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26 lines
1.1 KiB
26 lines
1.1 KiB
import numpy as np
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import pandas as pd
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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, standardization, PCA
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from training.model_training import simpleTrain, kFCrossValid
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musicFeatures = batchExtract('../dataset/music_wav/', 'feature_extraction/music_features/', 22050)
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musicFeatures = musicFeatures.assign(target=0)
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speechFeatures = batchExtract('../dataset/speech_wav/', 'feature_extraction/speech_features/', 22050)
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speechFeatures = speechFeatures.assign(target=1)
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dataset = pd.concat([musicFeatures, speechFeatures])
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target = dataset.pop('target').values
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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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features = extractFeatures('compined.wav', 'tmp.json', 22050)
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features = standardization(features)
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audioClass = clf.predict(features)
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print(audioClass)
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