Mercurial Hosting > traffic-intelligence
changeset 616:0791b3b55b8f
Merge
| author | MohamedGomaa |
|---|---|
| date | Wed, 10 Dec 2014 14:18:30 -0500 |
| parents | 0954aaf28231 (diff) 34111db7cecb (current diff) |
| children | e7f6ca76b7db |
| files | python/moving.py |
| diffstat | 9 files changed, 362 insertions(+), 160 deletions(-) [+] |
line wrap: on
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--- a/python/events.py Wed Dec 03 18:56:49 2014 +0000 +++ b/python/events.py Wed Dec 10 14:18:30 2014 -0500 @@ -8,12 +8,39 @@ import multiprocessing import itertools -import sys import moving, prediction, indicators, utils -sys.path.append("D:/behaviourAnalysis/libs") -import trajLearning __metaclass__ = type +def findRoute(prototypes,objects,i,j,noiseEntryNums,noiseExitNums,minSimilarity= 0.3, spatialThreshold=1.0, delta=180): + if i[0] not in noiseEntryNums: + prototypesRoutes= [ x for x in sorted(prototypes.keys()) if i[0]==x[0]] + elif i[1] not in noiseExitNums: + prototypesRoutes=[ x for x in sorted(prototypes.keys()) if i[1]==x[1]] + else: + prototypesRoutes=[x for x in sorted(prototypes.keys())] + routeSim={} + lcss = utils.LCSS(similarityFunc=lambda x,y: (distanceForLCSS(x,y) <= spatialThreshold),delta=delta) + for y in prototypesRoutes: + if y in prototypes.keys(): + prototypesIDs=prototypes[y] + similarity=[] + for x in prototypesIDs: + s=lcss.computeNormalized(objects[j].positions, objects[x].positions) + similarity.append(s) + routeSim[y]=max(similarity) + route=max(routeSim, key=routeSim.get) + if routeSim[route]>=minSimilarity: + return route + else: + return i + +def getRoute(obj,prototypes,objects,noiseEntryNums,noiseExitNums,useDestination=True): + route=(obj.startRouteID,obj.endRouteID) + if useDestination: + if route not in prototypes.keys(): + route= findRoute(prototypes,objects,route,obj.getNum(),noiseEntryNums,noiseExitNums) + return route + class Interaction(moving.STObject): '''Class for an interaction between two road users or a road user and an obstacle @@ -126,17 +153,20 @@ minDistance[instant] = moving.MovingObject.minDistance(self.roadUser1, self.roadUser2, instant) self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[3], minDistance)) - def computeCrossingsCollisions(self, predictionParameters, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False, timeInterval = None, nProcesses = 1): + def computeCrossingsCollisions(self, predictionParameters, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False, timeInterval = None, nProcesses = 1,usePrototypes=True,route1= (-1,-1),route2=(-1,-1),prototypes={},secondStepPrototypes={},nMatching={},objects=[],noiseEntryNums=[],noiseExitNums=[],minSimilarity=0.1,mostMatched=None,useDestination=True,useSpeedPrototype=True,acceptPartialLength=30, step=1): '''Computes all crossing and collision points at each common instant for two road users. ''' self.collisionPoints={} self.crossingZones={} TTCs = {} + if usePrototypes: + route1= getRoute(self.roadUser1,prototypes,objects,noiseEntryNums,noiseExitNums,useDestination) + route2= getRoute(self.roadUser2,prototypes,objects,noiseEntryNums,noiseExitNums,useDestination) if timeInterval: commonTimeInterval = timeInterval else: commonTimeInterval = self.timeInterval - self.collisionPoints, self.crossingZones = prediction.computeCrossingsCollisions(predictionParameters, self.roadUser1, self.roadUser2, collisionDistanceThreshold, timeHorizon, computeCZ, debug, commonTimeInterval, nProcesses) + self.collisionPoints, self.crossingZones = prediction.computeCrossingsCollisions(predictionParameters, self.roadUser1, self.roadUser2, collisionDistanceThreshold, timeHorizon, computeCZ, debug, commonTimeInterval, nProcesses,usePrototypes,route1,route2,prototypes,secondStepPrototypes,nMatching,objects,noiseEntryNums,noiseExitNums,minSimilarity,mostMatched,useDestination,useSpeedPrototype,acceptPartialLength, step) for i, cp in self.collisionPoints.iteritems(): TTCs[i] = prediction.SafetyPoint.computeExpectedIndicator(cp) # add probability of collision, and probability of successful evasive action @@ -144,70 +174,8 @@ if computeCZ: pPETs = {} - for i in list(commonTimeInterval)[:-1]: - if len(self.crossingZones[i]) > 0: - pPETs[i] = prediction.SafetyPoint.computeExpectedIndicator(self.crossingZones[i]) - self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[9], pPETs)) - - def computeCrosssingCollisionsPrototypeAtInstant(self, instant,route1,route2,predictionParameters, collisionDistanceThreshold, timeHorizon, prototypes,secondStepPrototypes,nMatching,objects,noiseEntryNums,noiseExitNums,minSimilarity=0.1,mostMatched=None, computeCZ = False, debug = False,useDestination=True,useSpeedPrototype=True): - inter1=moving.Interval(self.roadUser1.timeInterval.first,instant) - inter2=moving.Interval(self.roadUser2.timeInterval.first,instant) - partialObjPositions1= self.roadUser1.getObjectInTimeInterval(inter1).positions - partialObjPositions2= self.roadUser2.getObjectInTimeInterval(inter2).positions - if useSpeedPrototype: - prototypeTrajectories1=trajLearning.findPrototypesSpeed(prototypes,secondStepPrototypes,nMatching,objects,route1,partialObjPositions1,noiseEntryNums,noiseExitNums,minSimilarity,mostMatched,useDestination) - prototypeTrajectories2=trajLearning.findPrototypesSpeed(prototypes,secondStepPrototypes,nMatching,objects,route2,partialObjPositions2,noiseEntryNums,noiseExitNums,minSimilarity,mostMatched,useDestination) - else: - prototypeTrajectories1=trajLearning.findPrototypes(prototypes,nMatching,objects,route1,partialObjPositions1,noiseEntryNums,noiseExitNums,minSimilarity,mostMatched) - prototypeTrajectories2=trajLearning.findPrototypes(prototypes,nMatching,objects,route2,partialObjPositions2,noiseEntryNums,noiseExitNums,minSimilarity,mostMatched) - if prototypeTrajectories1=={}: - print self.roadUser1.num, 'is abnormal at instant', str(instant) - return [],[] - elif prototypeTrajectories2=={}: - print self.roadUser2.num, 'is abnormal at instant', str(instant) - return [],[] - else: - currentInstant,collisionPoints, crossingZones = predictionParameters.computeCrossingsCollisionsAtInstant(instant, self.roadUser1, self.roadUser2, collisionDistanceThreshold, timeHorizon, computeCZ, debug,prototypeTrajectories1,prototypeTrajectories2) - return collisionPoints,crossingZones - - def computeCrossingsCollisionsPrototype2stages(self, predictionParameters, collisionDistanceThreshold, timeHorizon, prototypes,secondStepPrototypes,nMatching,objects,noiseEntryNums,noiseExitNums,step=10,minSimilarity=0.1,mostMatched=None, computeCZ = False, debug = False, timeInterval = None,acceptPartialLength=30,useDestination=True,useSpeedPrototype=True): - '''Computes all crossing and collision points at each common instant for two road users. ''' - self.collisionPoints={} - self.crossingZones={} - TTCs = {} - route1=(self.roadUser1.startRouteID,self.roadUser1.endRouteID) - route2=(self.roadUser2.startRouteID,self.roadUser2.endRouteID) - if useDestination: - if route1 not in prototypes.keys(): - route1= trajLearning.findRoute(prototypes,objects,route1,self.roadUser1.num,noiseEntryNums,noiseExitNums) - if route2 not in prototypes.keys(): - route2= trajLearning.findRoute(prototypes,objects,route2,self.roadUser2.num,noiseEntryNums,noiseExitNums) - - if timeInterval: - commonTimeInterval = timeInterval - else: - commonTimeInterval = self.timeInterval - reCompute=False - for i in xrange(commonTimeInterval.first,commonTimeInterval.last,step): # incremental calculation of CP,CZ to save time - if i-self.roadUser1.timeInterval.first >= acceptPartialLength and i-self.roadUser2.timeInterval.first >= acceptPartialLength: - self.collisionPoints[i], self.crossingZones[i] = self.computeCrosssingCollisionsPrototypeAtInstant(i,route1,route2,predictionParameters, collisionDistanceThreshold, timeHorizon, prototypes,secondStepPrototypes,nMatching,objects,noiseEntryNums,noiseExitNums,minSimilarity,mostMatched, computeCZ, debug,useDestination,useSpeedPrototype) - if len(self.collisionPoints[i]) >0 or len(self.crossingZones[i])>0: - reCompute=True - break - if reCompute: - for i in list(commonTimeInterval)[:-1]: # do not look at the 1 last position/velocities, often with errors - if i-self.roadUser1.timeInterval.first >= acceptPartialLength and i-self.roadUser2.timeInterval.first >= acceptPartialLength: - self.collisionPoints[i], self.crossingZones[i] = self.computeCrosssingCollisionsPrototypeAtInstant(i,route1,route2,predictionParameters, collisionDistanceThreshold, timeHorizon, prototypes,secondStepPrototypes,nMatching,objects,noiseEntryNums,noiseExitNums,minSimilarity,mostMatched, computeCZ, debug,useDestination,useSpeedPrototype) - if len(self.collisionPoints[i]) > 0: - TTCs[i] = prediction.SafetyPoint.computeExpectedIndicator(self.collisionPoints[i]) - # add probability of collision, and probability of successful evasive action - self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[7], TTCs)) - - if computeCZ: - pPETs = {} - for i in list(commonTimeInterval)[:-1]: - if i in self.crossingZones.keys() and len(self.crossingZones[i]) > 0: - pPETs[i] = prediction.SafetyPoint.computeExpectedIndicator(self.crossingZones[i]) + for i, cz in self.crossingZones.iteritems(): + pPETs[i] = prediction.SafetyPoint.computeExpectedIndicator(cz) self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[9], pPETs)) def addVideoFilename(self,videoFilename):
--- a/python/moving.py Wed Dec 03 18:56:49 2014 +0000 +++ b/python/moving.py Wed Dec 10 14:18:30 2014 -0500 @@ -924,7 +924,8 @@ class MovingObject(STObject): '''Class for moving objects: a spatio-temporal object - with a trajectory and a geometry (constant volume over time) and a usertype (e.g. road user) coded as a number (see + with a trajectory and a geometry (constant volume over time) + and a usertype (e.g. road user) coded as a number (see userTypeNames) ''' def __init__(self, num = None, timeInterval = None, positions = None, velocities = None, geometry = None, userType = userType2Num['unknown']): @@ -1279,6 +1280,24 @@ return Point.cosine(movingObject1.getPositionAtInstant(instant)-movingObject2.getPositionAtInstant(instant), #deltap movingObject2.getVelocityAtInstant(instant)-movingObject1.getVelocityAtInstant(instant)) #deltav + +################## +# Annotations +################## + +class BBAnnotation(MovingObject): + '''Class for : a series of ground truth annotations using bounding boxes + Its center is the center of the containing shape + ''' + + def __init__(self, num = None, timeInterval = None, topPositions = None, bottomPositions = None, userType = userType2Num['unknown']): + super(BBAnnotation, self).