Mercurial Hosting > traffic-intelligence
changeset 1049:c9c03c97ed9f
bug fix to store numpy integers in SQLite
| author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
|---|---|
| date | Fri, 06 Jul 2018 15:58:45 -0400 |
| parents | 27a822922cb0 |
| children | 9d4a06f49cb8 d13f9bfbf3ff |
| files | scripts/process.py trafficintelligence/storage.py |
| diffstat | 2 files changed, 5 insertions(+), 3 deletions(-) [+] |
line wrap: on
line diff
--- a/scripts/process.py Fri Jul 06 11:13:10 2018 -0400 +++ b/scripts/process.py Fri Jul 06 15:58:45 2018 -0400 @@ -168,7 +168,7 @@ lcss = utils.LCSS(metric = args.metric, epsilon = args.epsilon) similarityFunc = lambda x,y : lcss.computeNormalized(x, y) trainingObjects = [o for tmpobjects in objects.values() for o in tmpobjects] - if args.nMPObjects is not None: + if args.nMPObjects is not None and args.nMPObjects < len(trainingObjects): m = int(np.floor(float(len(trainingObjects))/args.nMPObjects)) trainingObjects = trainingObjects[::m] similarities = -np.ones((len(trainingObjects), len(trainingObjects))) @@ -179,7 +179,6 @@ outputPrototypeDatabaseFilename = args.outputPrototypeDatabaseFilename # TODO maintain mapping from object prototype to db filename + compute nmatchings before clusterSizes = ml.computeClusterSizes(labels, prototypeIndices, -1) - #print([clusterSizes[i] for i in prototypeIndices]) storage.savePrototypesToSqlite(str(parentPath/site.getPath()/outputPrototypeDatabaseFilename), [moving.Prototype(object2VideoSequences[trainingObjects[i]].getDatabaseFilename(False), trainingObjects[i].getNum(), prototypeType, clusterSizes[i]) for i in prototypeIndices])
--- a/trafficintelligence/storage.py Fri Jul 06 11:13:10 2018 -0400 +++ b/trafficintelligence/storage.py Fri Jul 06 15:58:45 2018 -0400 @@ -7,7 +7,7 @@ from copy import copy import sqlite3, logging -from numpy import log, min as npmin, max as npmax, round as npround, array, sum as npsum, loadtxt, floor as npfloor, ceil as npceil, linalg +from numpy import log, min as npmin, max as npmax, round as npround, array, sum as npsum, loadtxt, floor as npfloor, ceil as npceil, linalg, int32, int64 from pandas import read_csv, merge from trafficintelligence import utils, moving, events, indicators @@ -22,6 +22,9 @@ 'object': 'objects', 'objectfeatures': 'positions'} +sqlite3.register_adapter(int64, lambda val: int(val)) +sqlite3.register_adapter(int32, lambda val: int(val)) + ######################### # Sqlite #########################