Mercurial Hosting > traffic-intelligence
annotate python/events.py @ 992:2cd1ce245024
update to python 3
author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
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date | Fri, 13 Apr 2018 16:48:02 -0400 |
parents | 030b16ab4f64 |
children | 933670761a57 |
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1 #! /usr/bin/env python |
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2 '''Libraries for events |
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3 Interactions, pedestrian crossing...''' |
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4 |
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5 import moving, prediction, indicators, utils, cvutils, ml |
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6 from base import VideoFilenameAddable |
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7 |
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8 import numpy as np |
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9 |
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10 import multiprocessing |
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11 import itertools, logging |
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12 |
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13 |
613 | 14 def findRoute(prototypes,objects,i,j,noiseEntryNums,noiseExitNums,minSimilarity= 0.3, spatialThreshold=1.0, delta=180): |
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15 if i[0] not in noiseEntryNums: |
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16 prototypesRoutes= [ x for x in sorted(prototypes.keys()) if i[0]==x[0]] |
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17 elif i[1] not in noiseExitNums: |
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18 prototypesRoutes=[ x for x in sorted(prototypes.keys()) if i[1]==x[1]] |
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19 else: |
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20 prototypesRoutes=[x for x in sorted(prototypes.keys())] |
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21 routeSim={} |
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22 lcss = utils.LCSS(similarityFunc=lambda x,y: (distanceForLCSS(x,y) <= spatialThreshold),delta=delta) |
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23 for y in prototypesRoutes: |
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24 if y in prototypes.keys(): |
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25 prototypesIDs=prototypes[y] |
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26 similarity=[] |
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27 for x in prototypesIDs: |
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28 s=lcss.computeNormalized(objects[j].positions, objects[x].positions) |
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29 similarity.append(s) |
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30 routeSim[y]=max(similarity) |
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31 route=max(routeSim, key=routeSim.get) |
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32 if routeSim[route]>=minSimilarity: |
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33 return route |
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34 else: |
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35 return i |
613 | 36 |
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37 def getRoute(obj,prototypes,objects,noiseEntryNums,noiseExitNums,useDestination=True): |
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38 route=(obj.startRouteID,obj.endRouteID) |
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39 if useDestination: |
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40 if route not in prototypes.keys(): |
613 | 41 route= findRoute(prototypes,objects,route,obj.getNum(),noiseEntryNums,noiseExitNums) |
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42 return route |
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43 |
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44 class Interaction(moving.STObject, VideoFilenameAddable): |
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45 '''Class for an interaction between two road users |
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46 or a road user and an obstacle |
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47 |
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48 link to the moving objects |
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49 contains the indicators in a dictionary with the names as keys |
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50 ''' |
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51 |
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52 categories = {'Head On': 0, |
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53 'rearend': 1, |
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54 'side': 2, |
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55 'parallel': 3} |
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56 |
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57 indicatorNames = ['Collision Course Dot Product', |
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58 'Collision Course Angle', |
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59 'Distance', |
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60 'Minimum Distance', |
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61 'Velocity Angle', |
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62 'Speed Differential', |
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63 'Collision Probability', |
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64 'Time to Collision', # 7 |
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65 'Probability of Successful Evasive Action', |
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66 'predicted Post Encroachment Time', |
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67 'Post Encroachment Time'] |
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68 |
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69 indicatorNameToIndices = utils.inverseEnumeration(indicatorNames) |
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70 |
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71 indicatorShortNames = ['CCDP', |
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72 'CCA', |
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73 'Dist', |
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74 'MinDist', |
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75 'VA', |
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76 'SD', |
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77 'PoC', |
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78 'TTC', |
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79 'P(SEA)', |
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80 'pPET', |
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81 'PET'] |
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82 |
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83 indicatorUnits = ['', |
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84 'rad', |
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85 'm', |
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86 'm', |
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87 'rad', |
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88 'm/s', |
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89 '', |
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90 's', |
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91 '', |
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92 's', |
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93 's'] |
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94 |
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95 timeIndicators = ['Time to Collision', 'predicted Post Encroachment Time'] |
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96 |
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97 def __init__(self, num = None, timeInterval = None, roaduserNum1 = None, roaduserNum2 = None, roadUser1 = None, roadUser2 = None, categoryNum = None): |
