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annotate scripts/process.py @ 1066:862b55a87e63

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work on extracting information
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Mon, 16 Jul 2018 01:14:37 -0400
parents d4d052a05337
children 092bd9c7deaf
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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 from multiprocessing.pool import Pool
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6
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7 #import matplotlib
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8 #atplotlib.use('Agg')
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9 import matplotlib.pyplot as plt
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10 import numpy as np
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11 import pandas as pd
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12
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13 from trafficintelligence import storage, events, prediction, cvutils, utils, moving, processing, ml
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14 from trafficintelligence.metadata import *
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16 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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17 # input
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18 parser.add_argument('--db', dest = 'metadataFilename', help = 'name of the metadata file', required = True)
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19 parser.add_argument('--videos', dest = 'videoIds', help = 'indices of the video sequences', nargs = '*')
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20 parser.add_argument('--sites', dest = 'siteIds', help = 'indices of the video sequences', nargs = '*')
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22 # main function
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23 parser.add_argument('--delete', dest = 'delete', help = 'data to delete', choices = ['feature', 'object', 'classification', 'interaction'])
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24 parser.add_argument('--process', dest = 'process', help = 'data to process', choices = ['feature', 'object', 'classification', 'prototype', 'interaction'])
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25 parser.add_argument('--display', dest = 'display', help = 'data to display (replay over video)', choices = ['feature', 'object', 'classification', 'interaction'])
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26 parser.add_argument('--progress', dest = 'progress', help = 'information about the progress of processing', action = 'store_true')
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27 parser.add_argument('--analyze', dest = 'analyze', help = 'data to analyze (results)', choices = ['feature', 'object', 'classification', 'interaction', 'event'])
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29 # common options
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30 parser.add_argument('--cfg', dest = 'configFilename', help = 'name of the configuration file')
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31 parser.add_argument('-n', dest = 'nObjects', help = 'number of objects/interactions to process', type = int)
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32 parser.add_argument('-t', dest = 'trajectoryType', help = 'type of trajectories', choices = ['feature', 'object'], default = 'feature')
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33 parser.add_argument('--dry', dest = 'dryRun', help = 'dry run of processing', action = 'store_true')
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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 parser.add_argument('--subsample', dest = 'positionSubsamplingRate', help = 'rate of position subsampling (1 every n positions)', type = int)
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36
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37 ### process options
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38 # motion pattern learning and assignment
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39 parser.add_argument('--prototype-filename', dest = 'outputPrototypeDatabaseFilename', help = 'name of the Sqlite database file to save prototypes', default = 'prototypes.sqlite')
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40 #parser.add_argument('-i', dest = 'inputPrototypeDatabaseFilename', help = 'name of the Sqlite database file for prototypes to start the algorithm with')
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41 parser.add_argument('--nobjects-mp', dest = 'nMPObjects', help = 'number of objects/interactions to process', type = int)
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42 parser.add_argument('--nfeatures-per-object', dest = 'nLongestFeaturesPerObject', help = 'maximum number of features per object to load', type = int)
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43 parser.add_argument('--epsilon', dest = 'epsilon', help = 'distance for the similarity of trajectory points', type = float)
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44 parser.add_argument('--metric', dest = 'metric', help = 'metric for the similarity of trajectory points', default = 'cityblock') # default is manhattan distance
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45 parser.add_argument('--minsimil', dest = 'minSimilarity', help = 'minimum similarity to put a trajectory in a cluster', type = float)
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46 parser.add_argument('--min-cluster-size', dest = 'minClusterSize', help = 'minimum cluster size', type = int, default = 0)
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47 #parser.add_argument('--learn', dest = 'learn', help = 'learn', action = 'store_true')
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48 parser.add_argument('--optimize', dest = 'optimizeCentroid', help = 'recompute centroid at each assignment', action = 'store_true')
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49 parser.add_argument('--random', dest = 'randomInitialization', help = 'random initialization of clustering algorithm', action = 'store_true')
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50 #parser.add_argument('--similarities-filename', dest = 'similaritiesFilename', help = 'filename of the similarities')
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51 parser.add_argument('--save-similarities', dest = 'saveSimilarities', help = 'save computed similarities (in addition to prototypes)', action = 'store_true')
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52 parser.add_argument('--save-assignments', dest = 'saveAssignments', help = 'saves the assignments of the objects to the prototypes', action = 'store_true')
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53 parser.add_argument('--assign', dest = 'assign', help = 'assigns the objects to the prototypes and saves the assignments', action = 'store_true')
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54
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55 # safety analysis
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56 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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57 parser.add_argument('--pet', dest = 'computePET', help = 'computes PET', action = 'store_true')
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58 # override other tracking config, erase sqlite?
