/
tester.py
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/
tester.py
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import os
import timeit
import numpy as np
from collections import defaultdict
from sklearn.metrics import precision_recall_curve, roc_curve
from sklearn.metrics import auc
from sklearn.cross_validation import ShuffleSplit
from sklearn.linear_model.logistic import LogisticRegression
from sklearn.metrics import confusion_matrix
from sklearn.externals import joblib
from utils import plot_roc, plot_confusion_matrix, GENRE_DIR, GENRE_LIST, TEST_DIR
from ceps import read_ceps, create_ceps, read_ceps_test
from pydub import AudioSegment
genre_list = GENRE_LIST
clf = None
#!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
# Please run the classifier script first
#!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
def test_model_on_single_file(file_path):
clf = joblib.load('data/model_ceps.pkl')
create_ceps(test_file)
fnpy = file_path[:-3]+"ceps.npy"
print fnpy
X, y = read_ceps_test(fnpy)
probs = clf.predict_proba(X)
print str(probs)
#print "\t".join(str(x) for x in traverse)
#print "\t".join(str("%.3f" % x) for x in probs[0])
probs=probs[0]
max_prob = max(probs)
for i,j in enumerate(probs):
if probs[i] == max_prob:
max_prob_index=i
print max_prob_index
predicted_genre = genre_list[max_prob_index]
print "\n\npredicted genre = ",predicted_genre
return predicted_genre
if __name__ == "__main__":
test_file = "/home/eduardo/Downloads/genres/test/reggae.wav"
# should predict genre as "ROCK"
predicted_genre = test_model_on_single_file(test_file)