Mercurial > hg > nsaunier > traffic-intelligence

comparison scripts/classify-objects.py @ 899:1466a63dd1cf

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added a new classification parameter
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Wed, 21 Jun 2017 17:44:09 -0400
parents 1fc901d983ed
children 753a081989e2
comparison
equal deleted inserted replaced
898:1fc901d983ed 899:1466a63dd1cf
112 if inter.contains(frameNum): 112 if inter.contains(frameNum):
113 if inter.first == frameNum: 113 if inter.first == frameNum:
114 obj.initClassifyUserTypeHoGSVM(speedAggregationFunc, pedBikeCarSVM, bikeCarSVM, classifierParams.maxPedestrianSpeed, classifierParams.maxCyclistSpeed, classifierParams.nFramesIgnoreAtEnds) 114 obj.initClassifyUserTypeHoGSVM(speedAggregationFunc, pedBikeCarSVM, bikeCarSVM, classifierParams.maxPedestrianSpeed, classifierParams.maxCyclistSpeed, classifierParams.nFramesIgnoreAtEnds)
115 currentObjects.append(obj) 115 currentObjects.append(obj)
116 elif inter.last == frameNum: 116 elif inter.last == frameNum:
117 obj.classifyUserTypeHoGSVM(minSpeedEquiprobable = classifierParams.minSpeedEquiprobable, speedProbabilities = speedProbabilities, maxPercentUnknown = 0.5) # todo add maxPercentUnknown in cfg 117 obj.classifyUserTypeHoGSVM(minSpeedEquiprobable = classifierParams.minSpeedEquiprobable, speedProbabilities = speedProbabilities, maxPercentUnknown = classifierParams.maxPercentUnknown)
118 pastObjects.append(obj) 118 pastObjects.append(obj)
119 else: 119 else:
120 obj.classifyUserTypeHoGSVMAtInstant(img, frameNum, invHomography, width, height, classifierParams.percentIncreaseCrop, classifierParams.percentIncreaseCrop, classifierParams.minNPixels, classifierParams.hogRescaleSize, classifierParams.hogNOrientations, classifierParams.hogNPixelsPerCell, classifierParams.hogNCellsPerBlock, classifierParams.hogBlockNorm) 120 obj.classifyUserTypeHoGSVMAtInstant(img, frameNum, invHomography, width, height, classifierParams.percentIncreaseCrop, classifierParams.percentIncreaseCrop, classifierParams.minNPixels, classifierParams.hogRescaleSize, classifierParams.hogNOrientations, classifierParams.hogNPixelsPerCell, classifierParams.hogNCellsPerBlock, classifierParams.hogBlockNorm)
121 currentObjects.append(obj) 121 currentObjects.append(obj)
122 else: 122 else:
123 currentObjects.append(obj) 123 currentObjects.append(obj)
124 objects = currentObjects 124 objects = currentObjects
125 frameNum += 1 125 frameNum += 1
126 126
127 for obj in objects: 127 for obj in objects:
128 obj.classifyUserTypeHoGSVM(minSpeedEquiprobable = classifierParams.minSpeedEquiprobable, speedProbabilities = speedProbabilities) 128 obj.classifyUserTypeHoGSVM(minSpeedEquiprobable = classifierParams.minSpeedEquiprobable, speedProbabilities = speedProbabilities, maxPercentUnknown = classifierParams.maxPercentUnknown)
129 pastObjects.append(obj) 129 pastObjects.append(obj)
130 print('Saving user types') 130 print('Saving user types')
131 storage.setRoadUserTypes(databaseFilename, pastObjects) 131 storage.setRoadUserTypes(databaseFilename, pastObjects)