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59
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60
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61 # analysis options
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62 parser.add_argument('--output', dest = 'output', help = 'kind of output to produce (interval means)', choices = ['figure', 'interval', 'event'])
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63 parser.add_argument('--min-user-duration', dest = 'minUserDuration', help = 'mininum duration we have to see the user to take into account in the analysis (s)', type = float, default = 0.1)
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64 parser.add_argument('--interval-duration', dest = 'intervalDuration', help = 'length of time interval to aggregate data (min)', type = int, default = 15)
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65 parser.add_argument('--aggregation', dest = 'aggMethods', help = 'aggregation method per user/interaction and per interval', choices = ['mean', 'median', 'centile'], nargs = '*', default = ['median'])
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66 parser.add_argument('--aggregation-centile', dest = 'aggCentiles', help = 'centile(s) to compute from the observations', nargs = '*', type = int)
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67 parser.add_argument('--event-filename', dest = 'eventFilename', help = 'filename of the event data')
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68 dpi = 150
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69 # unit of analysis: site - camera-view
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70
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71 # need way of selecting sites as similar as possible to sql alchemy syntax
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72 # override tracking.cfg from db
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73 # manage cfg files, overwrite them (or a subset of parameters)
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74 # delete sqlite files
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75 # info of metadata
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76
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77 args = parser.parse_args()
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78
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79 #################################
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80 # Data preparation
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81 #################################
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82 session = connectDatabase(args.metadataFilename)
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83 parentPath = Path(args.metadataFilename).parent # files are relative to metadata location
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84 videoSequences = []
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85 sites = []
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86 if args.videoIds is not None:
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87 for videoId in args.videoIds:
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88 if '-' in videoId:
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89 videoSequences.extend([session.query(VideoSequence).get(i) for i in moving.TimeInterval.parse(videoId)])
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90 else:
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91 videoSequences.append(session.query(VideoSequence).get(int(videoId)))
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92 videoSequences = [vs for vs in videoSequences if vs is not None]
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93 sites = set([vs.cameraView.site for vs in videoSequences])
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94 elif args.siteIds is not None:
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95 for siteId in args.siteIds:
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96 if '-' in siteId:
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97 sites.extend([session.query(Site).get(i) for i in moving.TimeInterval.parse(siteId)])
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98 else:
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99 sites.append(session.query(Site).get(int(siteId)))
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100 sites = [s for s in sites if s is not None]
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101 for site in sites:
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102 videoSequences.extend(getSiteVideoSequences(site))
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103 else:
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104 print('No video/site to process')
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105
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106 if args.nProcesses > 1:
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107 pool = Pool(args.nProcesses)
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108
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109 #################################
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110 # Report progress in the processing
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111 #################################
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112 if args.progress:
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113 print('Providing information on data progress')
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114 headers = ['site', 'vs', 'features', 'objects', 'interactions'] # todo add prototypes and object classification
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115 data = []
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parents: 1064
diff changeset
116 for site in sites:
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diff changeset
117 unprocessedVideoSequences = []
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diff changeset
118 for vs in getSiteVideoSequences(site):
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parents: 1065
diff changeset
119 if (parentPath/vs.getDatabaseFilename()).is_file(): # TODO check time of file?