__init__(num, timeInterval, Trajectory(), userType = userType) + self.topPositions = topPositions.getPositions() + self.bottomPositions = bottomPositions.getPositions() + for i in xrange(int(topPositions.length())): + self.positions.addPosition((topPositions.getPositionAt(i) + bottomPositions.getPositionAt(i)).multiply(0.5)) + + def plotRoadUsers(objects, colors): '''Colors is a PlottingPropertyValues instance''' from matplotlib.pyplot import figure, axis
--- a/python/objectsmoothing.py Wed Dec 03 18:56:49 2014 +0000 +++ b/python/objectsmoothing.py Wed Dec 10 14:18:30 2014 -0500 @@ -13,13 +13,6 @@ dist[f]= moving.Point.distanceNorm2(feat.getPositionAtInstant(t-1),f.getPositionAtInstant(t)) return min(dist, key=dist.get) # = utils.argmaxDict(dist) -def FeatureList(obj,minLengthParam=0.7): - featureList=[] - for i in obj.features: - if i.length>= minLengthParam*obj.length(): - featureList.append(i.num) - return featureList - def getFeatures(obj,features,featureID): #longestFeature = utils.argmaxDict({f:f.length() for i,f in enumerate(obj.features)}) t1,t3 = features[featureID].getFirstInstant(), features[featureID].getLastInstant() @@ -80,7 +73,7 @@ p1= object.getPositionAtInstant(i) p2= object.getPositionAtInstant(i+1) velocities[i]=p2-p1 - velocities[object.timeInterval.last]= velocities[object.timeInterval.last-1] # duplicate last point + velocities[object.getLastInstant()]= velocities[object.getLastInstant()-1] # duplicate last point if smoothing: velX= [velocities[y].aslist()[0] for y in sorted(velocities.keys())] velY= [velocities[y].aslist()[1] for y in sorted(velocities.keys())] @@ -121,7 +114,7 @@ t+= jerk[i]* jerk[i] return t -def getObject(obj,features,featureID,newNum,smoothing=False,halfWidth=3,create=False): +def smoothObjectTrajectory(obj,features,featureID,newNum,smoothing=False,halfWidth=3,create=False): results=[] bearing={} if create: @@ -131,7 +124,7 @@ for t in feature.getTimeInterval(): p1= feature.getPositionAtInstant(t) p2= obj.getPositionAtInstant(t) - if t!=feature.timeInterval.last: + if t!=feature.getLastInstant(): p3= feature.getPositionAtInstant(t+1) else: p1= feature.getPositionAtInstant(t-1) @@ -174,24 +167,22 @@ d1= translated[halfWidth]- feature.positions[halfWidth] d2= translated[-halfWidth-1]- feature.positions[-halfWidth-1] for i in xrange(halfWidth): - p1.x=feature.positions.__getitem__(i).x+d1.x - p2.x= feature.positions.__getitem__(-i-1).x+d2.x - p1.y=feature.positions.__getitem__(i).y+d1.y - p2.y= feature.positions.__getitem__(-i-1).y+d2.y + p1= feature.getPositionAt(i)+d1 + p2= feature.getPositionAt(-i-1)+d2 translated.setPosition(i,p1) translated.setPosition(-i-1,p2) - newObj= moving.MovingObject(newNum,timeInterval=feature.timeInterval,positions=translated) + newObj= moving.MovingObject(newNum,timeInterval=feature.getTimeInterval(),positions=translated) return newObj def smoothObjectTrajectory(obj,features,newNum,minLengthParam=0.7,smoothing=False,plotResults=True,halfWidth=3,computeVelocities=True,optimize=True,create=False): - featureList=FeatureList(obj,minLengthParam=minLengthParam) + featureList=[i.num for i in obj.features if i.length() >= minLengthParam*obj.length()] if featureList==[]: featureList.append(longestFeature(obj)) create=True objs=[] for featureID in featureList: - objTMP=getObject(obj,features,featureID,newNum,smoothing=smoothing,halfWidth=halfWidth,create=create) + objTMP=smoothObjectTrajectory(obj,features,featureID,newNum,smoothing=smoothing,halfWidth=halfWidth,create=create) objs.append(objTMP) newTranslated = moving.Trajectory() newInterval=[]
--- a/python/poly-utils.py Wed Dec 03 18:56:49 2014 +0000 +++ b/python/poly-utils.py Wed Dec 10 14:18:30 2014 -0500 @@ -6,26 +6,18 @@ import numpy as np __metaclass__ = type +from indicators import SeverityIndicator -# inputs variables -#dirname= 'G:/0-phdstart/Code/trial/indicatorsNew/' -#extension= '-indicatorsNew.csv' -#indicatorsNames= {1:'Distance',2:'Cosine',3:'collision Course Angle',4:'Velocity Cosine',5:'Velocity Angle',6:'Speed Differential',7:'Collision Probability',8:'Severity Index',9:'TTC'} -''' min Distance case''' -dirname= 'G:/0-phdstart/Code/trial/minDistanceIndicator/' -extension= '-minDistanceInd.csv' -indicatorsNames= {1:'minDistance'} -def loadNewInteractions(videoFilename,interactionType, roaduserNum1,roaduserNum2, selectedIndicators=[]): +def loadNewInteractions(videoFilename,interactionType,dirname, extension, indicatorsNames, roaduserNum1,roaduserNum2, selectedIndicators=[]): '''Loads interactions from the POLY traffic event format''' from events import Interaction - from indicators import SeverityIndicator - #filename= dirname + videoFilename + extension - filename= dirname + interactionType+ '-' + videoFilename + extension # case of min distance todo: change the saving format to be matched with all outputs + filename= dirname + videoFilename + extension + #filename= dirname + interactionType+ '-' + videoFilename + extension # case of min distance todo: change the saving format to be matched with all outputs file = utils.openCheck(filename) if (not file): return [] - interactions = [] + #interactions = [] interactionNum = 0 data= np.loadtxt(filename) indicatorFrameNums= data[:,0] @@ -43,7 +35,92 @@ values[t] = [data[i,index] for index in selectedIndicators] inter.addIndicator(SeverityIndicator('selectedIndicators', values)) - interactions.append(inter) + #interactions.append(inter) file.close() - return interactions + #return interactions + return inter + +# Plotting results + +frameRate = 15. + +# To run in directory that contains the directories that contain the results (Miss-xx and Incident-xx) +#dirname = '/home/nicolas/Research/Data/kentucky-db/' + +interactingRoadUsers = {'Miss/0404052336': [(0,3)] # 0,2 and 1 vs 3 + #, + #'Incident/0306022035': [(1,3)] + #, + #'Miss/0208030956': [(4,5),(5,7)] + } + + +def getIndicatorName(filename, withUnit = False): + if withUnit: + unit = ' (s)' + else: + unit = '' + if 'collision-point' in filename: + return 'TTC'+unit + elif 'crossing' in filename: + return 'pPET'+unit + elif 'probability' in filename: + return 'P(UEA)' + +def getMethodName(fileprefix): + if fileprefix == 'constant-velocity': + return 'Con. Vel.' + elif fileprefix == 'normal-adaptation': + return 'Norm. Ad.' + elif fileprefix == 'point-set': + return 'Pos. Set' + elif fileprefix == 'evasive-action': + return 'Ev. Act.' + elif fileprefix == 'point-set-evasive-action': + return 'Pos. Set' + +indicator2TimeIdx = {'TTC':2,'pPET':2, 'P(UEA)':3} +def getDataAtInstant(data, i): + return data[data[:,2] == i] + +def getPointsAtInstant(data, i): + return getDataAtInstant(i)[3:5] + +def getIndicator(data, roadUserNumbers, indicatorName): + if data.ndim ==1: + data.shape = (1,data.shape[0]) + + # find the order for the roadUserNumbers + uniqueObj1 = np.unique(data[:,0]) + uniqueObj2 = np.unique(data[:,1]) + found = False + if roadUserNumbers[0] in uniqueObj1 and roadUserNumbers[1] in uniqueObj2: + objNum1 = roadUserNumbers[0] + objNum2 = roadUserNumbers[1] + found = True + if roadUserNumbers[1] in uniqueObj1 and roadUserNumbers[0] in uniqueObj2: + objNum1 = roadUserNumbers[1] + objNum2 = roadUserNumbers[0] + found = True + + # get subset of data for road user numbers + if found: + roadUserData = data[np.logical_and(data[:,0] == objNum1, data[:,1] == objNum2),:] + if roadUserData.size > 0: + time = np.unique(roadUserData[:,indicator2TimeIdx[indicatorName]]) + values = {} + if indicatorName == 'P(UEA)': + tmp = roadUserData[:,4] + for k,v in zip(time, tmp): + values[k]=v + return SeverityIndicator(indicatorName, values, mostSevereIsMax = False, maxValue = 1.), roadUserData + else: + for i in xrange(time[0],time[-1]+1): + try: + tmp = getDataAtInstant(roadUserData, i) + values[i] = np.sum(tmp[:,5]*tmp[:,6])/np.sum(tmp[:,5])/frameRate + except IOError: + values[i] = np.inf + return SeverityIndicator(indicatorName, values, mostSevereIsMax = False), roadUserData + return None, None \ No newline at end of file
--- a/python/prediction.py Wed Dec 03 18:56:49 2014 +0000 +++ b/python/prediction.py Wed Dec 10 14:18:30 2014 -0500 @@ -5,6 +5,7 @@ import math import random import numpy as np +from utils import LCSS class PredictedTrajectory: '''Class for predicted trajectories with lazy evaluation @@ -166,14 +167,94 @@ savefig('predicted-trajectories-t-{0}.png'.format(currentInstant)) close() -def computeCrossingsCollisionsAtInstant(predictionParams,currentInstant, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False,prototypeTrajectories1=None,prototypeTrajectories2=None): +def calculateProbability(nMatching,similarity,objects): + sumFrequencies=sum([nMatching[p] for p in similarity.keys()]) + prototypeProbability={} + for i in similarity.keys(): + prototypeProbability[i]= similarity[i] * float(nMatching[i])/sumFrequencies + sumProbabilities= sum([prototypeProbability[p] for p in prototypeProbability.keys()]) + probabilities={} + for i in prototypeProbability.keys(): + probabilities[objects[i]]= float(prototypeProbability[i])/sumProbabilities + return probabilities + +def findPrototypes(prototypes,nMatching,objects,route,partialObjPositions,noiseEntryNums,noiseExitNums,minSimilarity=0.1,mostMatched=None,spatialThreshold=1.0, delta=180): + ''' behaviour prediction first step''' + if route[0] not in noiseEntryNums: + prototypesRoutes= [ x for x in sorted(prototypes.keys()) if route[0]==x[0]] + elif route[1] not in noiseExitNums: + prototypesRoutes=[ x for x in sorted(prototypes.keys()) if route[1]==x[1]] + else: + prototypesRoutes=[x for x in sorted(prototypes.keys())] + lcss = LCSS(similarityFunc=lambda x,y: (distanceForLCSS(x,y) <= spatialThreshold),delta=delta) + similarity={} + for y in prototypesRoutes: + if y in prototypes.keys(): + prototypesIDs=prototypes[y] + for x in prototypesIDs: + s=lcss.computeNormalized(partialObjPositions, objects[x].positions) + if s >= minSimilarity: + similarity[x]=s + + if mostMatched==None: + probabilities= calculateProbability(nMatching,similarity,objects) + return