Calculates the Levenshtein distance between a and b.

Computes the precision@k for the specified values of k

Reads ground truth file, checks if it is well formatted, and returns the ground truth instances and the activity classes. Paramete

Reads ground truth file, checks if it is well formatted, and returns the ground truth instances and the activity classes. Paramete

Reads prediction file, checks if it is well formatted, and returns the prediction instances. Parameters ----------

Reads prediction file, checks if it is well formatted, and returns the prediction instances. Parameters ----------

Sets the learning rate to the initial LR decayed by 10 every 30 epochs

Channel shuffle: [N,C,H,W] -> [N,g,C/g,H,W] -> [N,C/g,g,H,w] -> [N,C,H,W]

Channel shuffle: [N,C,H,W] -> [N,g,C/g,H,W] -> [N,C/g,g,H,w] -> [N,C,H,W]

Compute accuracy at k prediction between ground truth and predictions data frames. This code is greatly inspired by evaluation performed in Ka

Compute accuracy at k prediction between ground truth and predictions data frames. This code is greatly inspired by evaluation performed in Ka

Evaluates a prediction file. For the detection task we measure the interpolated mean average precision to measure the performance of a

Extract frames of .avi files. Parameters ---------- modalities: list of str, ["color", "depth", "duo_left", "duo_right", "duo_dispari