1065
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diff changeset
120 tableNames = storage.tableNames(str(parentPath.absolute()/vs.getDatabaseFilename()))
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121 data.append([site.name, vs.idx, 'positions' in tableNames, 'objects' in tableNames, 'interactions' in tableNames])
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diff changeset
122 else:
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parents: 1064
diff changeset
123 unprocessedVideoSequences.append(vs)
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diff changeset
124 data.append([site.name, vs.idx, False, False, False])
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parents: 1064
diff changeset
125 #if len(unprocessedVideoSequences):
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diff changeset
126 # print('Site {} ({}) has {} completely unprocessed video sequences'.format (site.name, site.idx, len(unprocessedVideoSequences)))
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127 data = pd.DataFrame(data, columns = headers)
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diff changeset
128 print('-'*80)
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129 print('\t'+' '.join(headers[2:]))
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parents: 1064
diff changeset
130 print('-'*80)
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diff changeset
131 for name, group in data.groupby(['site']): #.agg({'vs': 'count'}))
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132 n = group.vs.count()
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diff changeset
133 print('{}: {} % / {} % / {} % ({})'.format(name, 100*group.features.sum()/float(n), 100*group.objects.sum()/float(n), 100*group.interactions.sum()/float(n), n))
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134 print('-'*80)
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diff changeset
135 print(data)
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parents: 1062
diff changeset
136
3c37d8d20e97 minor addition to process.py
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1062
diff changeset
137 #################################
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
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diff changeset
138 # Delete
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139 #################################
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140 if args.delete is not None:
1009
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parents: 1007
diff changeset
141 if args.delete == 'feature':
1026
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1023
diff changeset
142 response = input('Are you sure you want to delete the tracking results (SQLite files) of all these sites (y/n)?')
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diff changeset
143 if response == 'y':
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parents: 1023
diff changeset
144 for vs in videoSequences:
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145 p = parentPath.absolute()/vs.getDatabaseFilename()
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
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diff changeset
146 p.unlink()
1009
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147 elif args.delete in ['object', 'interaction']:
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diff changeset
148 #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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149 for vs in videoSequences:
1021
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
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diff changeset
150 storage.deleteFromSqlite(str(parentPath/vs.getDatabaseFilename()), args.delete)
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parents: 983
diff changeset
151
1009
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diff changeset
152 #################################
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diff changeset
153 # Process
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diff changeset
154 #################################
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parents: 998
diff changeset
155 if args.process in ['feature', 'object']: # tracking
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parents: 1003
diff changeset
156 if args.nProcesses == 1:
1009
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parents: 1007
diff changeset
157 for vs in videoSequences:
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parents: 1064
diff changeset
158 if not (parentPath/vs.getDatabaseFilename()).is_file() or args.process == 'object':
1009
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parents: 1007
diff changeset
159 if args.configFilename is None:
1021
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parents: 1009
diff changeset
160 configFilename = str(parentPath/vs.cameraView.getTrackingConfigurationFilename())
1009
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parents: 1007
diff changeset
161 else:
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parents: 1007
diff changeset
162 configFilename = args.configFilename
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parents: 1007
diff changeset
163 if vs.cameraView.cameraType is None:
1021
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1009
diff changeset
164 cvutils.tracking(configFilename, args.process == 'object', str(parentPath.absolute()/vs.getVideoSequenceFilename()), str(parentPath.absolute()/vs.getDatabaseFilename()), str(parentPath.absolute()/vs.cameraView.getHomographyFilename()), str(parentPath.absolute()/vs.cameraView.getMaskFilename()), False, None, None, args.dryRun)
1066
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parents: 1065
diff changeset
165 else: #caution: cameratype can be not none, but without parameters for undistortion
1021
