Return dataset statistics dictionary with images and instances counts per split per class To run in parent directory: export PYTHONPATH="$PWD/yol

Notes: We use this function to output jsons whenever possible. like the time that we exit the while loop of opencv.

Invalidate infeasible entries in cost matrix based on the state distributions obtained by Kalman filtering. Parameters ---------- kf

Returns all the registered actions by callback hook Args: hook The name of the hook to check, defaults to all

An intersection over union distance metric. Parameters ---------- tracks : List[deep_sort.track.Track] A list of tracks. dete

Returns True if this track is tentative (unconfirmed).

Returns true if ext exists in allowed_exts for video files. Args: ext: Returns:

Run matching cascade. Parameters ---------- distance_metric : Callable[List[Track], List[Detection], List[int], List[int]) -> ndarray

Suppress overlapping detections. Original code from [1]_ has been adapted to include confidence score. .. [1] http://www.pyimagesearch.com/2

Run Kalman filter prediction step. Parameters ---------- mean : ndarray The 8 dimensional mean vector of the obje

Propagate track state distributions one time step forward. This function should be called once every time step, before `update`.