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98 moving.STObject.__init__(self, num, timeInterval) |
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99 if timeInterval is None and roadUser1 is not None and roadUser2 is not None: |
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100 self.timeInterval = roadUser1.commonTimeInterval(roadUser2) |
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101 self.roadUser1 = roadUser1 |
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102 self.roadUser2 = roadUser2 |
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103 if roaduserNum1 is not None and roaduserNum2 is not None: |
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104 self.roadUserNumbers = set([roaduserNum1, roaduserNum2]) |
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105 elif roadUser1 is not None and roadUser2 is not None: |
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106 self.roadUserNumbers = set([roadUser1.getNum(), roadUser2.getNum()]) |
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107 else: |
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108 self.roadUserNumbers = None |
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109 self.categoryNum = categoryNum |
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110 self.indicators = {} |
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111 self.interactionInterval = None |
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112 # list for collison points and crossing zones |
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113 self.collisionPoints = None |
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114 self.crossingZones = None |
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115 |
340
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116 def getRoadUserNumbers(self): |
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117 return self.roadUserNumbers |
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118 |
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119 def setRoadUsers(self, objects): |
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120 nums = sorted(list(self.getRoadUserNumbers())) |
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121 if nums[0]<len(objects) and objects[nums[0]].getNum() == nums[0]: |
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122 self.roadUser1 = objects[nums[0]] |
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123 if nums[1]<len(objects) and objects[nums[1]].getNum() == nums[1]: |
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124 self.roadUser2 = objects[nums[1]] |
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125 |
694
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126 if self.roadUser1 is None or self.roadUser2 is None: |
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127 self.roadUser1 = None |
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128 self.roadUser2 = None |
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129 i = 0 |
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130 while i < len(objects) and self.roadUser2 is None: |
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131 if objects[i].getNum() in nums: |
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132 if self.roadUser1 is None: |
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133 self.roadUser1 = objects[i] |
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134 else: |
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135 self.roadUser2 = objects[i] |
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136 i += 1 |
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137 |
293
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138 def getIndicator(self, indicatorName): |
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139 return self.indicators.get(indicatorName, None) |
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140 |
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141 def addIndicator(self, indicator): |
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142 if indicator is not None: |
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143 self.indicators[indicator.name] = indicator |
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144 |
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145 def getIndicatorValueAtInstant(self, indicatorName, instant): |
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146 indicator = self.getIndicator(indicatorName) |
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147 if indicator is not None: |
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148 return indicator[instant] |
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149 else: |
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150 return None |
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151 |
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152 def getIndicatorValuesAtInstant(self, instant): |
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153 '''Returns list of indicator values at instant |
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154 as dict (with keys from indicators dict)''' |
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155 values = {} |
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156 for k, indicator in self.indicators.iteritems(): |
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157 values[k] = indicator[instant] |
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158 return values |
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159 |
628
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160 def plot(self, options = '', withOrigin = False, timeStep = 1, withFeatures = False, **kwargs): |
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161 self.roadUser1.plot(options, withOrigin, timeStep, withFeatures, **kwargs) |
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162 self.roadUser2.plot(options, withOrigin, timeStep, withFeatures, **kwargs) |
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163 |
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164 def plotOnWorldImage(self, nPixelsPerUnitDistance, options = '', withOrigin = False, timeStep = 1, **kwargs): |
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165 self.roadUser1.plotOnWorldImage(nPixelsPerUnitDistance, options, withOrigin, timeStep, **kwargs) |
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166 self.roadUser2.plotOnWorldImage(nPixelsPerUnitDistance, options, withOrigin, timeStep, **kwargs) |
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167 |
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168 def play(self, videoFilename, homography = None, undistort = False, intrinsicCameraMatrix = None, distortionCoefficients = None, undistortedImageMultiplication = 1., allUserInstants = False): |
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169 if self.roadUser1 is not None and self.roadUser2 is not None: |
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170 if allUserInstants: |
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171 firstFrameNum = min(self.roadUser1.getFirstInstant(), self.roadUser2.getFirstInstant()) |
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172 lastFrameNum = max(self.roadUser1.getLastInstant(), self.roadUser2.getLastInstant()) |
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173 else: |
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174 firstFrameNum = self.getFirstInstant() |
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175 lastFrameNum = self.getLastInstant() |
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176 cvutils.displayTrajectories(videoFilename, [self.roadUser1, self.roadUser2], homography = homography, firstFrameNum = firstFrameNum, lastFrameNumArg = lastFrameNum, undistort = undistort, intrinsicCameraMatrix = intrinsicCameraMatrix, distortionCoefficients = distortionCoefficients, undistortedImageMultiplication = undistortedImageMultiplication) |
628
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177 else: |
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178 print('Please set the interaction road user attributes roadUser1 and roadUser1 through the method setRoadUsers') |
