Downloads sample data and processes it. Stores all important paths for easy access.

Splits the skeleton data into separate arrays for each data category using the provided model info. Examples categories are body, left_hand,

Splits the skeleton data into separate arrays for each data category using the provided model info. Examples categories are body, left_hand,

Run the full test suite on python versions 3.10, 3.11, and 3.12.

test that the `2d detection` process worked correctly by checking that there is an `.npy` file containing the 2d data in the `output_data_folder`

test that the `3d detection` process worked correctly by checking that there is an `.npy` file containing the 3d data in the `output_data_folder`

test that the `3d detection` process worked correctly by checking: 1. Dimensions of the raw skeleton numpy array are correct 2. Dimension

Test if all the videos in this folder have precisely the same number of frames

Rotate points by given rotation vectors and translate. Rodrigues' rotation formula is used.

Given an CxNxPx2 array, this returns an Nx3 array of points by triangulating all possible points and picking the ones with best reproj

Given an CxNx2 array, this returns an Nx3 array of points, where N is the number of points and C is the number of cameras

Given an CxNx2 array, this returns an Nx3 array of points, where N is the number of points and C is the number of cameras

Triangulates 3D points with progressive outlier rejection. Performs triangulation using all valid cameras, and if reprojection error

Save the most recent recording path to a toml file

Initialize DataFrameManager with the given recording_folder_path. Args: recording_folder_path (Union[Path, str]): path t

Initialize the CalibrationGuideLink widget. Args: text: The link text to display. Defaults to "📚 Calibration Guide"