Mercurial > hg > nsaunier > traffic-intelligence
comparison scripts/compute-clearmot.py @ 726:43ae3a1af290
added functionality to display matchings between ground truth and tracked objects
| author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
|---|---|
| date | Fri, 07 Aug 2015 13:07:53 -0400 |
| parents | e14e2101a5a9 |
| children | f8e0a8ea8402 |
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| 725:35bc5e30a53f | 726:43ae3a1af290 |
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| 1 #! /usr/bin/env python | 1 #! /usr/bin/env python |
| 2 | 2 |
| 3 import sys, argparse | 3 import sys, argparse |
| 4 from numpy import loadtxt | 4 from numpy import loadtxt |
| 5 import moving, storage | 5 from numpy.linalg import inv |
| 6 import moving, storage, cvutils | |
| 6 | 7 |
| 7 # TODO: need to trim objects to same mask ? | 8 # TODO: need to trim objects to same mask ? |
| 8 | 9 |
| 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: | 10 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: |
| 10 Keni, Bernardin, and Stiefelhagen Rainer. "Evaluating multiple object tracking performance: the CLEAR MOT metrics." EURASIP Journal on Image and Video Processing 2008 (2008) | 11 Keni, Bernardin, and Stiefelhagen Rainer. "Evaluating multiple object tracking performance: the CLEAR MOT metrics." EURASIP Journal on Image and Video Processing 2008 (2008) |
| 14 see examples on http://www.jpjodoin.com/urbantracker/dataset.html''', formatter_class=argparse.RawDescriptionHelpFormatter) | 15 see examples on http://www.jpjodoin.com/urbantracker/dataset.html''', formatter_class=argparse.RawDescriptionHelpFormatter) |
| 15 parser.add_argument('-d', dest = 'trackerDatabaseFilename', help = 'name of the Sqlite database containing the tracker output', required = True) | 16 parser.add_argument('-d', dest = 'trackerDatabaseFilename', help = 'name of the Sqlite database containing the tracker output', required = True) |
| 16 parser.add_argument('-g', dest = 'groundTruthDatabaseFilename', help = 'name of the Sqlite database containing the ground truth', required = True) | 17 parser.add_argument('-g', dest = 'groundTruthDatabaseFilename', help = 'name of the Sqlite database containing the ground truth', required = True) |
| 17 parser.add_argument('-o', dest = 'homographyFilename', help = 'name of the filename for the homography (if tracking was done using the homography)') | 18 parser.add_argument('-o', dest = 'homographyFilename', help = 'name of the filename for the homography (if tracking was done using the homography)') |
| 18 parser.add_argument('-m', dest = 'matchingDistance', help = 'matching distance between tracker and ground truth trajectories', required = True, type = float) | 19 parser.add_argument('-m', dest = 'matchingDistance', help = 'matching distance between tracker and ground truth trajectories', required = True, type = float) |
| 20 parser.add_argument('--mask', dest = 'maskFilename', help = 'filename of the mask file used to define the where objects were tracked') | |
| 19 parser.add_argument('-f', dest = 'firstInstant', help = 'first instant for measurement', required = True, type = int) | 21 parser.add_argument('-f', dest = 'firstInstant', help = 'first instant for measurement', required = True, type = int) |
| 20 parser.add_argument('-l', dest = 'lastInstant', help = 'last instant for measurement', required = True, type = int) | 22 parser.add_argument('-l', dest = 'lastInstant', help = 'last instant for measurement', required = True, type = int) |
| 21 parser.add_argument('--display', dest = 'display', help = 'display the ground truth to object matches (graphically)', action = 'store_true') | 23 parser.add_argument('--display', dest = 'display', help = 'display the ground truth to object matches (graphically)', action = 'store_true') |
| 24 parser.add_argument('-i', dest = 'videoFilename', help = 'name of the video file (for display)') | |
| 22 args = parser.parse_args() | 25 args = parser.parse_args() |
| 23 | 26 |
| 24 if args.homographyFilename is not None: | 27 if args.homographyFilename is not None: |
| 25 homography = loadtxt(args.homographyFilename) | 28 homography = loadtxt(args.homographyFilename) |
| 26 else: | 29 else: |
| 27 homography = None | 30 homography = None |
| 28 | 31 |
| 29 objects = storage.loadTrajectoriesFromSqlite(args.trackerDatabaseFilename, 'object') | 32 objects = storage.loadTrajectoriesFromSqlite(args.trackerDatabaseFilename, 'object') |
| 33 | |
| 34 if args.maskFilename is not None: | |
| 35 maskObjects = [] | |
| 36 from matplotlib.pyplot import imread | |
| 37 mask = imread(args.maskFilename) | |
| 38 if len(mask) > 1: | |
| 39 mask = mask[:,:,0] | |
| 40 for obj in objects: | |
| 41 maskObjects += obj.getObjectsInMask(mask, inv(homography), 2) # TODO add option to keep object if at least one feature in mask | |
| 42 objects = maskObjects | |
| 43 | |
| 30 annotations = storage.loadGroundTruthFromSqlite(args.groundTruthDatabaseFilename) | 44 annotations = storage.loadGroundTruthFromSqlite(args.groundTruthDatabaseFilename) |
| 31 for a in annotations: | 45 for a in annotations: |
| 32 a.computeCentroidTrajectory(homography) | 46 a.computeCentroidTrajectory(homography) |
| 33 | 47 |
| 34 if args.display: | 48 if args.display: |
| 41 print 'MOTA: {}'.format(mota) | 55 print 'MOTA: {}'.format(mota) |
| 42 print 'Number of missed objects.frames: {}'.format(mt) | 56 print 'Number of missed objects.frames: {}'.format(mt) |
| 43 print 'Number of mismatches: {}'.format(mme) | 57 print 'Number of mismatches: {}'.format(mme) |
| 44 print 'Number of false alarms.frames: {}'.format(fpt) | 58 print 'Number of false alarms.frames: {}'.format(fpt) |
| 45 if args.display: | 59 if args.display: |
| 46 print('Ground truth matches') | 60 cvutils.displayTrajectories(args.videoFilename, objects, {}, inv(homography), args.firstInstant, args.lastInstant, annotations = annotations, gtMatches = gtMatches, toMatches = toMatches)#, rescale = args.rescale, nFramesStep = args.nFramesStep, saveAllImages = args.saveAllImages, undistort = (undistort or args.undistort), intrinsicCameraMatrix = intrinsicCameraMatrix, distortionCoefficients = distortionCoefficients, undistortedImageMultiplication = undistortedImageMultiplication) |
| 47 print(gtMatches) | 61 |
| 48 print('Object matches') | 62 #print('Ground truth matches') |
| 49 print toMatches | 63 #print(gtMatches) |
| 64 #print('Object matches') | |
| 65 #rint toMatches |