probabilities + else: + mostMatchedValues=sorted(similarity.values(),reverse=True)[:mostMatched] + keys=[k for k in similarity.keys() if similarity[k] in mostMatchedValues] + newSimilarity={} + for i in keys: + newSimilarity[i]=similarity[i] + probabilities= calculateProbability(nMatching,newSimilarity,objects) + return probabilities + +def findPrototypesSpeed(prototypes,secondStepPrototypes,nMatching,objects,route,partialObjPositions,noiseEntryNums,noiseExitNums,minSimilarity=0.1,mostMatched=None,useDestination=True,spatialThreshold=1.0, delta=180): + if useDestination: + prototypesRoutes=[route] + else: + if route[0] not in noiseEntryNums: + prototypesRoutes= [ x for x in sorted(prototypes.keys()) if route[0]==x[0]] + elif route[1] not in noiseExitNums: + prototypesRoutes=[ x for x in sorted(prototypes.keys()) if route[1]==x[1]] + else: + prototypesRoutes=[x for x in sorted(prototypes.keys())] + lcss = LCSS(similarityFunc=lambda x,y: (distanceForLCSS(x,y) <= spatialThreshold),delta=delta) + similarity={} + for y in prototypesRoutes: + if y in prototypes.keys(): + prototypesIDs=prototypes[y] + for x in prototypesIDs: + s=lcss.computeNormalized(partialObjPositions, objects[x].positions) + if s >= minSimilarity: + similarity[x]=s + + newSimilarity={} + for i in similarity.keys(): + if i in secondStepPrototypes.keys(): + for j in secondStepPrototypes[i]: + newSimilarity[j]=similarity[i] + probabilities= calculateProbability(nMatching,newSimilarity,objects) + return probabilities + +def getPrototypeTrajectory(obj,route,currentInstant,prototypes,secondStepPrototypes,nMatching,objects,noiseEntryNums,noiseExitNums,minSimilarity=0.1,mostMatched=None,useDestination=True,useSpeedPrototype=True): + partialInterval=moving.Interval(obj.getFirstInstant(),currentInstant) + partialObjPositions= obj.getObjectInTimeInterval(partialInterval).positions + if useSpeedPrototype: + prototypeTrajectories=findPrototypesSpeed(prototypes,secondStepPrototypes,nMatching,objects,route,partialObjPositions,noiseEntryNums,noiseExitNums,minSimilarity,mostMatched,useDestination) + else: + prototypeTrajectories=findPrototypes(prototypes,nMatching,objects,route,partialObjPositions,noiseEntryNums,noiseExitNums,minSimilarity,mostMatched) + return prototypeTrajectories + +def computeCrossingsCollisionsAtInstant(predictionParams,currentInstant, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False,usePrototypes=True,route1= (-1,-1),route2=(-1,-1),prototypes={},secondStepPrototypes={},nMatching={},objects=[],noiseEntryNums=[],noiseExitNums=[],minSimilarity=0.1,mostMatched=None,useDestination=True,useSpeedPrototype=True): '''returns the lists of collision points and crossing zones''' - if prototypeTrajectories1==None: + if usePrototypes: + prototypeTrajectories1=getPrototypeTrajectory(obj1,route1,currentInstant,prototypes,secondStepPrototypes,nMatching,objects,noiseEntryNums,noiseExitNums,minSimilarity,mostMatched,useDestination,useSpeedPrototype) + prototypeTrajectories2= getPrototypeTrajectory(obj2,route2,currentInstant,prototypes,secondStepPrototypes,nMatching,objects,noiseEntryNums,noiseExitNums,minSimilarity,mostMatched,useDestination,useSpeedPrototype) + predictedTrajectories1 = predictionParams.generatePredictedTrajectories(obj1, currentInstant,prototypeTrajectories1) + predictedTrajectories2 = predictionParams.generatePredictedTrajectories(obj2, currentInstant,prototypeTrajectories2) + else: predictedTrajectories1 = predictionParams.generatePredictedTrajectories(obj1, currentInstant) predictedTrajectories2 = predictionParams.generatePredictedTrajectories(obj2, currentInstant) - else: - predictedTrajectories1 = predictionParams.generatePredictedTrajectories(obj1, currentInstant,prototypeTrajectories1) - predictedTrajectories2 = predictionParams.generatePredictedTrajectories(obj2, currentInstant,prototypeTrajectories2) collisionPoints = [] crossingZones = [] @@ -205,7 +286,7 @@ savePredictedTrajectoriesFigure(currentInstant, obj1, obj2, predictedTrajectories1, predictedTrajectories2, timeHorizon) return currentInstant,collisionPoints, crossingZones -def computeCrossingsCollisions(predictionParams, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False, timeInterval = None,nProcesses = 1,prototypeTrajectories1=None,prototypeTrajectories2=None): +def computeCrossingsCollisions(predictionParams, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False, timeInterval = None,nProcesses = 1,usePrototypes=True,route1= (-1,-1),route2=(-1,-1),prototypes={},secondStepPrototypes={},nMatching={},objects=[],noiseEntryNums=[],noiseExitNums=[],minSimilarity=0.1,mostMatched=None,useDestination=True,useSpeedPrototype=True,acceptPartialLength=30, step=1): '''Computes all crossing and collision points at each common instant for two road users. ''' collisionPoints={} crossingZones={} @@ -214,16 +295,35 @@ else: commonTimeInterval = obj1.commonTimeInterval(obj2) if nProcesses == 1: - for i in list(commonTimeInterval)[:-1]: # do not look at the 1 last position/velocities, often with errors - i, cp, cz = computeCrossingsCollisionsAtInstant(predictionParams, i, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ, debug,prototypeTrajectories1,prototypeTrajectories2) - if