# HG changeset patch
# User Nicolas Saunier <nicolas.saunier@polymtl.ca>
# Date 1689182468 14400
# Node ID 5654c91735485c56c2799ef812ca57b52ff9e682
# Parent  eb3936809ea5d5896f719ad7b5e89dc1fdca7bb5# Parent  d478d3122804d83006e6fc2cdb23df363568569c
merged (bicycle)

diff -r eb3936809ea5 -r 5654c9173548 scripts/classify-objects.py
--- a/scripts/classify-objects.py	Wed Jul 12 13:14:09 2023 -0400
+++ b/scripts/classify-objects.py	Wed Jul 12 13:21:08 2023 -0400
@@ -37,9 +37,9 @@
 pedNorm = norm(classifierParams.meanPedestrianSpeed, classifierParams.stdPedestrianSpeed)
 # numpy lognorm shape, loc, scale: shape for numpy is scale (std of the normal) and scale for numpy is exp(location) (loc=mean of the normal)
 bicLogNorm = lognorm(classifierParams.scaleCyclistSpeed, loc = 0., scale = np.exp(classifierParams.locationCyclistSpeed))
-speedProbabilities = {'car': lambda s: carNorm.pdf(s),
-                      'pedestrian': lambda s: pedNorm.pdf(s), 
-                      'bicycle': lambda s: bicLogNorm.pdf(s)}
+speedProbabilities = {moving.userTypeNames[1]: lambda s: carNorm.pdf(s),
+                      moving.userTypeNames[2]: lambda s: pedNorm.pdf(s), 
+                      moving.userTypeNames[4]: lambda s: bicLogNorm.pdf(s)}
 
 if args.plotSpeedDistribution:
     import matplotlib.pyplot as plt
diff -r eb3936809ea5 -r 5654c9173548 scripts/manual-video-analysis.py
diff -r eb3936809ea5 -r 5654c9173548 scripts/polytracktopdtv.py
diff -r eb3936809ea5 -r 5654c9173548 scripts/train-object-classification.py
--- a/scripts/train-object-classification.py	Wed Jul 12 13:14:09 2023 -0400
+++ b/scripts/train-object-classification.py	Wed Jul 12 13:21:08 2023 -0400
@@ -22,9 +22,9 @@
 args = parser.parse_args()
 classifierParams = storage.ClassifierParameters(args.configFilename)
 
-imageDirectories = {'pedestrian': args.directoryName + "/Pedestrians/",
-                    'bicycle': args.directoryName + "/Cyclists/",
-                    'car': args.directoryName + "/Vehicles/"}
+imageDirectories = {moving.userTypeNames[2]: args.directoryName + "/Pedestrians/",
+                    moving.userTypeNames[4]: args.directoryName + "/Cyclists/",
+                    moving.userTypeNames[1]: args.directoryName + "/Vehicles/"}
 
 trainingSamplesPBV = {}
 trainingLabelsPBV = {}
@@ -39,11 +39,11 @@
     print('Loading {} samples'.format(k))
     trainingSamples, trainingLabels = cvutils.createHOGTrainingSet(v, moving.userType2Num[k], classifierParams.hogRescaleSize, classifierParams.hogNOrientations, classifierParams.hogNPixelsPerCell, classifierParams.hogBlockNorm, classifierParams.hogNCellsPerBlock)
     trainingSamplesPBV[k], trainingLabelsPBV[k] = trainingSamples, trainingLabels
-    if k != 'pedestrian':
+    if k != moving.userTypeNames[2]:
 	trainingSamplesBV[k], trainingLabelsBV[k] = trainingSamples, trainingLabels
-    if k != 'car':
+    if k != moving.userTypeNames[1]:
 	trainingSamplesPB[k], trainingLabelsPB[k] = trainingSamples, trainingLabels
-    if k != 'bicycle':
+    if k != moving.userTypeNames[4]:
 	trainingSamplesPV[k], trainingLabelsPV[k] = trainingSamples, trainingLabels
 
 # Training the Support Vector Machine
diff -r eb3936809ea5 -r 5654c9173548 trafficintelligence/moving.py
--- a/trafficintelligence/moving.py	Wed Jul 12 13:14:09 2023 -0400
+++ b/trafficintelligence/moving.py	Wed Jul 12 13:21:08 2023 -0400
@@ -1376,14 +1376,14 @@
                  'truck',
                  'automated']
 
-coco2UserTypes = {0: 2, 1: 4, 2: 1, 5: 5, 7: 6}
-cocoUserTypeNames = {0: 'person',
-                     1: 'bicycle',
-	             2:	'car',
-                     3: 'motorcycle',
-                     5: 'bus',
-                     6: 'train',
-                     7: 'truck'}
+coco2Types = {0: 2, 1: 4, 2: 1, 5: 5, 7: 6}
+cocoTypeNames = {0: 'person',
+                 1: 'bicycle',
+	         2: 'car',
+                 3: 'motorcycle',
+                 5: 'bus',
+                 6: 'train',
+                 7: 'truck'}
 
 userType2Num = utils.inverseEnumeration(userTypeNames)