16932cefabc1 work on paths in line with new configurations from tracker
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1009
diff changeset
166 cvutils.tracking(configFilename, args.process == 'object', str(parentPath.absolute()/vs.getVideoSequenceFilename()), str(parentPath.absolute()/vs.getDatabaseFilename()), str(parentPath.absolute()/vs.cameraView.getHomographyFilename()), str(parentPath.absolute()/vs.cameraView.getMaskFilename()), True, vs.cameraView.cameraType.intrinsicCameraMatrix, vs.cameraView.cameraType.distortionCoefficients, args.dryRun)
1009
0d29b75f74ea cleaning
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1007
diff changeset
167 else:
1021
16932cefabc1 work on paths in line with new configurations from tracker
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1009
diff changeset
168 print('SQLite already exists: {}'.format(parentPath/vs.getDatabaseFilename()))
1004
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1003
diff changeset
169 else:
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parents: 1003
diff changeset
170 for vs in videoSequences:
1065
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parents: 1064
diff changeset
171 if not (parentPath/vs.getDatabaseFilename()).is_file() or args.process == 'object':
1004
75601be6019f work on process
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1003
diff changeset
172 if args.configFilename is None:
1021
16932cefabc1 work on paths in line with new configurations from tracker
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1009
diff changeset
173 configFilename = str(parentPath/vs.cameraView.getTrackingConfigurationFilename())
1004
75601be6019f work on process
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1003
diff changeset
174 else:
75601be6019f work on process
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1003
diff changeset
175 configFilename = args.configFilename
75601be6019f work on process
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1003
diff changeset
176 if vs.cameraView.cameraType is None:
1021
16932cefabc1 work on paths in line with new configurations from tracker
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1009
diff changeset
177 pool.apply_async(cvutils.tracking, args = (configFilename, args.process == 'object', str(parentPath.absolute()/vs.getVideoSequenceFilename()), str(parentPath.absolute()/vs.getDatabaseFilename()), str(parentPath.absolute()/vs.cameraView.getHomographyFilename()), str(parentPath.absolute()/vs.cameraView.getMaskFilename()), False, None, None, args.dryRun))
1004
75601be6019f work on process
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1003
diff changeset
178 else:
1021
16932cefabc1 work on paths in line with new configurations from tracker
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1009
diff changeset
179 pool.apply_async(cvutils.tracking, args = (configFilename, args.process == 'object', str(parentPath.absolute()/vs.getVideoSequenceFilename()), str(parentPath.absolute()/vs.getDatabaseFilename()), str(parentPath.absolute()/vs.cameraView.getHomographyFilename()), str(parentPath.absolute()/vs.cameraView.getMaskFilename()), True, vs.cameraView.cameraType.intrinsicCameraMatrix, vs.cameraView.cameraType.distortionCoefficients, args.dryRun))
1004
75601be6019f work on process
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1003
diff changeset
180 else:
1021
16932cefabc1 work on paths in line with new configurations from tracker
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1009
diff changeset
181 print('SQLite already exists: {}'.format(parentPath/vs.getDatabaseFilename()))
1004
75601be6019f work on process
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1003
diff changeset
182 pool.close()
75601be6019f work on process
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1003
diff changeset
183 pool.join()
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1003
diff changeset
184
1039
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1036
diff changeset
185 elif args.process == 'prototype': # motion pattern learning
1050
9d4a06f49cb8 work in progress
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1049
diff changeset
186 # learn by site by default -> group videos by camera view TODO
1045
25db2383e7ae work in progress on process.py
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1044
diff changeset
187 # by default, load all objects, learn and then assign (BUT not save the assignments)
25db2383e7ae work in progress on process.py
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1044
diff changeset
188 for site in sites:
1048
27a822922cb0 work in progress
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1047
diff changeset
189 print('Learning motion patterns for site {} ({})'.format(site.idx, site.name))
1045
25db2383e7ae work in progress on process.py
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1044
diff changeset
190 objects = {}
25db2383e7ae work in progress on process.py
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1044
diff changeset
191 object2VideoSequences = {}
25db2383e7ae work in progress on process.py
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1044
diff changeset
192 for cv in site.cameraViews:
25db2383e7ae work in progress on process.py
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1044
diff changeset
193 for vs in cv.videoSequences:
25db2383e7ae work in progress on process.py
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1044
diff changeset
194 print('Loading '+vs.getDatabaseFilename())
1046
f2ba9858e6c6 motion pattern learning seems to work
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1045
diff changeset
195 objects[vs.idx] = storage.loadTrajectoriesFromSqlite(str(parentPath/vs.getDatabaseFilename()), args.trajectoryType, args.nObjects, timeStep = args.positionSubsamplingRate, nLongestFeaturesPerObject = args.nLongestFeaturesPerObject)
1045
25db2383e7ae work in progress on process.py
