#！/usr/bin/env python
import requests
import json
import base64
import pyaudio
import wave
import os
import psutil


#首先配置必要的信息
def bat(voice_path):
  baidu_server = 'https://aip.baidubce.com/oauth/2.0/token"wate_play"
  #读取文件二进制内容
  f_obj = open(FILE_NAME, 'rb')
  content = base64.b64encode(f_obj.read())  # 百度语音识别需要base64编码格式
  speech = content.decode("utf-8")
  size = os.path.getsize(FILE_NAME)

  #json封装
  datas = json.dumps({
    'format': FILE_TYPE,
    'rate': VOICE_RATE,
    'channel': 1,
    'cuid': CUID,
    'token': token,
    'speech': speech,
    'len': size,
    "dev_pid":"1536"
  })
  return datas

#设置headers和请求地址url
def post(datas):
  headers = {'Content-Type':'application/json'}
  url = 'https://vop.baidu.com/server_api'
  # url = "http://vop.baidu.com/server_api"

  #用post方法传数据
  request = requests.post(url, datas, headers)
  result = json.loads(request.text)
  text = result.get("result")
  if result['err_no'] == 0:
    return text
  else:
    return "Error"


def get_audio(filepath):
  input("回车开始录音 >")   #输出提示文本，input接收一个值,转为str，赋值给aa
  CHUNK = 256         #定义数据流块
  FORMAT = pyaudio.paInt16  #量化位数（音量级划分）
  CHANNELS = 1        # 声道数;声道数：可以是单声道或者是双声道
  RATE = 8000        # 采样率;采样率：一秒内对声音信号的采集次数，常用的有8kHz, 16kHz, 32kHz, 48kHz, 11.025kHz, 22.05kHz, 44.1kHz
  RECORD_SECONDS = 5     #录音秒数
  WAVE_OUTPUT_FILENAME = filepath   #wav文件路径
  p = pyaudio.PyAudio()        #实例化

  stream = p.open(format=FORMAT,
          channels=CHANNELS,
          rate=RATE,
          input=True,
          frames_per_buffer=CHUNK)
  print("*"*10, "开始录音：请在5秒内输入语音")
  frames = []                         #定义一个列表
  for i in range(0, int(RATE / CHUNK * RECORD_SECONDS)):   #循环，采样率11025 / 256 * 5
    data = stream.read(CHUNK)                #读取chunk个字节 保存到data中
    frames.append(data)                   #向列表frames中添加数据data
  # print(frames)
  print("*" * 10, "录音结束\n")

  stream.stop_stream()
  stream.close()     #关闭
  p.terminate()      #终结

  wf = wave.open(WAVE_OUTPUT_FILENAME, 'wb')         #打开wav文件创建一个音频对象wf，开始写WAV文件
  wf.setnchannels(CHANNELS)                  #配置声道数
  wf.setsampwidth(p.get_sample_size(FORMAT))         #配置量化位数
  wf.setframerate(RATE)                    #配置采样率
  wf.writeframes(b''.join(frames))              #转换为二进制数据写入文件
  wf.close()       #关闭
  return


def check_disk():
  list_drive = psutil.disk_partitions() # 找出本地磁盘列表，保存的是结构体对象
  list_disk = []
  for drive in list_drive:
    list_disk.append(drive.device)
  return list_disk


if __name__ == '__main__':
  list_disk = check_disk() # 检索本地磁盘
  dirname_path = os.path.join(list_disk[0], "voice") # 设置语音文件存放路径， 
                                  （mac os下需要自己定存储路径）
  if not os.path.exists(dirname_path):
    os.makedirs(dirname_path)

  filename = "voice.wav" # 定义语音文件名
  in_path = os.path.join(dirname_path, filename)

  get_audio(in_path) # 录音

  datas = bat(in_path) # 封装百度语音识别需要的配置信息，返回请求头
  res = post(datas) # 连接百度语音识别接口，得到识别结果
  print("识别结果：",res[0])