Mercurial > hg > nsaunier > traffic-intelligence

comparison scripts/train-object-classification.py @ 1226:d478d3122804

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change of bicycle to cyclist
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Wed, 12 Jul 2023 12:12:37 -0400
parents 933670761a57
children 5654c9173548
comparison
equal deleted inserted replaced
1225:202073959fb4 1226:d478d3122804
21 21
22 args = parser.parse_args() 22 args = parser.parse_args()
23 classifierParams = storage.ClassifierParameters(args.configFilename) 23 classifierParams = storage.ClassifierParameters(args.configFilename)
24 24
25 imageDirectories = {'pedestrian': args.directoryName + "/Pedestrians/", 25 imageDirectories = {'pedestrian': args.directoryName + "/Pedestrians/",
26 'bicycle': args.directoryName + "/Cyclists/", 26 'cyclist': args.directoryName + "/Cyclists/",
27 'car': args.directoryName + "/Vehicles/"} 27 'car': args.directoryName + "/Vehicles/"}
28 28
29 trainingSamplesPBV = {} 29 trainingSamplesPBV = {}
30 trainingLabelsPBV = {} 30 trainingLabelsPBV = {}
31 trainingSamplesBV = {} 31 trainingSamplesBV = {}
41 trainingSamplesPBV[k], trainingLabelsPBV[k] = trainingSamples, trainingLabels 41 trainingSamplesPBV[k], trainingLabelsPBV[k] = trainingSamples, trainingLabels
42 if k != 'pedestrian': 42 if k != 'pedestrian':
43 trainingSamplesBV[k], trainingLabelsBV[k] = trainingSamples, trainingLabels 43 trainingSamplesBV[k], trainingLabelsBV[k] = trainingSamples, trainingLabels
44 if k != 'car': 44 if k != 'car':
45 trainingSamplesPB[k], trainingLabelsPB[k] = trainingSamples, trainingLabels 45 trainingSamplesPB[k], trainingLabelsPB[k] = trainingSamples, trainingLabels
46 if k != 'bicycle': 46 if k != 'cyclist':
47 trainingSamplesPV[k], trainingLabelsPV[k] = trainingSamples, trainingLabels 47 trainingSamplesPV[k], trainingLabelsPV[k] = trainingSamples, trainingLabels
48 48
49 # Training the Support Vector Machine 49 # Training the Support Vector Machine
50 print("Training Pedestrian-Cyclist-Vehicle Model") 50 print("Training Pedestrian-Cyclist-Vehicle Model")
51 model = ml.SVM(args.svmType, args.kernelType, args.degree, args.gamma, args.coef0, args.cvalue, args.nu, args.svmP) 51 model = ml.SVM(args.svmType, args.kernelType, args.degree, args.gamma, args.coef0, args.cvalue, args.nu, args.svmP)