class RV(RecycleView):
# Initials
path = os.getcwd() + "/"
song = os.getcwd() + "/bird-sounds/"
bird_path = path + "bird-dir/bird-types.txt"
bird_names = open(bird_path, "r")
# Birds List
birds = initiate_birds()
# Birds and their songs Dictionary
libr = initiate_libr(birds)
def __init__(self, **kwargs):
super(RV, self).__init__(**kwargs)
tmp = list()
for x in self.libr.keys():
tmp.append(str(f'--{x}--'))
for y in self.libr.get(x):
tmp.append(y)
self.data = [{'text': str(x)} for x in tmp]
# ignore all future warnings
simplefilter(action='ignore', category=FutureWarning)
SAMPLE_RATE = 44100
#Initials
path = os.getcwd() + "/"
bird_path = path + "bird-dir/bird-types.txt"
bird_names = open(bird_path, "r")
pth = os.getcwd() + "/"
#Birds List
birds = initiate_birds()
#Birds and their songs Dictionary
libr = initiate_libr(birds)
#Read Dataset
train = pd.read_csv(f'{pth}train.csv')
test = pd.read_csv(f'{pth}test.csv')
train = pd.DataFrame(train)
test = pd.DataFrame(test)
def get_mfcc(name, path):
b, _ = librosa.core.load(name, sr=SAMPLE_RATE)
assert _ == SAMPLE_RATE
gmm = librosa.feature.mfcc(b, sr=SAMPLE_RATE, n_mfcc=20)
return pd.Series(np.hstack((np.mean(gmm, axis=1), np.std(gmm, axis=1))))
def Create():
SAMPLE_RATE = 44100
#Initials
path = os.getcwd() + "/"
song = os.getcwd() + "/bird-sounds/"
bird_path = path + "bird-dir/bird-types.txt"
bird_names = open(bird_path, "r")
#Birds List
birds = initiate_birds()
#Birds and their songs Dictionary
libr = initiate_libr(birds)
#Define train and test dicts
ones = open('train.csv', 'w').close()
zeros = open('test.csv', 'w').close()
train = dict()
test = dict()
for st in libr.keys():
train.update({st: []})
test.update({st: []})
#Init train and test dicts
for l in libr.keys():
counter = 0
for x in libr[l]:
if counter >= round(len(libr[l]) * 0.9):
test.update(l=test[l].append(x))
counter += 1
else:
train.update(l=train[l].append(x))
counter += 1
train.pop('l')
test.pop('l')
#x = open('train.csv', 'w+').close()
#Create train.csv
row = ['bird', 'song']
with open('train.csv', 'w') as csvFile:
writer = csv.writer(csvFile)
writer.writerow(row)
for t in train.keys():
for val in train[t]:
file = open('train.csv', 'a', newline='')
with file:
imp = t[:] + "~~" + song + t + "/" + val
writer = csv.writer(file)
writer.writerow(imp.split("~~"))
csvFile.close()
#Create test,csv
with open('test.csv', 'w') as csvFile:
writer = csv.writer(csvFile)
writer.writerow(row)
for t in test.keys():
for val in test[t]:
file = open('test.csv', 'a', newline='')
with file:
imp = t[:] + "~~" + song + t + "/" + val
writer = csv.writer(file)
writer.writerow(imp.split("~~"))
csvFile.close()