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comparison trafficintelligence/moving.py @ 1249:2aa56b101041

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added mask functionality for dltrack
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Thu, 15 Feb 2024 14:09:52 -0500
parents 371c718e57d7
children 77fbd0e2ba7d
comparison
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1248:c4c50678c856 1249:2aa56b101041
1 #! /usr/bin/env python 1 #! /usr/bin/env python
2 '''Libraries for moving objects, trajectories...''' 2 '''Libraries for moving objects, trajectories...'''
3 3
4 import copy 4 import copy
5 from math import sqrt, atan2, cos, sin 5 from math import sqrt, atan2, cos, sin, inf
6 6
7 from numpy import median, mean, array, arange, zeros, ones, hypot, NaN, std, floor, ceil, float32, argwhere, minimum, issubdtype, integer as npinteger, percentile 7 from numpy import median, mean, array, arange, zeros, ones, hypot, NaN, std, floor, ceil, float32, argwhere, minimum, issubdtype, integer as npinteger, percentile
8 from matplotlib.pyplot import plot, text, arrow 8 from matplotlib.pyplot import plot, text, arrow
9 from scipy.spatial.distance import cdist 9 from scipy.spatial.distance import cdist
10 from scipy.signal import savgol_filter 10 from scipy.signal import savgol_filter
293 293
294 def astuple(self): 294 def astuple(self):
295 return (self.x, self.y) 295 return (self.x, self.y)
296 296
297 def asint(self): 297 def asint(self):
298 return Point(int(self.x), int(self.y)) 298 return Point(int(round(self.x)), int(round(self.y)))
299 299
300 if shapelyAvailable: 300 if shapelyAvailable:
301 def asShapely(self): 301 def asShapely(self):
302 return shapelyPoint(self.x, self.y) 302 return shapelyPoint(self.x, self.y)
303 303
2052 for userTypename in speedProbabilities: 2052 for userTypename in speedProbabilities:
2053 userTypeProbabilities[userType2Num[userTypename]] = speedProbabilities[userTypename](self.aggregatedSpeed) 2053 userTypeProbabilities[userType2Num[userTypename]] = speedProbabilities[userTypename](self.aggregatedSpeed)
2054 self.setUserType(utils.argmaxDict(userTypeProbabilities)) 2054 self.setUserType(utils.argmaxDict(userTypeProbabilities))
2055 return userTypeProbabilities 2055 return userTypeProbabilities
2056 2056
2057 def initClassifyUserTypeHoGSVM(self, aggregationFunc, pedBikeCarSVM, bikeCarSVM = None, pedBikeSpeedThreshold = float('Inf'), bikeCarSpeedThreshold = float('Inf'), nInstantsIgnoredAtEnds = 0, homography = None, intrinsicCameraMatrix = None, distortionCoefficients = None): 2057 def initClassifyUserTypeHoGSVM(self, aggregationFunc, pedBikeCarSVM, bikeCarSVM = None, pedBikeSpeedThreshold = inf, bikeCarSpeedThreshold = float('Inf'), nInstantsIgnoredAtEnds = 0, homography = None, intrinsicCameraMatrix = None, distortionCoefficients = None):
2058 '''Initializes the data structures for classification 2058 '''Initializes the data structures for classification
2059 2059
2060 TODO? compute speed for longest feature?''' 2060 TODO? compute speed for longest feature?'''
2061 self.aggregatedSpeed = aggregationFunc(self.getSpeeds(nInstantsIgnoredAtEnds)) 2061 self.aggregatedSpeed = aggregationFunc(self.getSpeeds(nInstantsIgnoredAtEnds))
2062 if self.aggregatedSpeed < pedBikeSpeedThreshold or bikeCarSVM is None: 2062 if self.aggregatedSpeed < pedBikeSpeedThreshold or bikeCarSVM is None: