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annotate scripts/process.py @ 1003:75af46516b2b

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work in progress
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Fri, 01 Jun 2018 17:19:31 -0400
parents 933670761a57
children 75601be6019f
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933670761a57 updated code to python 3 (tests pass and scripts run, but non-executed parts of code are probably still not correct)
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1 #! /usr/bin/env python3
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2
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3 import sys, argparse
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4 from pathlib import Path
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5
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6 import matplotlib
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7 matplotlib.use('Agg')
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8 import matplotlib.pyplot as plt
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9 from numpy import percentile
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10
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11 import storage, events, prediction
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12 from metadata import *
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13
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14 parser = argparse.ArgumentParser(description='This program manages the processing of several files based on a description of the sites and video data in an SQLite database following the metadata module.')
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15 parser.add_argument('--db', dest = 'metadataFilename', help = 'name of the metadata file', required = True)
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16 parser.add_argument('--videos', dest = 'videoIds', help = 'indices of the video sequences', nargs = '*', type = int)
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17 parser.add_argument('--cfg', dest = 'configFilename', help = 'name of the configuration file')
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18 parser.add_argument('-n', dest = 'nObjects', help = 'number of objects/interactions to process', type = int)
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19 parser.add_argument('--prediction-method', dest = 'predictionMethod', help = 'prediction method (constant velocity (cvd: vector computation (approximate); cve: equation solving; cv: discrete time (approximate)), normal adaptation, point set prediction)', choices = ['cvd', 'cve', 'cv', 'na', 'ps', 'mp'])
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20 parser.add_argument('--pet', dest = 'computePET', help = 'computes PET', action = 'store_true')
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21 # override other tracking config, erase sqlite?
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22 parser.add_argument('--delete', dest = 'delete', help = 'data to delete', choices = ['feature', 'object', 'classification', 'interaction'])
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23 parser.add_argument('--process', dest = 'process', help = 'data to process', choices = ['feature', 'object', 'classification', 'interaction'])
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24 parser.add_argument('--display', dest = 'display', help = 'data to display (replay over video)', choices = ['feature', 'object', 'classification', 'interaction'])
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25 parser.add_argument('--analyze', dest = 'analyze', help = 'data to analyze (results)', choices = ['feature', 'object', 'classification', 'interaction'])
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26
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27 # need way of selecting sites as similar as possible to sql alchemy syntax
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28 # override tracking.cfg from db
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29 # manage cfg files, overwrite them (or a subset of parameters)
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30 # delete sqlite files
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31
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32 # info of metadata
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33
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34 parser.add_argument('--nthreads', dest = 'nProcesses', help = 'number of processes to run in parallel', type = int, default = 1)
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35
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36 args = parser.parse_args()
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37 # files are relative to metadata location
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38
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39 session = connectDatabase(args.metadataFilename)
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40 parentDir = Path(args.metadataFilename).parent
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41
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42 if args.delete is not None:
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43 if args.delete in ['object', 'interaction']:
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44 #parser.add_argument('-t', dest = 'dataType', help = 'type of the data to remove', required = True, choices = ['object','interaction', 'bb', 'pois', 'prototype'])
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45 for videoId in args.videoIds:
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46 vs = session.query(VideoSequence).get(videoId)
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47 storage.deleteFromSqlite(str(parentDir/vs.getDatabaseFilename()), args.delete)
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48
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49 if args.process in ['feature', 'object']: # tracking
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50 for videoId in args.videoIds:
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51 vs = session.query(VideoSequence).get(videoId)
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52 if args.configFilename is None:
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53 configFilename = vs.cameraView.getTrackingConfigurationFilename()
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54 else:
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55 configFilename = args.configFilename
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56 #todo cvutils.tracking(configFilename, args.process == 'object', str(parentDir/vs.getVideoSequenceFilename(), str(parentDir/vs.getDatabaseFilename(), configFilename = vs.cameraView.getHomographyFilename())
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57
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58 elif args.process == 'interaction':
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59 # safety analysis TODO make function in safety analysis script
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60 if args.predictionMethod == 'cvd':
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61 predictionParameters = prediction.CVDirectPredictionParameters()
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62 if args.predictionMethod == 'cve':
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63 predictionParameters = prediction.CVExactPredictionParameters()
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64 for videoId in args.videoIds:
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65 vs = session.query(VideoSequence).get(videoId)
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66 print('Processing '+vs.getDatabaseFilename())
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67 objects = storage.loadTrajectoriesFromSqlite(str(parentDir/vs.getDatabaseFilename()), 'object')#, args.nObjects, withFeatures = (params.useFeaturesForPrediction or predictionMethod == 'ps' or predictionMethod == 'mp'))
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68 interactions = events.createInteractions(objects)
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69 #if args.nProcesses == 1:
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70 #print(str(parentDir/vs.cameraView.getTrackingConfigurationFilename()))
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71 params = storage.ProcessParameters(str(parentDir/vs.cameraView.getTrackingConfigurationFilename()))
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72 #print(len(interactions), args.computePET, predictionParameters, params.collisionDistance, params.predictionTimeHorizon, params.crossingZones)
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73 processed = events.computeIndicators(interactions, True, args.computePET, predictionParameters, params.collisionDistance, params.predictionTimeHorizon, params.crossingZones, False, None)
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74 storage.saveIndicatorsToSqlite(str(parentDir/vs.getDatabaseFilename()), processed)
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75 # else:
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76 # pool = Pool(processes = args.nProcesses)
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77 # nInteractionPerProcess = int(np.ceil(len(interactions)/float(args.nProcesses)))
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78 # jobs = [pool.apply_async(events.computeIndicators, args = (interactions[i*nInteractionPerProcess:(i+1)*nInteractionPerProcess], not args.noMotionPrediction, args.computePET, predictionParameters, params.collisionDistance, params.predictionTimeHorizon, params.crossingZones, False, None)) for i in range(args.nProcesses)]
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79 # processed = []
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80 # for job in jobs:
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81 # processed += job.get()
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82 # pool.close()
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83
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84 if args.analyze == 'object': # user speed for now
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85 medianSpeeds = {}
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86 speeds85 = {}
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87 minLength = 2*30
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88 for videoId in args.videoIds:
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89 vs = session.query(VideoSequence).get(videoId)
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90 if not vs.cameraView.siteIdx in medianSpeeds:
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91 medianSpeeds[vs.cameraView.siteIdx] = []
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92 speeds85[vs.cameraView.siteIdx] = []
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93 print('Extracting speed from '+vs.getDatabaseFilename())
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94 objects = storage.loadTrajectoriesFromSqlite(str(parentDir/vs.getDatabaseFilename()), 'object')
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95 for o in objects:
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96 if o.length() > minLength:
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97 speeds = 30*3.6*percentile(o.getSpeeds(), [50, 85])
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98 medianSpeeds[vs.cameraView.siteIdx].append(speeds[0])
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99 speeds85[vs.cameraView.siteIdx].append(speeds[1])
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100 for speeds, name in zip([medianSpeeds, speeds85], ['Median', '85th Centile']):
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101 plt.ioff()
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102 plt.figure()
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103 plt.boxplot(list(speeds.values()), labels = [session.query(Site).get(siteId).name for siteId in speeds])
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104 plt.ylabel(name+' Speeds (km/h)')
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105 plt.savefig(name.lower()+'-speeds.png', dpi=150)
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106 plt.close()
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107
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108 if args.analyze == 'interaction':
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109 indicatorIds = [2,5,7,10]
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110 conversionFactors = {2: 1., 5: 30.*3.6, 7:1./30, 10:1./30}
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111 maxIndicatorValue = {2: float('inf'), 5: float('inf'), 7:10., 10:10.}
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112 indicators = {}
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113 interactions = {}
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114 for videoId in args.videoIds:
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115 vs = session.query(VideoSequence).get(videoId)
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116 if not vs.cameraView.siteIdx in interactions:
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117 interactions[vs.cameraView.siteIdx] = []
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118 indicators[vs.cameraView.siteIdx] = {}
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119 for i in indicatorIds:
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120 indicators[vs.cameraView.siteIdx][i] = []
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121 interactions[vs.cameraView.siteIdx] += storage.loadInteractionsFromSqlite(str(parentDir/vs.getDatabaseFilename()))
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122 print(vs.getDatabaseFilename(), len(interactions[vs.cameraView.siteIdx]))
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123 for inter in interactions[vs.cameraView.siteIdx]:
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124 for i in indicatorIds:
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125 indic = inter.getIndicator(events.Interaction.indicatorNames[i])
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126 if indic is not None:
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127 v = indic.getMostSevereValue()*conversionFactors[i]
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128 if v < maxIndicatorValue[i]:
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129 indicators[vs.cameraView.siteIdx][i].append(v)
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130
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131 for i in indicatorIds:
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132 tmp = [indicators[siteId][i] for siteId in indicators]
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133 plt.ioff()
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134 plt.figure()
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135 plt.boxplot(tmp, labels = [session.query(Site).get(siteId).name for siteId in indicators])
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136 plt.ylabel(events.Interaction.indicatorNames[i]+' ('+events.Interaction.indicatorUnits[i]+')')
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137 plt.savefig(events.Interaction.indicatorNames[i]+'.png', dpi=150)
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138 plt.close()