from_file#

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

Create a movement poses dataset from any supported file.

Parameters:
  • file_path (pathlib.Path or str) – Path to the file containing predicted poses. The file format must be among those supported by the from_dlc_file(), from_slp_file() or from_lp_file() functions. One of these these functions will be called internally, based on the value of source_software.

  • source_software ("DeepLabCut", "SLEAP" or "LightningPose") – The source software of the file.

  • 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_file(
...     "path/to/file.h5", source_software="DeepLabCut", fps=30
... )