Mercurial > hg > nsaunier > traffic-intelligence

comparison trafficintelligence/processing.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 25db2383e7ae
children 092bd9c7deaf
comparison
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1065:d4d052a05337 1066:862b55a87e63
1 #! /usr/bin/env python 1 #! /usr/bin/env python
2 '''Algorithms to process trajectories and moving objects''' 2 '''Algorithms to process trajectories and moving objects'''
3 3
4 import numpy as np 4 import numpy as np
5 5
6 from trafficintelligence import ml 6 from trafficintelligence import ml, storage, utils
7 7
8 def extractSpeeds(objects, zone): 8 def extractSpeeds(objects, zone):
9 speeds = {} 9 speeds = {}
10 objectsNotInZone = [] 10 objectsNotInZone = []
11 import matplotlib.nxutils as nx 11 import matplotlib.nxutils as nx
15 objspeeds = [o.getVelocityAt(i).norm2() for i in range(int(o.length()-1)) if inPolygon[i]] 15 objspeeds = [o.getVelocityAt(i).norm2() for i in range(int(o.length()-1)) if inPolygon[i]]
16 speeds[o.num] = np.mean(objspeeds) # km/h 16 speeds[o.num] = np.mean(objspeeds) # km/h
17 else: 17 else:
18 objectsNotInZone.append(o) 18 objectsNotInZone.append(o)
19 return speeds, objectsNotInZone 19 return speeds, objectsNotInZone
20
21 def extractVideoSequenceSpeeds(dbFilename, siteName, nObjects, startTime, frameRate, minUserDurationSeconds, aggFunctions):
22 data = []
23 d = startTime.date()
24 t1 = startTime.time()
25 minUserDuration = minUserDurationSeconds*frameRate
26 print('Extracting speed from '+dbFilename)
27 objects = storage.loadTrajectoriesFromSqlite(dbFilename, 'object', nObjects)
28 for o in objects:
29 if o.length() > minUserDuration:
30 row = [siteName, d, utils.framesToTime(o.getFirstInstant(), frameRate, t1), o.getUserType()]
31 tmp = o.getSpeeds()
32 for method,func in aggFunctions.items():
33 aggSpeeds = frameRate*3.6*func(tmp)
34 if method == 'centile':
35 row += aggSpeeds.tolist()
36 else:
37 row.append(aggSpeeds)
38 data.append(row)
39 return data
20 40
21 def learnAssignMotionPatterns(learn, assign, objects, similarities, minSimilarity, similarityFunc, minClusterSize = 0, optimizeCentroid = False, randomInitialization = False, removePrototypesAfterAssignment = False, initialPrototypes = []): 41 def learnAssignMotionPatterns(learn, assign, objects, similarities, minSimilarity, similarityFunc, minClusterSize = 0, optimizeCentroid = False, randomInitialization = False, removePrototypesAfterAssignment = False, initialPrototypes = []):
22 '''Learns motion patterns 42 '''Learns motion patterns
23 43
24 During assignments, if using minClusterSize > 0, prototypes can change (be removed) 44 During assignments, if using minClusterSize > 0, prototypes can change (be removed)