RTS Tracker Prediction Score about pytracking HOT 1 CLOSED

The classification scores in DiMP can be smaller than 0 or larger than 1. Since we are not enforcing any limits here but rather compute a hinge like loss between the ground truth score map [0,1] and the predictions. Since we mainly care about localizing the object in the scene (locations > threshold) negative values or values above 1 are not an issue for our task. You can certainly squeeze these score values in the [0,1] interval by clipping or using a sigmoid. Depends what works for you. For the segmentation mask you get probability values for each location in the output. It is up to you to define a classification score based on the raw segmentation values that fits your need.

from pytracking.