annotate scripts/compute-clearmot.py @ 594:9e39cd95e017

first implementation of CLEAR MOT (needs formal tests)
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Sun, 07 Dec 2014 01:32:36 -0500
parents e2a873e08568
children 17b02c8054d0
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1 #! /usr/bin/env python
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2
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3 import sys, argparse
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4 from numpy import loadtxt
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5 import moving, storage
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7 # TODO: need to trim objects to same mask ?
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9 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:
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10 Keni, Bernardin, and Stiefelhagen Rainer. "Evaluating multiple object tracking performance: the CLEAR MOT metrics." EURASIP Journal on Image and Video Processing 2008 (2008)
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11
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12 Polytrack format:
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13 JP. Jodoin\'s MSc thesis (in french)
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14 see examples on http://www.jpjodoin.com/urbantracker/dataset.html''', formatter_class=argparse.RawDescriptionHelpFormatter)
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15 parser.add_argument('-d', dest = 'trackerDatabaseFilename', help = 'name of the Sqlite database containing the tracker output', required = True)
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16 parser.add_argument('-g', dest = 'groundTruthDatabaseFilename', help = 'name of the Sqlite database containing the ground truth', required = True)
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17 parser.add_argument('-o', dest = 'homographyFilename', help = 'name of the filename for the homography (if tracking was done using the homography)')
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18 parser.add_argument('-m', dest = 'matchingDistance', help = 'matching distance between tracker and ground truth trajectories', required = True, type = float)
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19 parser.add_argument('-f', dest = 'firstInstant', help = 'first instant for measurement', required = True, type = int)
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20 parser.add_argument('-l', dest = 'lastInstant', help = 'last instant for measurement', required = True, type = int)
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21 args = parser.parse_args()
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23 if args.homographyFilename != None:
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24 homography = loadtxt(args.homographyFilename)
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25 else:
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26 homography = None
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28 objects = storage.loadTrajectoriesFromSqlite(args.trackerDatabaseFilename, 'object')
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29 annotations = storage.loadGroundTruthFromSqlite(args.groundTruthDatabaseFilename)
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30 for a in annotations:
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31 a.computeCentroidTrajectory(homography)
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33 motp, mota, mt, mme, fpt, gt = moving.computeClearMOT(objects, annotations, args.matchingDistance, args.firstInstant, args.lastInstant)
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35 print 'MOTP: {}'.format(motp)
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36 print 'MOTA: {}'.format(mota)
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37 print 'Number of missed objects.frames: {}'.format(mt)
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38 print 'Number of mismatches: {}'.format(mme)
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39 print 'Number of false alarms.frames: {}'.format(fpt)