selected as the end of the limb.

Export keypoints

A new convenience function has been added for exporting keypoints:

kpms.save_keypoints(save_dir, coordinates, confidences=confidences, bodyparts=bodyparts)


One csv file is saved for each recording in `coordinates`. Each row in the csv corresponds to one frame and the columns are named

"BODYPART1_x", "BODYPART1_y", "BODYPART1_conf", "BODYPART2_x", ...

Columns with confidence scores are ommitted if `confidences` is not provided. Besides confidences, there can be 2 or 3 columns for each bodypart, depending on whether the keypoints are 2D or 3D.

0.4.4

Added support for loading DLC files with unique bodyparts

0.4.3

Fixed bug in calibration widget

0.4.2

Bugfixes
- Remove "linestyle" keyword from analysis code
- Pad states before unbatch rather than after - prevents error for sequences with length < nlags

0.4.1

0.4.0

Important note!

Because of the change in jax-moseq version (see below), models trained before this update will no longer be compatible with the modeling code. Therefore, if you plan to update and have previous keypoint-MoSeq projects, we recommend installing the new code version in a separate conda environment so that you can still interact with existing projects.

Changes

- Updated jax-moseq dependency to version 0.2.0

- Added option for location-aware modeling (see docs for details)

- Added a new section docs section and associated code for model comparison, selection and averaging

- Added option to load data from facemap

- Updated kappa scan example code to include both autoregressive-only and full-model modeling steps

- Fixed conda environment file for Windows GPU install (thanks !)

- Added support for 3D data in statistical analysis pipeline (thanks )

- Bugfixes

Page 2 of 6

© 2025 Safety CLI Cybersecurity Inc. All Rights Reserved.