Mercurial Hosting > traffic-intelligence
view scripts/compute-clearmot.py @ 595:17b02c8054d0
added tests and corrected one bug
author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
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date | Sun, 07 Dec 2014 22:59:47 -0500 |
parents | 9e39cd95e017 |
children | 3058e00887bc |
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#! /usr/bin/env python import sys, argparse from numpy import loadtxt import moving, storage # TODO: need to trim objects to same mask ? parser = argparse.ArgumentParser(description='The program computes the CLEAR MOT metrics between ground truth and tracker output (in Polytrack format)', epilog='''CLEAR MOT metrics information: Keni, Bernardin, and Stiefelhagen Rainer. "Evaluating multiple object tracking performance: the CLEAR MOT metrics." EURASIP Journal on Image and Video Processing 2008 (2008) Polytrack format: JP. Jodoin\'s MSc thesis (in french) see examples on http://www.jpjodoin.com/urbantracker/dataset.html''', formatter_class=argparse.RawDescriptionHelpFormatter) parser.add_argument('-d', dest = 'trackerDatabaseFilename', help = 'name of the Sqlite database containing the tracker output', required = True) parser.add_argument('-g', dest = 'groundTruthDatabaseFilename', help = 'name of the Sqlite database containing the ground truth', required = True) parser.add_argument('-o', dest = 'homographyFilename', help = 'name of the filename for the homography (if tracking was done using the homography)') parser.add_argument('-m', dest = 'matchingDistance', help = 'matching distance between tracker and ground truth trajectories', required = True, type = float) parser.add_argument('-f', dest = 'firstInstant', help = 'first instant for measurement', required = True, type = int) parser.add_argument('-l', dest = 'lastInstant', help = 'last instant for measurement', required = True, type = int) args = parser.parse_args() if args.homographyFilename != None: homography = loadtxt(args.homographyFilename) else: homography = None objects = storage.loadTrajectoriesFromSqlite(args.trackerDatabaseFilename, 'object') annotations = storage.loadGroundTruthFromSqlite(args.groundTruthDatabaseFilename) for a in annotations: a.computeCentroidTrajectory(homography) motp, mota, mt, mme, fpt, gt = moving.computeClearMOT(annotations, objects, args.matchingDistance, args.firstInstant, args.lastInstant) print 'MOTP: {}'.format(motp) print 'MOTA: {}'.format(mota) print 'Number of missed objects.frames: {}'.format(mt) print 'Number of mismatches: {}'.format(mme) print 'Number of false alarms.frames: {}'.format(fpt)