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1044
diff changeset
196 if args.trajectoryType == 'object' and args.nLongestFeaturesPerObject is not None:
25db2383e7ae work in progress on process.py
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1044
diff changeset
197 objectsWithFeatures = objects[vs.idx]
25db2383e7ae work in progress on process.py
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1044
diff changeset
198 objects[vs.idx] = [f for o in objectsWithFeatures for f in o.getFeatures()]
25db2383e7ae work in progress on process.py
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1044
diff changeset
199 prototypeType = 'feature'
25db2383e7ae work in progress on process.py
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1044
diff changeset
200 else:
25db2383e7ae work in progress on process.py
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1044
diff changeset
201 prototypeType = args.trajectoryType
25db2383e7ae work in progress on process.py
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1044
diff changeset
202 for obj in objects[vs.idx]:
25db2383e7ae work in progress on process.py
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1044
diff changeset
203 object2VideoSequences[obj] = vs
25db2383e7ae work in progress on process.py
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1044
diff changeset
204 lcss = utils.LCSS(metric = args.metric, epsilon = args.epsilon)
25db2383e7ae work in progress on process.py
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1044
diff changeset
205 similarityFunc = lambda x,y : lcss.computeNormalized(x, y)
1048
27a822922cb0 work in progress
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1047
diff changeset
206 trainingObjects = [o for tmpobjects in objects.values() for o in tmpobjects]
1049
c9c03c97ed9f bug fix to store numpy integers in SQLite
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1048
diff changeset
207 if args.nMPObjects is not None and args.nMPObjects < len(trainingObjects):
1048
27a822922cb0 work in progress
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1047
diff changeset
208 m = int(np.floor(float(len(trainingObjects))/args.nMPObjects))
27a822922cb0 work in progress
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1047
diff changeset
209 trainingObjects = trainingObjects[::m]
27a822922cb0 work in progress
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1047
diff changeset
210 similarities = -np.ones((len(trainingObjects), len(trainingObjects)))
27a822922cb0 work in progress
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1047
diff changeset
211 prototypeIndices, labels = processing.learnAssignMotionPatterns(True, True, trainingObjects, similarities, args.minSimilarity, similarityFunc, args.minClusterSize, args.optimizeCentroid, args.randomInitialization, True, [])
1045
25db2383e7ae work in progress on process.py
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1044
diff changeset
212 if args.outputPrototypeDatabaseFilename is None:
25db2383e7ae work in progress on process.py
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1044
diff changeset
213 outputPrototypeDatabaseFilename = args.databaseFilename
25db2383e7ae work in progress on process.py
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1044
diff changeset
214 else:
25db2383e7ae work in progress on process.py
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1044
diff changeset
215 outputPrototypeDatabaseFilename = args.outputPrototypeDatabaseFilename
25db2383e7ae work in progress on process.py
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1044
diff changeset
216 clusterSizes = ml.computeClusterSizes(labels, prototypeIndices, -1)
1048
27a822922cb0 work in progress
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1047
diff changeset
217 storage.savePrototypesToSqlite(str(parentPath/site.getPath()/outputPrototypeDatabaseFilename), [moving.Prototype(object2VideoSequences[trainingObjects[i]].getDatabaseFilename(False), trainingObjects[i].getNum(), prototypeType, clusterSizes[i]) for i in prototypeIndices])
1043
b735895c8815 work in progress on process (learn motion patterns)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1039
diff changeset
218
1039
5621e4ad2428 removing prefix option to loadtrajectories from SQLite
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1036
diff changeset
219
1003
75af46516b2b work in progress
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 998
diff changeset
220 elif args.process == 'interaction':
985
668a85c963c3 work on processing and managing large video datasets
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 984
diff changeset
221 # safety analysis TODO make function in safety analysis script
987
f026ce2af637 found bug with direct ttc computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 986
diff changeset
222 if args.predictionMethod == 'cvd':
f026ce2af637 found bug with direct ttc computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 986
diff changeset
223 predictionParameters = prediction.CVDirectPredictionParameters()
f026ce2af637 found bug with direct ttc computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 986
diff changeset
224 if args.predictionMethod == 'cve':
f026ce2af637 found bug with direct ttc computation
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 986
diff changeset
225 predictionParameters = prediction.CVExactPredictionParameters()
1009
0d29b75f74ea cleaning
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1007
diff changeset
226 for vs in videoSequences:
985
668a85c963c3 work on processing and managing large video datasets
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 984
diff changeset
227 print('Processing '+vs.getDatabaseFilename())
1021
16932cefabc1 work on paths in line with new configurations from tracker
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1009
diff changeset
