本文整理汇总了Python中extractor.Extractor.get_zcr_moy方法的典型用法代码示例。如果您正苦于以下问题：Python Extractor.get_zcr_moy方法的具体用法？Python Extractor.get_zcr_moy怎么用？Python Extractor.get_zcr_moy使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类extractor.Extractor的用法示例。
在下文中一共展示了Extractor.get_zcr_moy方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: __init__
# 需要导入模块: from extractor import Extractor [as 别名]
# 或者: from extractor.Extractor import get_zcr_moy [as 别名]
class Teacher:
def __init__(self):
self.model = SongModel()
self.extractor = Extractor()
def parse_set(self):
content = []
with open("training/Tracks/ground_truth.csv") as f:
for l in f:
l = l.replace('\"', '').replace('\n', '')
name = ""
genre = ""
flag = 0
for c in l:
if c == ',':
flag = 1
elif flag == 0:
name += c
elif flag == 1:
genre += c
content.append([name, genre])
return content
def train(self):
for item in self.parse_set():
self.extractor.set_song(item[0])
tempo = self.extractor.get_tempo()
rolloffmoy = self.extractor.get_rolloff_moy()
rolloffect = self.extractor.get_rolloff_ect()
zcrmoy = self.extractor.get_zcr_moy()
zcrect = self.extractor.get_zcr_ect()
duration = self.extractor.get_duration()
self.model.add(item[0], item[1], tempo, rolloffmoy, rolloffect, zcrmoy, zcrect, duration)
print("ADDED : " + item[0] + " " + item[1] + " " + str(tempo) + " " + str(rolloffmoy) + " " + str(rolloffect) + " " + str(zcrmoy) + " " + str(zcrect) + " " + str(duration))
print("DONE")示例2: __init__
# 需要导入模块: from extractor import Extractor [as 别名]
# 或者: from extractor.Extractor import get_zcr_moy [as 别名]
class AI:
def __init__(self, song):
self.song = song
self.model = SongModel()
self.extractor = Extractor()
self.tempo = 0
self.rolloffmoy = 0.0
self.rolloffect = 0.0
self.zcrmoy = 0.0
self.zcrect = 0.0
self.duration = 0.0
self.genre = []
for l in open("training/Tracks/genres.txt"):
self.genre.append(l.replace('\n',''))
def get_song_datas(self):
self.extractor.set_song(self.song)
self.tempo = self.extractor.get_tempo()
self.rolloffmoy = self.extractor.get_rolloff_moy()
self.rolloffect = self.extractor.get_rolloff_ect()
self.zcrmoy = self.extractor.get_zcr_moy()
self.zcrect = self.extractor.get_zcr_ect()
self.duration = self.extractor.get_duration()
def classify_with_knn(self):
vect, mat = self.model.get_datas()
clf = neighbors.KNeighborsClassifier()
clf.fit(mat, vect)
self.get_song_datas()
l = [[self.tempo, self.rolloffmoy, self.rolloffect, self.zcrmoy, self.zcrect, self.duration]]
ret = clf.predict(l)
print(self.genre[ret[0]])
def classify_with_svm(self):
vect, mat = self.model.get_datas()
clf = svm.SVC(class_weight='auto', kernel='linear')
clf.fit(mat, vect)
self.get_song_datas()
l = [[self.tempo, self.rolloffmoy, self.rolloffect, self.zcrmoy, self.zcrect, self.duration]]
ret = clf.predict(l)
print(self.genre[int(ret[0])])