def write_to_csv(location):
print "omer"
os.chdir(location)
for file in glob.glob("*.wav"):
print "omer"
mfcc = MFCC.extract_mfcc(file)
mfcc = np.hstack([np.ones((mfcc.shape[0], 1)), mfcc])
print mfcc.shape
with open("/home/omer/Desktop/Echo/Machine_Learning/Data_Gunshot.csv",
'a') as f_handle:
np.savetxt(f_handle, mfcc, delimiter=",")
def write_to_csv(fold0, fold_n, location):
count = 0
for i in range(fold0, fold_n):
path = location + st(
i) #"/home/Desktop/UrbanSound8K/UrbanSound8K/audio/fold" +str(i)
os.chdir(path)
print path
for file in glob.glob("*.wav"):
if (file.split('-')[1] == '6'):
mfcc = MFCC.extract_mfcc(file)
mfcc = np.hstack([np.ones((mfcc.shape[0], 1)), mfcc])
with open(
"/home/omer/Desktop/UrbanSound8K/UrbanSound8K/audio/Data_Gunskhdot.csv",
'a') as f_handle:
np.savetxt(f_handle, mfcc, delimiter=",")
def test_mfcc(self):
List=[[ -1.58999199e+02 , 8.34436590e+00, -4.44382643e+01, -1.05713490e+01,
-4.14216808e+00 , 5.43735320e+00 ,-6.23641973e+00, 1.13643816e+01,
1.11168843e+01 ,2.09593413e+01 , 2.08886976e+01 , 1.78893376e+01,
-1.85126261e+00 ,1.98630431e+00 ,-3.58780406e+00 , 1.07466142e+01,
4.06712767e+00 , -3.77452706e+00 ,-9.57172794e+00 ,2.71010408e+00,
2.28370949e-01 ,-1.67914367e+00 ,-2.70335598e+00 ,9.36659239e+00,
-1.06643306e+00 , -4.19447993e+00 ,-1.55310523e+00 ,9.63509903e+00,
-2.36770851e+00 , 1.16768921e+00 ,1.74342284e+00 , -6.92783306e-01,
-2.74215299e+00 , 7.46808225e+00 ,-3.92998483e+00 ,-1.10826282e+00,
2.49712828e+00, -1.59097153e+00 , -5.17096235e+00 , 3.18161592e+00,
-4.68084505e+00 , 4.28643721e+00, -3.98783991e-01 ,-4.31620744e+00,
1.85530792e+00 , 1.94520311e+00 ,-3.32610635e+00 , 5.60897361e+00,
-1.59248264e+00 ,3.31523211e+00 , 3.20098072e-01 , 3.58511203e-01,
3.37264297e+00, -1.70320401e+00 , -1.18435935e-01 , 1.40946029e+00,
-4.82136239e+00 , 3.66574126e+00, -1.98897953e+00 ,1.42700455e+00]]
self.assertListEqual(List,list( MFCC.extract_mfcc("/home/omer/Desktop/UrbanSound8K/UrbanSound8K/audio/fold1/7061-6-0-0.wav")))