228 objects = storage.loadTrajectoriesFromSqlite(str(parentPath/vs.getDatabaseFilename()), 'object')#, args.nObjects, withFeatures = (params.useFeaturesForPrediction or predictionMethod == 'ps' or predictionMethod == 'mp'))
985
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 984
diff changeset
229 interactions = events.createInteractions(objects)
668a85c963c3 work on processing and managing large video datasets
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 984
diff changeset
230 #if args.nProcesses == 1:
1021
16932cefabc1 work on paths in line with new configurations from tracker
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1009
diff changeset
231 #print(str(parentPath/vs.cameraView.getTrackingConfigurationFilename()))
16932cefabc1 work on paths in line with new configurations from tracker
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 1009
diff changeset
232 params = storage.ProcessParameters(str(parentPath/vs.cameraView.getTrackingConfigurationFilename()))
985
668a85c963c3 work on processing and managing large video datasets
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 984
diff changeset
233 #print(len(interactions), args.computePET, predictionParameters, params.collisionDistance, params.predictionTimeHorizon, params.crossingZones)
668a85c963c3 work on processing and managing large video datasets
Nicolas Saunier <nicolas.saunier@polymtl.ca>
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diff changeset
234 processed = events.computeIndicators(interactions, True, args.computePET, predictionParameters, params.collisionDistance, params.predictionTimeHorizon, params.crossingZones, False, None)
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235 storage.saveIndicatorsToSqlite(str(parentPath/vs.getDatabaseFilename()), processed)
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236 # else:
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237 # pool = Pool(processes = args.nProcesses)
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238 # nInteractionPerProcess = int(np.ceil(len(interactions)/float(args.nProcesses)))
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239 # 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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240 # processed = []
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241 # for job in jobs:
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242 # processed += job.get()
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243 # pool.close()
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244
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245 #################################
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246 # Analyze
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247 #################################
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248 if args.analyze == 'object':
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249 # user speeds, accelerations
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250 # aggregation per site
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251 data = [] # list of observation per site-user with time
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252 headers = ['site', 'date', 'time', 'user_type']
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253 aggFunctions, tmpheaders = utils.aggregationMethods(args.aggMethods, args.aggCentiles)
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254 headers.extend(tmpheaders)
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255 if args.nProcesses == 1:
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256 for vs in videoSequences:
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257 data.extend(processing.extractVideoSequenceSpeeds(str(parentPath/vs.getDatabaseFilename()), vs.cameraView.site.name, args.nObjects, vs.startTime, vs.cameraView.cameraType.frameRate, args.minUserDuration, aggFunctions))
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258 else:
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259 jobs = [pool.apply_async(processing.extractVideoSequenceSpeeds, args = (str(parentPath/vs.getDatabaseFilename()), vs.cameraView.site.name, args.nObjects, vs.startTime, vs.cameraView.cameraType.frameRate, args.minUserDuration, aggFunctions)) for vs in videoSequences]
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260 for job in jobs:
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261 data.extend(job.get())
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262 pool.close()
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263
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264 data = pd.DataFrame(data, columns = headers)
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265 if args.output == 'figure':
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266 for name in headers[4:]:
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267 plt.ioff()
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268 plt.figure() # siteids does not exist
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269 plt.boxplot([data.loc[data['site']==site.name, name] for site in sites], labels = [site.name for site in sites])
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270 plt.ylabel(name+' Speeds (km/h)')
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271 plt.savefig(name.lower()+'-speeds.png', dpi=dpi)
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272 plt.close()
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273 elif args.output == 'event':
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274 data.to_csv(args.eventFilename, index = False)
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275
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276 if args.analyze == 'interaction': # redo as for object, export in dataframe all interaction data
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277 indicatorIds = [2,5,7,10]
