Mercurial Hosting > traffic-intelligence
comparison python/moving.py @ 608:078adacd72a4
moving.py integrating Mohamed's comments refactored
author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
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date | Wed, 26 Nov 2014 19:49:13 +0000 |
parents | 84690dfe5560 |
children | 0791b3b55b8f |
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607:84690dfe5560 | 608:078adacd72a4 |
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3 | 3 |
4 import utils | 4 import utils |
5 import cvutils | 5 import cvutils |
6 | 6 |
7 from math import sqrt | 7 from math import sqrt |
8 from numpy import median,percentile | 8 from numpy import median |
9 | 9 |
10 try: | 10 try: |
11 from shapely.geometry import Polygon, Point as shapelyPoint | 11 from shapely.geometry import Polygon, Point as shapelyPoint |
12 from shapely.prepared import prep | 12 from shapely.prepared import prep |
13 shapelyAvailable = True | 13 shapelyAvailable = True |
788 if count > lengthThreshold: | 788 if count > lengthThreshold: |
789 return True | 789 return True |
790 return False | 790 return False |
791 | 791 |
792 def wiggliness(self): | 792 def wiggliness(self): |
793 return self.computeCumulativeDistances()/float(Point.distanceNorm2(self.__getitem__(0),self.__getitem__(self.length()-1))) | 793 return self.getCumulativeDistance(self.length()-1)/float(Point.distanceNorm2(self.__getitem__(0),self.__getitem__(self.length()-1))) |
794 | 794 |
795 def getIntersections(self, p1, p2): | 795 def getIntersections(self, p1, p2): |
796 '''Returns a list of the indices at which the trajectory | 796 '''Returns a list of the indices at which the trajectory |
797 intersects with the segment of extremities p1 and p2 | 797 intersects with the segment of extremities p1 and p2 |
798 the list is empty if there is no crossing''' | 798 the list is empty if there is no crossing''' |
1154 relativePositions[(j,i)] = -relativePositions[(i,j)] | 1154 relativePositions[(j,i)] = -relativePositions[(i,j)] |
1155 | 1155 |
1156 ### | 1156 ### |
1157 # User Type Classification | 1157 # User Type Classification |
1158 ### | 1158 ### |
1159 def classifyUserTypeSpeedMotorized(self, threshold, percentileFactor=95, ignoreNInstantsAtEnds = 0): | 1159 def classifyUserTypeSpeedMotorized(self, threshold, aggregationFunc = median, ignoreNInstantsAtEnds = 0): |
1160 '''Classifies slow and fast road users | 1160 '''Classifies slow and fast road users |
1161 slow: non-motorized -> pedestrians | 1161 slow: non-motorized -> pedestrians |
1162 fast: motorized -> cars | 1162 fast: motorized -> cars |
1163 The percentile function is the same as the median if percentileFactor=50, the same as the minimum if percentileFactor=0 and the same as the maximum if percentileFactor=100.''' | 1163 |
1164 aggregationFunc can be any function that can be applied to a vector of speeds, including percentile: | |
1165 aggregationFunc = lambda x: percentile(x, percentileFactor) # where percentileFactor is 85 for 85th percentile''' | |
1164 if ignoreNInstantsAtEnds > 0: | 1166 if ignoreNInstantsAtEnds > 0: |
1165 speeds = self.getSpeeds()[ignoreNInstantsAtEnds:-ignoreNInstantsAtEnds] | 1167 speeds = self.getSpeeds()[ignoreNInstantsAtEnds:-ignoreNInstantsAtEnds] |
1166 else: | 1168 else: |
1167 speeds = self.getSpeeds() | 1169 speeds = self.getSpeeds() |
1168 if percentile(speeds,percentileFactor) >= threshold: | 1170 if aggregationFunc(speeds) >= threshold: |
1169 self.setUserType(userType2Num['car']) | 1171 self.setUserType(userType2Num['car']) |
1170 else: | 1172 else: |
1171 self.setUserType(userType2Num['pedestrian']) | 1173 self.setUserType(userType2Num['pedestrian']) |
1172 | 1174 |
1173 def classifyUserTypeSpeed(self, speedProbabilities, aggregationFunc = median): | 1175 def classifyUserTypeSpeed(self, speedProbabilities, aggregationFunc = median): |