from_lp_file#

movement.io.load_poses.from_lp_file(file_path, fps=None)[source]#

Create a movement poses dataset from a LightningPose file.

Parameters:

  • file_path (pathlib.Path or str) – Path to the file containing the predicted poses, in .csv format.

  • fps (float, optional) – The number of frames per second in the video. If None (default), the time coordinates will be in frame numbers.

Returns:

movement dataset containing the pose tracks, confidence scores, and associated metadata.

Return type:

xarray.Dataset

Examples

>>> from movement.io import load_poses
>>> ds = load_poses.from_lp_file("path/to/file.csv", fps=30)