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278 conversionFactors = {2: 1., 5: 30.*3.6, 7:1./30, 10:1./30}
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279 maxIndicatorValue = {2: float('inf'), 5: float('inf'), 7:10., 10:10.}
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280 indicators = {}
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281 interactions = {}
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282 for vs in videoSequences:
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283 if not vs.cameraView.siteIdx in interactions:
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284 interactions[vs.cameraView.siteIdx] = []
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285 indicators[vs.cameraView.siteIdx] = {}
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286 for i in indicatorIds:
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287 indicators[vs.cameraView.siteIdx][i] = []
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288 interactions[vs.cameraView.siteIdx] += storage.loadInteractionsFromSqlite(str(parentPath/vs.getDatabaseFilename()))
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289 print(vs.getDatabaseFilename(), len(interactions[vs.cameraView.siteIdx]))
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290 for inter in interactions[vs.cameraView.siteIdx]:
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291 for i in indicatorIds:
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292 indic = inter.getIndicator(events.Interaction.indicatorNames[i])
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293 if indic is not None:
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294 v = indic.getMostSevereValue()*conversionFactors[i]
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295 if v < maxIndicatorValue[i]:
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296 indicators[vs.cameraView.siteIdx][i].append(v)
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297
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298 for i in indicatorIds:
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299 tmp = [indicators[siteId][i] for siteId in indicators]
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300 plt.ioff()
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301 plt.figure()
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302 plt.boxplot(tmp, labels = [session.query(Site).get(siteId).name for siteId in indicators])
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303 plt.ylabel(events.Interaction.indicatorNames[i]+' ('+events.Interaction.indicatorUnits[i]+')')
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304 plt.savefig(events.Interaction.indicatorNames[i]+'.png', dpi=150)
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305 plt.close()
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306
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307 if args.analyze == 'event': # aggregate event data by 15 min interval (args.intervalDuration), count events with thresholds
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308 data = pd.read_csv(args.eventFilename, parse_dates = [2])
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309 #data = pd.read_csv('./speeds.csv', converters = {'time': lambda s: datetime.datetime.strptime(s, "%H:%M:%S").time()}, nrows = 5000)
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310 # create time for end of each 15 min, then group by, using the agg method for each data column
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311 headers = ['site', 'date', 'intervalend15', 'duration', 'count']
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diff changeset
312 aggFunctions, tmpheaders = utils.aggregationMethods(args.aggMethods, args.aggCentiles)
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313 dataColumns = list(data.columns[4:])
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314 for h in dataColumns:
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315 for h2 in tmpheaders:
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diff changeset
316 headers.append(h+'-'+h2)
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diff changeset
317 data['intervalend15'] = data.time.apply(lambda t: (pd.Timestamp(year = t.year, month = t.month, day = t.day,hour = t.hour, minute = (t.minute // args.intervalDuration)*args.intervalDuration)+pd.Timedelta(minutes = 15)).time())
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318 outputData = []
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319 for name, group in data.groupby(['site', 'date', 'intervalend15']):
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320 # get duration as intervalend15-min(time), apply agg methods to each centile
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diff changeset
321 row = []
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322 row.extend(name)
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323 row.append((name[2].minute-group.time.min().minute) % 60)
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324 row.append(len(group))
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325 for h in dataColumns:
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326 for method,func in aggFunctions.items():
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327 aggregated = func(group[h])
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328 if method == 'centile':
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329 row.extend(aggregated)
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330 else:
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331 row.append(aggregated)
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332 outputData.append(row)
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diff changeset
333 pd.DataFrame(outputData, columns = headers).to_csv(utils.removeExtension(args.eventFilename)+'-aggregated.csv', index = False)