smidm / clearmetrics

Python implementation of CLEAR multi object tracking (MOT) evaluation metrics

Deprecation

⚠️ Deprecated in favor of the great https://github.com/cheind/py-motmetrics!

Python implementation of CLEAR multi object tracking evaluation metrics

• works for arbitrary dimensional data
• described in: Keni, Bernardin, and Stiefelhagen Rainer. "Evaluating multiple object tracking performance: the CLEAR MOT metrics." EURASIP Journal on Image and Video Processing 2008 (2008).

Requirements

$ pip install numpy munkres  

or

$ pip install -r requirements.txt

Usage

import clearmetrics

# 1d ground truth and measurements for 3 frames
groundtruth = {0: [2, 3, 6],
               1: [3, 2, 6],
               2: [4, 0, 6]
               }

measurements = {
    0: [1, 3, 8],
    1: [2, 3, None, 6],
    2: [0, 4, None, 6, 8]
}
clear = clearmetrics.ClearMetrics(groundtruth, measurements, 1.5)
clear.match_sequence()
evaluation = [clear.get_mota(),
              clear.get_motp(),
              clear.get_fn_count(),
              clear.get_fp_count(),
              clear.get_mismatches_count(),
              clear.get_object_count(),
              clear.get_matches_count()]

Extended sample is in example.py.