view scripts/process.py @ 985:668a85c963c3

work on processing and managing large video datasets
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Tue, 06 Mar 2018 22:44:33 -0500
parents a69695d14e59
children 3be8aaa47651
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#! /usr/bin/env python

import sys, argparse
from pathlib2 import Path

import storage, events, prediction
from metadata import *

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.')
parser.add_argument('--db', dest = 'metadataFilename', help = 'name of the metadata file', required = True)
parser.add_argument('--videos', dest = 'videoIds', help = 'indices of the video sequences', nargs = '*', type = int)
parser.add_argument('--pet', dest = 'computePET', help = 'computes PET', action = 'store_true')
parser.add_argument('--delete', dest = 'delete', help = 'data to delete', choices = ['feature', 'object', 'classification', 'interaction'])
parser.add_argument('--process', dest = 'process', help = 'data to process', choices = ['feature', 'object', 'classification', 'interaction'])
parser.add_argument('--analyze', dest = 'analyze', help = 'data to analyze (results)', choices = ['feature', 'object', 'classification', 'interaction'])

# need way of selecting sites as similar as possible to sql alchemy syntax
# override tracking.cfg from db
# manage cfg files, overwrite them (or a subset of parameters)
# delete sqlite files

parser.add_argument('--nthreads', dest = 'nProcesses', help = 'number of processes to run in parallel', type = int, default = 1)

args = parser.parse_args()
# files are relative to metadata location

session = connectDatabase(args.metadataFilename)
parentDir = Path(args.metadataFilename).parent

if args.delete is not None:
    if args.delete in ['object', 'interaction']:
        #parser.add_argument('-t', dest = 'dataType', help = 'type of the data to remove', required = True, choices = ['object','interaction', 'bb', 'pois', 'prototype'])
        for videoId in args.videoIds:
            vs = session.query(VideoSequence).get(videoId)
            storage.deleteFromSqlite(str(parentDir/vs.getDatabaseFilename()), args.delete)

if args.process == 'interaction':
    # safety analysis TODO make function in safety analysis script
    predictionParameters = prediction.CVExactPredictionParameters()
    for videoId in args.videoIds:
        vs = session.query(VideoSequence).get(videoId)
        print('Processing '+vs.getDatabaseFilename())
        objects = storage.loadTrajectoriesFromSqlite(str(parentDir/vs.getDatabaseFilename()), 'object')#, args.nObjects, withFeatures = (params.useFeaturesForPrediction or predictionMethod == 'ps' or predictionMethod == 'mp'))
        interactions = events.createInteractions(objects)
        #if args.nProcesses == 1:
        #print(str(parentDir/vs.cameraView.getTrackingConfigurationFilename()))
        params = storage.ProcessParameters(str(parentDir/vs.cameraView.getTrackingConfigurationFilename()))
        #print(len(interactions), args.computePET, predictionParameters, params.collisionDistance, params.predictionTimeHorizon, params.crossingZones)
        processed = events.computeIndicators(interactions, True, args.computePET, predictionParameters, params.collisionDistance, params.predictionTimeHorizon, params.crossingZones, False, None)
        storage.saveIndicatorsToSqlite(str(parentDir/vs.getDatabaseFilename()), processed)
    # else:
    #     pool = Pool(processes = args.nProcesses)
    #     nInteractionPerProcess = int(np.ceil(len(interactions)/float(args.nProcesses)))
    #     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)]
    #     processed = []
    #     for job in jobs:
    #         processed += job.get()
    #     pool.close()

if args.analyze == 'interaction':
    indicatorIds = [2,5,7,10]
    indicators = {}
    interactions = {}
    for videoId in args.videoIds:
        vs = session.query(VideoSequence).get(videoId)
        if not vs.cameraView.siteIdx in interactions:
            interactions[vs.cameraView.siteIdx] = []
            for i in indicatorIds:
                indicators[events.Interaction.indicatorNames[i]][vs.cameraView.siteIdx] = []
        interactions[vs.cameraView.siteIdx].append(storage.loadInteractionsFromSqlite(str(parentDir/vs.getDatabaseFilename())))
        print(vs.getDatabaseFilename(), len(interactions))
        for inter in interactions[videoId]:
            for i in indicatorIds:
                indic = inter.getIndicator(events.Interaction.indicatorNames[i])
                if indic is not None:
                    indicators[events.Interaction.indicatorNames[i]][vs.cameraView.siteIdx].append(indic.getMostSevereValue())