def __init__(self, input_file_name, output_file_name):
self.configure = Configure(0.7)
self.output_file_name = output_file_name
self.frames = wave.open(input_file_name, "rb")
self.binary_wav_data = self.frames.readframes(self.frames.getnframes())
# 如果if False 那么就没有 digit_wav_data 了
if self.configure.FORMAT == pyaudio.paInt16:
self.digit_wav_data = np.fromstring(self.binary_wav_data,
dtype=np.short)
else:
print("Error!->Configure.FORMAT != pyaudio.paInt16:")
sys.exit(-1)
self.input_size = len(self.digit_wav_data)
self.record_seconds = self.configure.RECORD_SECONDS
self.rate = self.configure.RATE
self.output_size = int(self.rate * self.record_seconds)
#存储处理之后的结果，预测len(self.wave_data_after)==self.output_size
self.wave_data_after = []
self.run()
self.save_file()
def save_file(self):
c=Configure()
wf = wave.open(self.output_file_name, 'wb')
wf.setnchannels(c.CHANNELS)
wf.setsampwidth(pyaudio.get_sample_size(c.FORMAT))
wf.setframerate(c.RATE)
wf.writeframes(b''.join(self.wave_data_after))
wf.close()
def __init__(self):
self.counts = 1
self.cur_num=0#本次录音的编号，0对应“前进”（labels）
self.labels=["前进","后退","左转","右转","停止","启动"]
self.format_dir()
self.label_len=len(self.labels)
# 对应编号的次数
self.times=[1]*len(self.labels)
self.user_name=""
self.font_size=12
self.window = Tk()
# 声明一个bar用来显示录音的进程
self.pro = Progressbar(self.window, length=200, style='black.Horizontal.TProgressbar')
# labels：
self.lb_name = Label(self.window, text="您的名字设置：", font=("Arial Bold", self.font_size))
self.lb_pro_left = Label(self.window, text="进度条：", font=("Arial Bold", self.font_size))
self.lb_pro_right = Label(self.window, text="0%", font=("Arial Bold", self.font_size))
# 需要设置text
self.lb_please = Label(self.window,foreground='red',text="请说："+self.labels[0], font=("Arial Bold", self.font_size))
# 这个设置成第i遍说相同的词，需要在初始化中进行更改
self.lb_times = Label(self.window, text="第1次", font=("Arial Bold", self.font_size))
self.lb_time_set = Label(self.window, text="时间长度设置：", font=("Arial Bold", self.font_size))
#Entry控件
self.et_name=Entry(self.window,width=15)
self.et_name.insert(0,'default')
self.et_time=Entry(self.window,width=15)
self.et_time.insert(0, '1.5')
self.begin_button=Button(self.window,text="录音",command=self.record_run)
self.save_button=Button(self.window,text="保存",command=self.save_wav)
#设置按钮的初始化状态
self.save_button['state']='disable'
# 保存每次录音的中间结果，然后决定是不是要保存。
self.frames=[]
self.p=[]
self.configure=Configure()
# 初始化每个组件的位置
self.place_all()
def run(self, binary_str, unit_time):
"""
:param binary_str: 外层录音所得到的二进制的字符串
:return: 返回识别的结果集合
"""
# digit_data = np.fromstring(binary_str, np.int16)
# plt.plot(list(range(len(digit_data))),digit_data)
# plt.show()
c = Configure(unit_time=unit_time)
wf = wave.open('before.wav', 'wb')
wf.setnchannels(c.CHANNELS)
wf.setsampwidth(pyaudio.get_sample_size(c.FORMAT))
wf.setframerate(c.RATE)
wf.writeframes(binary_str)
wf.close()
print("Identify ...")
print("录音的时间长度 %.2f" % (len(binary_str) / 32000))
p = ShorterWav('before.wav', 'after.wav')
result_dict = self.get_result('after.wav') # 识别语音指令
return result_dict
def recoder_and_decide(unit_time=0.3):
pa = PyAudio()
config = Configure(unit_time=unit_time)
times = 0
result_before = []
binary_str = b""
pre_str = b""
temp_binary_str = b""
print("begin_____________________")
is_recording,pre_is_recording = False, False
test_zcr_count = 0
while times < 100 or True:
stream = pa.open(format=config.FORMAT,
channels=config.CHANNELS,
rate=config.RATE,
input=True,
frames_per_buffer=config.CHUNK)
frames = []
times += 1
pre_is_recording = is_recording
pre_str = temp_binary_str
stream.start_stream()
for i in range(0, config.get_count_chunk()):
data = stream.read(config.CHUNK)
frames.append(data)
stream.stop_stream()
temp_binary_str = b''.join(frames)
digit_data = np.fromstring(temp_binary_str, np.int16)
zcr = ZCR(digit_data)
zcr_flag,energy_flag = zcr.get_weather_start_record_state()
is_recording = energy_flag or zcr_flag
# is_recording = zcr_flag or energy_flag
print(zcr_flag,energy_flag)
if zcr_flag:
test_zcr_count += 1
# print("zcr_rate = {},max_energy = {}".format(max(zcr_rate),max(energy)))
# zcr_flag = max(zcr_rate) > zcr.zcr_threshold
# energy_flag = max(energy) > zcr.energy_threshold
# print("max_zcr={},max_energy={}".format(max(zcr_rate),max(energy)))
# print("t={}s,z={},e={}".format(times*config.RECORD_SECONDS,zcr_flag,energy_flag))
# if zcr_flag or energy_flag:
# is_recording = True
# else
# is_recording = False
# result_before += list(digit_data)
if is_recording:
# print(type(binary_str),type(temp_binary_str))
if not pre_is_recording:
binary_str = pre_str
binary_str += temp_binary_str
print("Recording,time=%s" % str(len(binary_str)/32000))
print("\n__________________________________________")
# print("Recording@@@{}@@@{}".format(zcr_flag,energy_flag))
elif pre_is_recording:
# stop recording and start recognizing
print("test_zcr_count = %d" % test_zcr_count)
test_zcr_count = 0
print("Recognizing......")
sp = Recognition('./969_914.pb', './conv_labels.txt')
recognized_dict = sp.run(binary_str,unit_time)
print("识别结果：{}".format(recognized_dict))
binary_str = b""
else:
print("Finding")
# print("Finding+++{}+++{}".format(zcr_flag,energy_flag))
stream.stop_stream()
stream.close()
pa.terminate()
return None
def read_commit_file():
with open(conf.commit_database) as f:
content = f.readlines()
set_log_files()
content = [x.strip() for x in content]
for line_number, line in enumerate(content, start=conf.start_bug):
split_content = line.split(',')
bug_version = split_content[conf.bug_ind]
fix_version = split_content[conf.fix_ind]
if conf.start_bug <= line_number <= conf.end_bug:
try:
run_conf = RunConfigure(conf.root_dir, conf.project_name,
conf.clone_name, line_number,
fix_version, bug_version)
if exists(run_conf.trace_file):
run_prediction(line_number, fix_version, bug_version,
run_conf)
except Exception as e:
traceback.print_exc()
write_to_log_error(e, str(line_number))
if __name__ == '__main__':
if len(sys.argv) == 4:
conf = Configure(sys.argv[1], sys.argv[2], sys.argv[3])
file_address = FilesAddress(conf.root_dir)
read_commit_file()