def main():
for label, genre in enumerate(GENRE_LIST):
for fn in glob.glob(os.path.join(GENRE_DIR, genre)):
for wavfile in os.listdir(fn):
if wavfile.endswith("wav"):
print(genre)
create_ceps(os.path.join(GENRE_DIR, genre, wavfile))
def main():
for label, dialect in enumerate(DIALECT_LIST):
for fn in glob.glob(os.path.join(DIALECT_DIR, dialect)):
for wavfile in os.listdir(fn):
if wavfile.endswith("wav"):
create_ceps(os.path.join(DIALECT_DIR, dialect, wavfile))
def main_function(docName):
'''
docName is the string which tells the name of the file to be downloaded.
Returns :
1. Success message
2. full file location (to download later)
'''
for wavfile in os.listdir(MEDIA_ROOT):
if wavfile.endswith("wav"):
if wavfile == docName:
# for FFT Features :
create_fft(os.path.join(MEDIA_ROOT + wavfile))
# for MFCC Features :
#create_ceps(os.path.join(MEDIA_ROOT + wavfile))
# for STFT Features :
#create_stft_feature(os.path.join(MEDIA_ROOT + wavfile))
# for DWT Features :
#create_dwt_feature(os.path.join(MEDIA_ROOT + wavfile))
# for FFT :
df_feature_1 = pd.DataFrame(function_dict_1)
# for MFCC :
df_feature_2 = pd.DataFrame(function_dict_2)
# for STFT :
df_feature_3 = pd.DataFrame(function_dict_3).astype(str)
# for DWT :
df_feature_4 = pd.DataFrame(function_dict_4)
# combining them all :
df = pd.concat(
[df_feature_1, df_feature_2, df_feature_3, df_feature_4],
ignore_index=False,
axis=1)
#print(df.head())
# to get the file name.
base_fn, ext = os.path.splitext(wavfile)
fname = base_fn + ".xlsx"
full_file_loc = MEDIA_ROOT + 'convFiles/' + fname
writer = ExcelWriter(full_file_loc)
df.to_excel(writer, 'Sheet1', index=False)
writer.save()
return ("File " + fname + " created!", full_file_loc)
import sys
import os
import scipy.io.wavfile
import scipy.signal
import matplotlib.pyplot as plt
# from matplotlib.pyplot import specgram
os.chdir(sys.argv[1])
# Directory provided as a command line argument will be opened to visualize the files inside
wavfiles = []
for wavfile in os.listdir(sys.argv[1]):
if wavfile.endswith("wav"):
wavfiles.append(wavfile)
wavfiles.sort()
# Declare sampling rates and song arrays for each arg
sampling_rates = []
song_arrays = []
# Read wavfiles
for wavfile in wavfiles:
sampling_rate, song_array = scipy.io.wavfile.read(wavfile)
sampling_rates.append(sampling_rate)
song_arrays.append(song_array)
i = 1 # plot number
# Plot spectrogram for each wave_file