len(cp) != 0: - collisionPoints[i] = cp - if len(cz) != 0: - crossingZones[i] = cz + if usePrototypes: + firstInstant= next( (x for x in xrange(commonTimeInterval.first,commonTimeInterval.last) if x-obj1.getFirstInstant() >= acceptPartialLength and x-obj2.getFirstInstant() >= acceptPartialLength), commonTimeInterval.last) + commonTimeIntervalList1= list(xrange(firstInstant,commonTimeInterval.last-1)) # do not look at the 1 last position/velocities, often with errors + commonTimeIntervalList2= list(xrange(firstInstant,commonTimeInterval.last-1,step)) # do not look at the 1 last position/velocities, often with errors + for i in commonTimeIntervalList2: + i, cp, cz = computeCrossingsCollisionsAtInstant(predictionParams, i, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ, debug,usePrototypes,route1,route2,prototypes,secondStepPrototypes,nMatching,objects,noiseEntryNums,noiseExitNums,minSimilarity,mostMatched,useDestination,useSpeedPrototype) + if len(cp) != 0: + collisionPoints[i] = cp + if len(cz) != 0: + crossingZones[i] = cz + if collisionPoints!={} or crossingZones!={}: + for i in commonTimeIntervalList1: + if i not in commonTimeIntervalList2: + i, cp, cz = computeCrossingsCollisionsAtInstant(predictionParams, i, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ, debug,usePrototypes,route1,route2,prototypes,secondStepPrototypes,nMatching,objects,noiseEntryNums,noiseExitNums,minSimilarity,mostMatched,useDestination,useSpeedPrototype) + if len(cp) != 0: + collisionPoints[i] = cp + if len(cz) != 0: + crossingZones[i] = cz + else: + for i in list(commonTimeInterval)[:-1]: # do not look at the 1 last position/velocities, often with errors + i, cp, cz = computeCrossingsCollisionsAtInstant(predictionParams, i, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ, debug,usePrototypes,route1,route2,prototypes,secondStepPrototypes,nMatching,objects,noiseEntryNums,noiseExitNums,minSimilarity,mostMatched,useDestination,useSpeedPrototype) + if len(cp) != 0: + collisionPoints[i] = cp + if len(cz) != 0: + crossingZones[i] = cz else: from multiprocessing import Pool pool = Pool(processes = nProcesses) - jobs = [pool.apply_async(computeCrossingsCollisionsAtInstant, args = (predictionParams, i, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ, debug,prototypeTrajectories1,prototypeTrajectories2)) for i in list(commonTimeInterval)[:-1]] + jobs = [pool.apply_async(computeCrossingsCollisionsAtInstant, args = (predictionParams, i, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ, debug,usePrototypes,route1,route2,prototypes,secondStepPrototypes,nMatching,objects,noiseEntryNums,noiseExitNums,minSimilarity,mostMatched,useDestination,useSpeedPrototype)) for i in list(commonTimeInterval)[:-1]] #results = [j.get() for j in jobs] #results.sort() for j in jobs: @@ -247,11 +347,11 @@ def generatePredictedTrajectories(self, obj, instant): return [] - def computeCrossingsCollisionsAtInstant(self, currentInstant, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False,prototypeTrajectories1=None,prototypeTrajectories2=None): - return computeCrossingsCollisionsAtInstant(self, currentInstant, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ, debug,prototypeTrajectories1,prototypeTrajectories2) + def computeCrossingsCollisionsAtInstant(self, currentInstant, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False,usePrototypes=True,route1= (-1,-1),route2=(-1,-1),prototypes={},secondStepPrototypes={},nMatching={},objects=[],noiseEntryNums=[],noiseExitNums=[],minSimilarity=0.1,mostMatched=None,useDestination=True,useSpeedPrototype=True): + return computeCrossingsCollisionsAtInstant(self, currentInstant, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ, debug,usePrototypes,route1,route2,prototypes,secondStepPrototypes,nMatching,objects,noiseEntryNums,noiseExitNums,minSimilarity,mostMatched,useDestination,useSpeedPrototype) - def computeCrossingsCollisions(self, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False, timeInterval = None, nProcesses = 1,prototypeTrajectories1=None,prototypeTrajectories2=None): - return computeCrossingsCollisions(self, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ, debug, timeInterval, nProcesses,prototypeTrajectories1,prototypeTrajectories2) + def computeCrossingsCollisions(self, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False, timeInterval = None, nProcesses = 1,usePrototypes=True,route1= (-1,-1),route2=(-1,-1),prototypes={},secondStepPrototypes={},nMatching={},objects=[],noiseEntryNums=[],noiseExitNums=[],minSimilarity=0.1,mostMatched=None,useDestination=True,useSpeedPrototype=True,acceptPartialLength=30, step=1): + return computeCrossingsCollisions(self, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ, debug, timeInterval, nProcesses,usePrototypes,route1,route2,prototypes,secondStepPrototypes,nMatching,objects,noiseEntryNums,noiseExitNums,minSimilarity,mostMatched,useDestination,useSpeedPrototype,acceptPartialLength, step) def computeCollisionProbability(self, obj1, obj2, collisionDistanceThreshold, timeHorizon, debug = False, timeInterval = None): '''Computes only collision probabilities
