Mercurial Hosting > traffic-intelligence
comparison trafficintelligence/processing.py @ 1066:862b55a87e63
work on extracting information
author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
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date | Mon, 16 Jul 2018 01:14:37 -0400 |
parents | 25db2383e7ae |
children | 092bd9c7deaf |
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1065:d4d052a05337 | 1066:862b55a87e63 |
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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) |