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comparison python/events.py @ 628:977407c9f815

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corrected bugs in loading interactions (index shifted) and added functionalities to play/plot interactions
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Mon, 16 Feb 2015 11:58:51 +0100
parents 82e9f78a4714
children 0a5e89d6fc62
comparison
equal deleted inserted replaced
627:82e9f78a4714 628:977407c9f815
6 from numpy import arccos 6 from numpy import arccos
7 7
8 import multiprocessing 8 import multiprocessing
9 import itertools 9 import itertools
10 10
11 import moving, prediction, indicators, utils 11 import moving, prediction, indicators, utils, cvutils
12 __metaclass__ = type 12 __metaclass__ = type
13 13
14 def findRoute(prototypes,objects,i,j,noiseEntryNums,noiseExitNums,minSimilarity= 0.3, spatialThreshold=1.0, delta=180): 14 def findRoute(prototypes,objects,i,j,noiseEntryNums,noiseExitNums,minSimilarity= 0.3, spatialThreshold=1.0, delta=180):
15 if i[0] not in noiseEntryNums: 15 if i[0] not in noiseEntryNums:
16 prototypesRoutes= [ x for x in sorted(prototypes.keys()) if i[0]==x[0]] 16 prototypesRoutes= [ x for x in sorted(prototypes.keys()) if i[0]==x[0]]
59 'Distance', 59 'Distance',
60 'Minimum Distance', 60 'Minimum Distance',
61 'Velocity Angle', 61 'Velocity Angle',
62 'Speed Differential', 62 'Speed Differential',
63 'Collision Probability', 63 'Collision Probability',
64 'Time to Collision', 64 'Time to Collision', # 7
65 'Probability of Successful Evasive Action', 65 'Probability of Successful Evasive Action',
66 'predicted Post Encroachment Time'] 66 'predicted Post Encroachment Time']
67 67
68 indicatorNameToIndices = utils.inverseEnumeration(indicatorNames) 68 indicatorNameToIndices = utils.inverseEnumeration(indicatorNames)
69 69
106 self.interactionInterval = None 106 self.interactionInterval = None
107 107
108 def getRoadUserNumbers(self): 108 def getRoadUserNumbers(self):
109 return self.roadUserNumbers 109 return self.roadUserNumbers
110 110
111 def setRoadUsers(self, objects):
112 nums = list(self.getRoadUserNumbers())
113 if objects[nums[0]].getNum() == nums[0]:
114 self.roadUser1 = objects[nums[0]]
115 if objects[nums[1]].getNum() == nums[1]:
116 self.roadUser2 = objects[nums[1]]
117
118 i = 0
119 while i < len(objects) and self.roadUser2 == None:
120 if objects[i].getNum() in nums:
121 if self.roadUser1 == None:
122 self.roadUser1 = objects[i]
123 else:
124 self.roadUser2 = objects[i]
125 i += 1
126
111 def getIndicator(self, indicatorName): 127 def getIndicator(self, indicatorName):
112 return self.indicators.get(indicatorName, None) 128 return self.indicators.get(indicatorName, None)
113 129
114 def addIndicator(self, indicator): 130 def addIndicator(self, indicator):
115 if indicator: 131 if indicator:
116 self.indicators[indicator.name] = indicator 132 self.indicators[indicator.name] = indicator
133
134 def plot(self, options = '', withOrigin = False, timeStep = 1, withFeatures = False, **kwargs):
135 self.roadUser1.plot(options, withOrigin, timeStep, withFeatures, **kwargs)
136 self.roadUser2.plot(options, withOrigin, timeStep, withFeatures, **kwargs)
137
138 def plotOnWorldImage(self, nPixelsPerUnitDistance, options = '', withOrigin = False, timeStep = 1, **kwargs):
139 self.roadUser1.plotOnWorldImage(nPixelsPerUnitDistance, options, withOrigin, timeStep, **kwargs)
140 self.roadUser2.plotOnWorldImage(nPixelsPerUnitDistance, options, withOrigin, timeStep, **kwargs)
141
142 def play(self, videoFilename, homography = None, undistort = False, intrinsicCameraMatrix = None, distortionCoefficients = None, undistortedImageMultiplication = 1.):
143 if self.roadUser1 != None and self.roadUser2 != None:
144 cvutils.displayTrajectories(videoFilename, [self.roadUser1, self.roadUser2], homography = homography, firstFrameNum = self.getFirstInstant(), lastFrameNumArg = self.getLastInstant(), undistort = undistort, intrinsicCameraMatrix = intrinsicCameraMatrix, distortionCoefficients = distortionCoefficients, undistortedImageMultiplication = undistortedImageMultiplication)
145 else:
146 print('Please set the interaction road user attributes roadUser1 and roadUser1 through the method setRoadUsers')
117 147
118 def computeIndicators(self): 148 def computeIndicators(self):
119 '''Computes the collision course cosine only if the cosine is positive''' 149 '''Computes the collision course cosine only if the cosine is positive'''
120 collisionCourseDotProducts = {}#[0]*int(self.timeInterval.length()) 150 collisionCourseDotProducts = {}#[0]*int(self.timeInterval.length())
121 collisionCourseAngles = {} 151 collisionCourseAngles = {}
199 commonTimeInterval = objects[i].commonTimeInterval(others[j]) 229 commonTimeInterval = objects[i].commonTimeInterval(others[j])
200 if not commonTimeInterval.empty(): 230 if not commonTimeInterval.empty():
201 interactions.append(Interaction(num, commonTimeInterval, objects[i].num, others[j].num, objects[i], others[j])) 231 interactions.append(Interaction(num, commonTimeInterval, objects[i].num, others[j].num, objects[i], others[j]))
202 num += 1 232 num += 1
203 return interactions 233 return interactions
234
235 def findInteraction(interactions, roadUserNum1, roadUserNum2):
236 'Returns the right interaction in the set'
237 i=0
238 while i<len(interactions) and set([roadUserNum1, roadUserNum2]) != interactions[i].getRoadUserNumbers():
239 i+=1
240 if i<len(interactions):
241 return interactions[i]
242 else:
243 return None
204 244
205 def prototypeCluster(interactions, similarityMatrix, alignmentMatrix, indicatorName, minSimilarity): 245 def prototypeCluster(interactions, similarityMatrix, alignmentMatrix, indicatorName, minSimilarity):
206 '''Finds exemplar indicator time series for all interactions 246 '''Finds exemplar indicator time series for all interactions
207 Returns the prototype indices (in the interaction list) and the label of each indicator (interaction) 247 Returns the prototype indices (in the interaction list) and the label of each indicator (interaction)
208 248