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179 |
293
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180 def computeIndicators(self): |
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181 '''Computes the collision course cosine only if the cosine is positive''' |
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182 collisionCourseDotProducts = {}#[0]*int(self.timeInterval.length()) |
320
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183 collisionCourseAngles = {} |
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184 velocityAngles = {} |
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185 distances = {}#[0]*int(self.timeInterval.length()) |
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186 speedDifferentials = {} |
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187 interactionInstants = [] |
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188 for instant in self.timeInterval: |
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189 deltap = self.roadUser1.getPositionAtInstant(instant)-self.roadUser2.getPositionAtInstant(instant) |
325
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190 v1 = self.roadUser1.getVelocityAtInstant(instant) |
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191 v2 = self.roadUser2.getVelocityAtInstant(instant) |
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192 deltav = v2-v1 |
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193 velocityAngles[instant] = np.arccos(moving.Point.dot(v1, v2)/(v1.norm2()*v2.norm2())) |
299
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|
194 collisionCourseDotProducts[instant] = moving.Point.dot(deltap, deltav) |
317
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195 distances[instant] = deltap.norm2() |
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196 speedDifferentials[instant] = deltav.norm2() |
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197 if collisionCourseDotProducts[instant] > 0: |
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198 interactionInstants.append(instant) |
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199 if distances[instant] != 0 and speedDifferentials[instant] != 0: |
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200 collisionCourseAngles[instant] = np.arccos(collisionCourseDotProducts[instant]/(distances[instant]*speedDifferentials[instant])) |
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201 |
452
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202 if len(interactionInstants) >= 2: |
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203 self.interactionInterval = moving.TimeInterval(interactionInstants[0], interactionInstants[-1]) |
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204 else: |
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205 self.interactionInterval = moving.TimeInterval() |
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206 self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[0], collisionCourseDotProducts)) |
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207 self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[1], collisionCourseAngles)) |
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208 self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[2], distances, mostSevereIsMax = False)) |
387
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209 self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[4], velocityAngles)) |
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210 self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[5], speedDifferentials)) |
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211 |
317
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212 # if we have features, compute other indicators |
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213 if self.roadUser1.hasFeatures() and self.roadUser2.hasFeatures(): |
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214 minDistances={} |
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215 for instant in self.timeInterval: |
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216 minDistances[instant] = moving.MovingObject.minDistance(self.roadUser1, self.roadUser2, instant) |
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217 self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[3], minDistances, mostSevereIsMax = False)) |
317
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218 |
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219 def computeCrossingsCollisions(self, predictionParameters, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False, timeInterval = None): |
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220 '''Computes all crossing and collision points at each common instant for two road users. ''' |
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221 TTCs = {} |
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222 collisionProbabilities = {} |
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223 if timeInterval is not None: |
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224 commonTimeInterval = timeInterval |
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225 else: |
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226 commonTimeInterval = self.timeInterval |
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227 self.collisionPoints, crossingZones = predictionParameters.computeCrossingsCollisions(self.roadUser1, self.roadUser2, collisionDistanceThreshold, timeHorizon, computeCZ, debug, commonTimeInterval) |
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228 for i, cps in self.collisionPoints.iteritems(): |
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229 TTCs[i] = prediction.SafetyPoint.computeExpectedIndicator(cps) |
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230 collisionProbabilities[i] = sum([p.probability for p in cps]) |
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231 if len(TTCs) > 0: |
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232 self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[7], TTCs, mostSevereIsMax=False)) |
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233 self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[6], collisionProbabilities)) |
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234 |
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235 # crossing zones and pPET |
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236 if computeCZ: |
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237 self.crossingZones = crossingZones |
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238 pPETs = {} |
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239 for i, cz in self.crossingZones.iteritems(): |
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240 pPETs[i] = prediction.SafetyPoint.computeExpectedIndicator(cz) |
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241 self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[9], pPETs, mostSevereIsMax=False)) |
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242 # TODO add probability of collision, and probability of successful evasive action |
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243 |
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244 def computePET(self, collisionDistanceThreshold): |
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245 pet, t1, t2= moving.MovingObject.computePET(self.roadUser1, self.roadUser2, collisionDistanceThreshold) |
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246 if pet is not None: |
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247 self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[10], {min(t1, t2): pet}, mostSevereIsMax = False)) |
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248 |
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249 def setCollision(self, collision): |
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250 '''indicates if it is a collision: argument should be boolean''' |
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251 self.collision = collision |
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252 |
