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import numpy as np
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from feature_extraction.feature_extractor import extractFeatures
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from feature_extraction.batch_feature_extractor import batchExtract
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from preprocessing.data_preprocessing import arrayFromJSON, createSingleFeaturesArray, standardization, PCA
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from training.model_training import simpleTrain, kFCrossValid
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batchExtract('../dataset/music_wav/', 'feature_extraction/music_features/', 22050)
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batchExtract('../dataset/speech_wav/', 'feature_extraction/speech_features/', 22050)
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dataset, target, featureKeys = createSingleFeaturesArray(
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'feature_extraction/music_features/',
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'feature_extraction/speech_features/')
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dataset = standardization(dataset)
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# dataset = PCA(dataset)
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print('Simple train accuracy achieved = ' + str(simpleTrain(dataset, target)))
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kFCrossValid(dataset, target, model = 'svm')
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clf = kFCrossValid(dataset, target, model = 'rndForest')
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extractFeatures('compined.wav', 'featuresStream/tmp.json', 22050)
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values = arrayFromJSON('featuresStream/tmp.json')[1]
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values = standardization(values)
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audioClass = clf.predict(values)
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print(audioClass)
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