--- a/scripts/compute-clearmot.py	Mon Aug 10 17:51:49 2015 -0400
+++ b/scripts/compute-clearmot.py	Mon Aug 10 17:52:19 2015 -0400
@@ -2,7 +2,8 @@
 
 import sys, argparse
 from numpy import loadtxt
-import moving, storage
+from numpy.linalg import inv
+import moving, storage, cvutils
 
 # TODO: need to trim objects to same mask ?
 
@@ -16,8 +17,11 @@
 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('--mask', dest = 'maskFilename', help = 'filename of the mask file used to define the where objects were tracked')
 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)
+parser.add_argument('--display', dest = 'display', help = 'display the ground truth to object matches (graphically)', action = 'store_true')
+parser.add_argument('-i', dest = 'videoFilename', help = 'name of the video file (for display)')
 args = parser.parse_args()
 
 if args.homographyFilename is not None:
@@ -26,14 +30,36 @@
     homography = None
 
 objects = storage.loadTrajectoriesFromSqlite(args.trackerDatabaseFilename, 'object')
+
+if args.maskFilename is not None:
+    maskObjects = []
+    from matplotlib.pyplot import imread
+    mask = imread(args.maskFilename)
+    if len(mask) > 1:
+        mask = mask[:,:,0]
+    for obj in objects:
+        maskObjects += obj.getObjectsInMask(mask, inv(homography), 2) # TODO add option to keep object if at least one feature in mask
+    objects = maskObjects    
+
 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)
+if args.display:
+    motp, mota, mt, mme, fpt, gt, gtMatches, toMatches = moving.computeClearMOT(annotations, objects, args.matchingDistance, args.firstInstant, args.lastInstant, True)
+else:
+    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)
+if args.display:
+    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)
+
+    #print('Ground truth matches')
+    #print(gtMatches)
+    #print('Object matches')
+    #rint toMatches