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annotate scripts/compute-clearmot.py @ 1152:dceaca7e1c97 dev

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old work on stabilization for drones
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Mon, 24 Aug 2020 15:34:39 -0400
parents 3aa6102ccc12
children f6790357f53b
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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 from numpy.linalg import inv
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6 import moving, storage, cvutils
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7
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8 # TODO: need to trim objects to same mask ?
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9
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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:
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11 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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12
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13 Polytrack format:
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14 JP. Jodoin\'s MSc thesis (in french)
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15 see examples on http://www.jpjodoin.com/urbantracker/dataset.html''', formatter_class=argparse.RawDescriptionHelpFormatter)
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16 parser.add_argument('-d', dest = 'trackerDatabaseFilename', help = 'name of the Sqlite database containing the tracker output', required = True)
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17 parser.add_argument('-g', dest = 'groundTruthDatabaseFilename', help = 'name of the Sqlite database containing the ground truth', required = True)
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18 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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19 parser.add_argument('-m', dest = 'matchingDistance', help = 'matching distance between tracker and ground truth trajectories', required = True, type = float)
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20 parser.add_argument('--mask', dest = 'maskFilename', help = 'filename of the mask file used to define the where objects were tracked')
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21 parser.add_argument('-f', dest = 'firstInstant', help = 'first instant for measurement', required = True, type = int)
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22 parser.add_argument('-l', dest = 'lastInstant', help = 'last instant for measurement', required = True, type = int)
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23 parser.add_argument('--offset', dest = 'nFramesOffsetAnnotations', help = 'number of frames to offset the ground truth annotations', type = int)
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24 parser.add_argument('--displayOffset', dest = 'nFramesOffsetDisplay', help = 'number of frames to offset annotations and objects for display', type = int)
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25 parser.add_argument('--display', dest = 'display', help = 'display the ground truth to object matches (graphically)', action = 'store_true')
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26 parser.add_argument('-i', dest = 'videoFilename', help = 'name of the video file (for display)')
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27 args = parser.parse_args()
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28
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29 if args.homographyFilename is not None:
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30 homography = loadtxt(args.homographyFilename)
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31 else:
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32 homography = None
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33
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34 objects = storage.loadTrajectoriesFromSqlite(args.trackerDatabaseFilename, 'object')
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35
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36 if args.maskFilename is not None:
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37 maskObjects = []
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38 from matplotlib.pyplot import imread
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39 mask = imread(args.maskFilename)
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40 if len(mask) > 1:
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41 mask = mask[:,:,0]
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42 for obj in objects:
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43 maskObjects += obj.getObjectsInMask(mask, inv(homography), 2) # TODO add option to keep object if at least one feature in mask
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44 objects = maskObjects
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45
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46 annotations = storage.loadBBMovingObjectsFromSqlite(args.groundTruthDatabaseFilename)
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47 for a in annotations:
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48 a.computeCentroidTrajectory(homography)
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49
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50 if args.nFramesOffsetAnnotations is not None:
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51 for a in annotations:
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52 a.shiftTimeInterval(args.nFramesOffsetAnnotations)
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53
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54 if args.display:
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55 motp, mota, mt, mme, fpt, gt, gtMatches, toMatches = moving.computeClearMOT(annotations, objects, args.matchingDistance, args.firstInstant, args.lastInstant, True)
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56 else:
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57 motp, mota, mt, mme, fpt, gt = moving.computeClearMOT(annotations, objects, args.matchingDistance, args.firstInstant, args.lastInstant)
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59
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60 print 'MOTP: {}'.format(motp)
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61 print 'MOTA: {}'.format(mota)
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62 print 'Number of missed objects.frames: {}'.format(mt)
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63 print 'Number of mismatches: {}'.format(mme)
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64 print 'Number of false alarms.frames: {}'.format(fpt)
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65
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66 def shiftMatches(matches, offset):
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67 shifted = {}
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68 for k in matches:
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69 shifted[k] = {t+offset:v for t, v in matches[k].iteritems()}
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70 return shifted
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72 if args.display:
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73 if args.nFramesOffsetDisplay is not None:
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74 firstInstant = args.firstInstant+args.nFramesOffsetDisplay
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75 lastInstant = args.lastInstant+args.nFramesOffsetDisplay
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76 for a in annotations:
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77 a.shiftTimeInterval(args.nFramesOffsetDisplay)
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78 for o in objects:
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79 o.shiftTimeInterval(args.nFramesOffsetDisplay)
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80 gtMatches = shiftMatches(gtMatches, args.nFramesOffsetDisplay)
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81 toMatches = shiftMatches(toMatches, args.nFramesOffsetDisplay)
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82 cvutils.displayTrajectories(args.videoFilename, objects, {}, inv(homography), firstInstant, 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)
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83
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84 #print('Ground truth matches')
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85 #print(gtMatches)
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86 #print('Object matches')
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87 #rint toMatches