Mercurial Hosting > traffic-intelligence

changeset 1226:d478d3122804

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change of bicycle to cyclist
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Wed, 12 Jul 2023 12:12:37 -0400
parents 202073959fb4
children 5654c9173548
files scripts/classify-objects.py scripts/manual-video-analysis.py scripts/polytracktopdtv.py scripts/train-object-classification.py trafficintelligence/moving.py
diffstat 5 files changed, 9 insertions(+), 9 deletions(-) [+]
line wrap: on
line diff
--- a/scripts/classify-objects.py	Mon Jul 03 10:33:20 2023 -0400
+++ b/scripts/classify-objects.py	Wed Jul 12 12:12:37 2023 -0400
@@ -39,7 +39,7 @@
 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)}
+                      'cyclist': lambda s: bicLogNorm.pdf(s)}
 
 if args.plotSpeedDistribution:
     import matplotlib.pyplot as plt
--- a/scripts/manual-video-analysis.py	Mon Jul 03 10:33:20 2023 -0400
+++ b/scripts/manual-video-analysis.py	Wed Jul 12 12:12:37 2023 -0400
@@ -29,7 +29,7 @@
                  'car',
                  'pedestrian',
                  'motorcycle',
-                 'bicycle',
+                 'cyclist',
                  'bus',
                  'truck']
 class UserConfiguration(object):
--- a/scripts/polytracktopdtv.py	Mon Jul 03 10:33:20 2023 -0400
+++ b/scripts/polytracktopdtv.py	Wed Jul 12 12:12:37 2023 -0400
@@ -25,7 +25,7 @@
           "1"  -> "car"
           "2"  -> "pedestrians"
           "3"  -> "motorcycle"
-          "4"  -> "bicycle"
+          "4"  -> "cyclist"
           "5"  -> "bus"
           "6"  -> "truck"
           ... and other type if the objects_type table is defined in SQLite'''
@@ -38,7 +38,7 @@
         typeDict["1"] = "car"
         typeDict["2"] = "pedestrians"
         typeDict["3"] = "motorcycle"
-        typeDict["4"] = "bicycle"
+        typeDict["4"] = "cyclist"
         typeDict["5"] = "bus"
         typeDict["6"] = "truck"
         
--- a/scripts/train-object-classification.py	Mon Jul 03 10:33:20 2023 -0400
+++ b/scripts/train-object-classification.py	Wed Jul 12 12:12:37 2023 -0400
@@ -23,7 +23,7 @@
 classifierParams = storage.ClassifierParameters(args.configFilename)
 
 imageDirectories = {'pedestrian': args.directoryName + "/Pedestrians/",
-                    'bicycle': args.directoryName + "/Cyclists/",
+                    'cyclist': args.directoryName + "/Cyclists/",
                     'car': args.directoryName + "/Vehicles/"}
 
 trainingSamplesPBV = {}
@@ -43,7 +43,7 @@
 	trainingSamplesBV[k], trainingLabelsBV[k] = trainingSamples, trainingLabels
     if k != 'car':
 	trainingSamplesPB[k], trainingLabelsPB[k] = trainingSamples, trainingLabels
-    if k != 'bicycle':
+    if k != 'cyclist':
 	trainingSamplesPV[k], trainingLabelsPV[k] = trainingSamples, trainingLabels
 
 # Training the Support Vector Machine
--- a/trafficintelligence/moving.py	Mon Jul 03 10:33:20 2023 -0400
+++ b/trafficintelligence/moving.py	Wed Jul 12 12:12:37 2023 -0400
@@ -1376,8 +1376,8 @@
                  'truck',
                  'automated']
 
-coco2UserTypes = {0: 2, 1: 4, 2: 1, 5: 5, 7: 6}
-cocoUserTypeNames = {0: 'person',
+coco2Types = {0: 2, 1: 4, 2: 1, 5: 5, 7: 6}
+cocoTypeNames = {0: 'person',
                      1: 'bicycle',
 	             2:	'car',
                      3: 'motorcycle',
@@ -2073,7 +2073,7 @@
                     self.classifyUserTypeHoGSVMAtInstant(images[t], t, homography, width, height, px, py, minNPixels, rescaleSize, orientations, pixelsPerCell, cellsPerBlock)
         # compute P(Speed|Class)
         if speedProbabilities is None or self.aggregatedSpeed < minSpeedEquiprobable: # equiprobable information from speed
-            userTypeProbabilities = {userType2Num['car']: 1., userType2Num['pedestrian']: 1., userType2Num['bicycle']: 1.}
+            userTypeProbabilities = {userType2Num['car']: 1., userType2Num['pedestrian']: 1., userType2Num['cyclist']: 1.}
         else:
             userTypeProbabilities = {userType2Num[userTypename]: speedProbabilities[userTypename](self.aggregatedSpeed) for userTypename in speedProbabilities}
         # compute P(Class|Appearance)