Mercurial Hosting > traffic-intelligence

comparison scripts/process.py @ 987:f026ce2af637

Find changesets by keywords (author, files, the commit message), revision number or hash, or revset expression.
found bug with direct ttc computation
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Wed, 07 Mar 2018 23:37:00 -0500
parents 3be8aaa47651
children dc0be55e2bf5
comparison
equal deleted inserted replaced
986:3be8aaa47651 987:f026ce2af637
11 from metadata import * 11 from metadata import *
12 12
13 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.') 13 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.')
14 parser.add_argument('--db', dest = 'metadataFilename', help = 'name of the metadata file', required = True) 14 parser.add_argument('--db', dest = 'metadataFilename', help = 'name of the metadata file', required = True)
15 parser.add_argument('--videos', dest = 'videoIds', help = 'indices of the video sequences', nargs = '*', type = int) 15 parser.add_argument('--videos', dest = 'videoIds', help = 'indices of the video sequences', nargs = '*', type = int)
16 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'])
16 parser.add_argument('--pet', dest = 'computePET', help = 'computes PET', action = 'store_true') 17 parser.add_argument('--pet', dest = 'computePET', help = 'computes PET', action = 'store_true')
17 parser.add_argument('--delete', dest = 'delete', help = 'data to delete', choices = ['feature', 'object', 'classification', 'interaction']) 18 parser.add_argument('--delete', dest = 'delete', help = 'data to delete', choices = ['feature', 'object', 'classification', 'interaction'])
18 parser.add_argument('--process', dest = 'process', help = 'data to process', choices = ['feature', 'object', 'classification', 'interaction']) 19 parser.add_argument('--process', dest = 'process', help = 'data to process', choices = ['feature', 'object', 'classification', 'interaction'])
19 parser.add_argument('--analyze', dest = 'analyze', help = 'data to analyze (results)', choices = ['feature', 'object', 'classification', 'interaction']) 20 parser.add_argument('--analyze', dest = 'analyze', help = 'data to analyze (results)', choices = ['feature', 'object', 'classification', 'interaction'])
20 21
38 vs = session.query(VideoSequence).get(videoId) 39 vs = session.query(VideoSequence).get(videoId)
39 storage.deleteFromSqlite(str(parentDir/vs.getDatabaseFilename()), args.delete) 40 storage.deleteFromSqlite(str(parentDir/vs.getDatabaseFilename()), args.delete)
40 41
41 if args.process == 'interaction': 42 if args.process == 'interaction':
42 # safety analysis TODO make function in safety analysis script 43 # safety analysis TODO make function in safety analysis script
43 predictionParameters = prediction.CVDirectPredictionParameters()#prediction.CVExactPredictionParameters() 44 if args.predictionMethod == 'cvd':
45 predictionParameters = prediction.CVDirectPredictionParameters()
46 if args.predictionMethod == 'cve':
47 predictionParameters = prediction.CVExactPredictionParameters()
44 for videoId in args.videoIds: 48 for videoId in args.videoIds:
45 vs = session.query(VideoSequence).get(videoId) 49 vs = session.query(VideoSequence).get(videoId)
46 print('Processing '+vs.getDatabaseFilename()) 50 print('Processing '+vs.getDatabaseFilename())
47 objects = storage.loadTrajectoriesFromSqlite(str(parentDir/vs.getDatabaseFilename()), 'object')#, args.nObjects, withFeatures = (params.useFeaturesForPrediction or predictionMethod == 'ps' or predictionMethod == 'mp')) 51 objects = storage.loadTrajectoriesFromSqlite(str(parentDir/vs.getDatabaseFilename()), 'object')#, args.nObjects, withFeatures = (params.useFeaturesForPrediction or predictionMethod == 'ps' or predictionMethod == 'mp'))
48 interactions = events.createInteractions(objects) 52 interactions = events.createInteractions(objects)