--- a/python/storage.py Wed Dec 03 18:56:49 2014 +0000 +++ b/python/storage.py Wed Dec 10 14:18:30 2014 -0500 @@ -34,6 +34,7 @@ except sqlite3.OperationalError as error: printDBError(error) +# TODO: add test if database connection is open # IO to sqlite def writeTrajectoriesToSqlite(objects, outputFilename, trajectoryType, objectNumbers = -1): """ @@ -293,20 +294,21 @@ if trajectoryType == 'feature': statementBeginning = 'where trajectory_id ' elif trajectoryType == 'object': - statementBeginning = 'and OF.object_id ' + statementBeginning = 'and OF.object_id ' + elif trajectoryType == 'bbtop' or 'bbbottom': + statementBeginning = 'where object_id ' else: print('no trajectory type was chosen') - if type(objectNumbers) == int: - if objectNumbers == -1: - query = '' - else: - query = statementBeginning+'between 0 and {0} '.format(objectNumbers) + if objectNumbers is None: + query = '' + elif type(objectNumbers) == int: + query = statementBeginning+'between 0 and {0} '.format(objectNumbers) elif type(objectNumbers) == list: query = statementBeginning+'in ('+', '.join([str(n) for n in objectNumbers])+') ' return query -def loadTrajectoriesFromTable(connection, tableName, trajectoryType, objectNumbers = -1): +def loadTrajectoriesFromTable(connection, tableName, trajectoryType, objectNumbers = None): '''Loads trajectories (in the general sense) from the given table can be positions or velocities @@ -314,14 +316,21 @@ cursor = connection.cursor() try: + idQuery = getTrajectoryIdQuery(objectNumbers, trajectoryType) if trajectoryType == 'feature': - trajectoryIdQuery = getTrajectoryIdQuery(objectNumbers, trajectoryType) - queryStatement = 'SELECT * from '+tableName+' '+trajectoryIdQuery+'order by trajectory_id, frame_number' + queryStatement = 'SELECT * from '+tableName+' '+idQuery+'ORDER BY trajectory_id, frame_number' cursor.execute(queryStatement) logging.debug(queryStatement) elif trajectoryType == 'object': - objectIdQuery = getTrajectoryIdQuery(objectNumbers, trajectoryType) - queryStatement = 'SELECT OF.object_id, P.frame_number, avg(P.x_coordinate), avg(P.y_coordinate) from '+tableName+' P, objects_features OF where P.trajectory_id = OF.trajectory_id '+objectIdQuery+'group by OF.object_id, P.frame_number order by OF.object_id, P.frame_number' + queryStatement = 'SELECT OF.object_id, P.frame_number, avg(P.x_coordinate), avg(P.y_coordinate) from '+tableName+' P, objects_features OF where P.trajectory_id = OF.trajectory_id '+idQuery+'group by OF.object_id, P.frame_number ORDER BY OF.object_id, P.frame_number' + cursor.execute(queryStatement) + logging.debug(queryStatement) + elif trajectoryType in ['bbtop', 'bbbottom']: + if trajectoryType == 'bbtop': + corner = 'top_left' + elif trajectoryType == 'bbbottom': + corner = 'bottom_right' + queryStatement = 'SELECT object_id, frame_number, x_'+corner+', y_'+corner+' FROM '+tableName+' '+trajectoryIdQuery+'ORDER BY object_id, frame_number' cursor.execute(queryStatement) logging.debug(queryStatement) else: @@ -336,21 +345,36 @@ for row in cursor: if row[0] != objId: objId = row[0] - if obj: + if obj != None and obj.length() == obj.positions.length(): objects.append(obj) + elif obj != None: + print('Object {} is missing {} positions'.format(obj.getNum(), int(obj.length())-obj.positions.length())) obj = moving.MovingObject(row[0], timeInterval = moving.TimeInterval(row[1], row[1]), positions = moving.Trajectory([[row[2]],[row[3]]])) else: obj.timeInterval.last = row[1] obj.positions.addPositionXY(row[2],row[3]) - if obj: + if obj != None and obj.length() == obj.positions.length(): objects.append(obj) + elif obj != None: + print('Object {} is missing {} positions'.format(obj.getNum(), int(obj.length())-obj.positions.length())) return objects -def loadTrajectoriesFromSqlite(filename, trajectoryType, objectNumbers = -1): - '''Loads nObjects or the indices in objectNumbers from the database''' - connection = sqlite3.connect(filename) # add test if it open +def loadUserTypesFromTable(cursor, trajectoryType, objectNumbers): + objectIdQuery = getTrajectoryIdQuery(objectNumbers, trajectoryType) + if objectIdQuery == '': + cursor.execute('SELECT object_id, road_user_type from objects') + else: + cursor.execute('SELECT object_id, road_user_type from objects where '+objectIdQuery[7:]) + userTypes = {} + for row in cursor: + userTypes[row[0]] = row[1] + return userTypes + +def loadTrajectoriesFromSqlite(filename, trajectoryType, objectNumbers = None): + '''Loads the first objectNumbers objects or the indices in objectNumbers from the database''' + connection = sqlite3.connect(filename) objects = loadTrajectoriesFromTable(connection, 'positions', trajectoryType, objectNumbers) objectVelocities = loadTrajectoriesFromTable(connection, 'velocities', trajectoryType, objectNumbers) @@ -384,26 +408,40 @@ obj.featureNumbers = featureNumbers[obj.getNum()] # load userType - if objectIdQuery == '': - cursor.execute('SELECT object_id, road_user_type from objects') - else: - cursor.execute('SELECT object_id, road_user_type from objects where '+objectIdQuery[7:]) - userTypes = {} - for row in cursor: - userTypes[row[0]] = row[1] - + userTypes = loadUserTypesFromTable(cursor, trajectoryType, objectNumbers) for obj in objects: obj.userType = userTypes[obj.getNum()] except sqlite3.OperationalError as error: printDBError(error) - return [] + objects = [] connection.close() return objects -def removeFromSqlite(filename, dataType): - 'Removes some tables in the filename depending on type of data' +def loadGroundTruthFromSqlite(filename, gtType, gtNumbers = None): + 'Loads bounding box annotations (ground truth) from an SQLite ' + connection = sqlite3.connect(filename) + gt = [] + + if gtType == 'bb': + topCorners = loadTrajectoriesFromTable(connection, 'bounding_boxes', 'bbtop', gtNumbers) + bottomCorners = loadTrajectoriesFromTable(connection, 'bounding_boxes', 'bbbottom', gtNumbers) + userTypes = loadUserTypesFromTable(connection.cursor(), 'object', gtNumbers) # string format is same as object + + for t, b in zip(topCorners, bottomCorners): + num = t.getNum() + if t.getNum() == b.getNum(): + annotation = moving.BBAnnotation(num, t.getTimeInterval(), t, b, userTypes[num]) + gt.append(annotation) + else: + print ('Unknown type of annotation {}'.format(gtType)) + + connection.close() + return gt + +def deleteFromSqlite(filename, dataType): + 'Deletes (drops) some tables in the filename depending on type of data' import os if os.path.isfile(filename): connection = sqlite3.connect(filename) @@ -525,7 +563,7 @@ connection.commit() connection.close() -def loadBoundingBoxTable(filename): +def loadBoundingBoxTableForDisplay(filename): connection = sqlite3.connect(filename) cursor = connection.cursor() boundingBoxes = {} # list of bounding boxes for each instant @@ -534,9 +572,7 @@ result = [row for row in cursor] if len(result) > 0: cursor.execute('SELECT * FROM bounding_boxes') - #objId = -1 for row in cursor: - #if row[0] != objId: boundingBoxes.setdefault(row[1], []).append([moving.Point(row[2], row[3]), moving.Point(row[4], row[5])]) except sqlite3.OperationalError as error: printDBError(error) @@ -544,6 +580,19 @@ connection.close() return boundingBoxes +def loadBoundingBoxTable(filename): + connection = sqlite3.connect(filename) + cursor = connection.cursor() + boundingBoxes = [] + + try: + pass + except sqlite3.OperationalError as error: + printDBError(error) + return boundingBoxes + connection.close() + return boundingBoxes + ######################### # txt files
--- a/python/utils.py Wed Dec 03 18:56:49 2014 +0000 +++ b/python/utils.py Wed Dec 10 14:18:30 2014 -0500 @@ -61,15 +61,13 @@ def nSamples(self): return sum(self.counts) -def cumulativeDensityFunction(sample): +def cumulativeDensityFunction(sample, normalized = False): '''Returns the cumulative density function of the sample of a random variable''' - from numpy.core.multiarray import array - from numpy.lib.function_base import unique - from numpy.core.fromnumeric import sum - a = array(sample) - a.sort() - xaxis = unique(a) - counts = [sum(a <= x) for x in xaxis] + from numpy import arange, cumsum + xaxis = sorted(sample) + counts = arange(1,len(sample)+1) # dtype = float + if normalized: + counts /= float(len(sample)) return xaxis, counts class EmpiricalDiscreteDistribution(EmpiricalDistribution):
--- a/scripts/delete-tables.py Wed Dec 03 18:56:49 2014 +0000 +++ b/scripts/delete-tables.py Wed Dec 10 14:18:30 2014 -0500 @@ -5,10 +5,10 @@ import utils import storage -parser = argparse.ArgumentParser(description='The program deletes the tables in the database before saving new results (for objects, tables object_features and objects are dropped; for interactions, the tables interactions and indicators are dropped') +parser = argparse.ArgumentParser(description='The program deletes (drops) the tables in the database before saving new results (for objects, tables object_features and objects are dropped; for interactions, the tables interactions and indicators are dropped') #parser.add_argument('configFilename', help = 'name of the configuration file') parser.add_argument('-d', dest = 'databaseFilename', help = 'name of the Sqlite database', required = True) parser.add_argument('-t', dest = 'dataType', help = 'type of the data to remove', required = True, choices = ['object','interaction', 'bb']) args = parser.parse_args() -storage.removeFromSqlite(args.databaseFilename, args.dataType) +storage.deleteFromSqlite(args.databaseFilename, args.dataType)
--- a/scripts/display-trajectories.py Wed Dec 03 18:56:49 2014 +0000 +++ b/scripts/display-trajectories.py Wed Dec 10 14:18:30 2014 -0500 @@ -63,5 +63,5 @@ objects = storage.loadTrajectoriesFromSqlite(databaseFilename, args.trajectoryType) -boundingBoxes = storage.loadBoundingBoxTable(databaseFilename) +boundingBoxes = storage.loadBoundingBoxTableForDisplay(databaseFilename) cvutils.displayTrajectories(videoFilename, objects, boundingBoxes, homography, firstFrameNum, args.lastFrameNum, rescale = args.rescale, nFramesStep = args.nFramesStep, saveAllImages = args.saveAllImages, undistort = (undistort or args.undistort), intrinsicCameraMatrix = intrinsicCameraMatrix, distortionCoefficients = distortionCoefficients, undistortedImageMultiplication = undistortedImageMultiplication)