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253 def isCollision(self): |
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254 if hasattr(self, 'collision'): |
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255 return self.collision |
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256 else: |
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257 return None |
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258 |
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259 def getCollisionPoints(self): |
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260 return self.collisionPoints |
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261 |
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262 def getCrossingZones(self): |
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263 return self.crossingZones |
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264 |
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265 def createInteractions(objects, _others = None): |
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266 '''Create all interactions of two co-existing road users''' |
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267 if _others is not None: |
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268 others = _others |
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269 |
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270 interactions = [] |
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271 num = 0 |
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272 for i in xrange(len(objects)): |
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273 if _others is None: |
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274 others = objects[:i] |
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275 for j in xrange(len(others)): |
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276 commonTimeInterval = objects[i].commonTimeInterval(others[j]) |
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277 if not commonTimeInterval.empty(): |
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278 interactions.append(Interaction(num, commonTimeInterval, objects[i].num, others[j].num, objects[i], others[j])) |
293
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279 num += 1 |
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280 return interactions |
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281 |
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282 def findInteraction(interactions, roadUserNum1, roadUserNum2): |
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283 'Returns the right interaction in the set' |
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284 i=0 |
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285 while i<len(interactions) and set([roadUserNum1, roadUserNum2]) != interactions[i].getRoadUserNumbers(): |
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286 i+=1 |
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287 if i<len(interactions): |
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288 return interactions[i] |
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289 else: |
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290 return None |
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291 |
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292 def computeIndicators(interactions, computeMotionPrediction, computePET, predictionParameters, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False, timeInterval = None): |
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293 for inter in interactions: |
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294 print('processing interaction {}'.format(inter.getNum())) # logging.debug('processing interaction {}'.format(inter.getNum())) |
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295 inter.computeIndicators() |
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296 if computeMotionPrediction: |
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297 inter.computeCrossingsCollisions(predictionParameters, collisionDistanceThreshold, timeHorizon, computeCZ, debug, timeInterval) |
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298 if computePET: |
954 | 299 inter.computePET(collisionDistanceThreshold) |
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300 return interactions |
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301 |
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302 def aggregateSafetyPoints(interactions, pointType = 'collision'): |
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303 '''Put all collision points or crossing zones in a list for display''' |
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304 allPoints = [] |
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305 if pointType == 'collision': |
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306 for i in interactions: |
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307 for points in i.collisionPoints.values(): |
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308 allPoints += points |
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309 elif pointType == 'crossing': |
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310 for i in interactions: |
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311 for points in i.crossingZones.values(): |
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312 allPoints += points |
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313 else: |
705
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314 print('unknown type of point: '+pointType) |
632
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315 return allPoints |
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316 |
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317 def prototypeCluster(interactions, similarities, indicatorName, minSimilarity, similarityFunc = None, minClusterSize = None, randomInitialization = False): |
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318 return ml.prototypeCluster([inter.getIndicator(indicatorName) for inter in interactions], similarities, minSimilarity, similarityFunc, minClusterSize, randomInitialization) |
291
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319 |
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320 class Crossing(moving.STObject): |
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321 '''Class for the event of a street crossing |
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322 |
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323 TODO: detecter passage sur la chaussee |
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324 identifier origines et destination (ou uniquement chaussee dans FOV) |
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325 carac traversee |
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326 detecter proximite veh (retirer si trop similaire simultanement |
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327 carac interaction''' |
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328 |
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329 def __init__(self, roaduserNum = None, num = None, timeInterval = None): |
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330 moving.STObject.__init__(self, num, timeInterval) |
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331 self.roaduserNum = roaduserNum |
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332 |
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333 |
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334 |
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335 if __name__ == "__main__": |
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336 import doctest |
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337 import unittest |
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338 suite = doctest.DocFileSuite('tests/events.txt') |
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339 #suite = doctest.DocTestSuite() |
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340 unittest.TextTestRunner().run(suite) |
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341 |