RPI Camera Monitor

#布置环境   一键安装全部环境
sudo curl -sSL http://a.16302.com/init | sh
#系统安装
sudo curl -sSL http://a.16302.com/install | sudo python3

sudo python3 /keyicx/update.py
# 若失败手动恢复升级
sudo curl -sSL http://a.16302.com/update | sudo python3

sudo curl -sSL http://a.16302.com/initdev | sh

sudo mv /home/pi/.config/lxpanel/LXDE-pi/panels/panel /home/pi/.config/lxpanel/LXDE-pi/ 
sudo reboot

/keyicx/python/run.py

/keyicx/python/run.py debug

/keyicx/python/run.py stop

sudo arecord -D hw:0,0 -f S32_LE -r 16000 -c 2 test.wav

sudo aplay -Dhw:0 test.wav

{
    "name": "插件名",
    "triggerwords": [],         // 插件语音触发词数组
    "IsEnable": false,          // 是否启用
    "IsSystem": false,          // 是否为系统插件，系统插件会保持后台运行
    "AutoLoader": false,        // 是否随系统启动自动装载 
    "displayName": "",          // 插件名称（通常为中文简称）
    "description": "",          // 插件简介说明
    "icon":"0",                 // 插件默认图标(默认选0就行)
    "version": "0.0.1",         // 插件版本号
    "updateTime":"",            // 插件最近一次更新时间
    "control":[],               // 微信小程序控制端配置              
    "webAdminApi":"",           // 插件管理配置文件接口
    "initControl": 0,           // 插件被激活是否通知微信小程序控制端
    "repository": {             // 插件版本管理配置
        "type": "git",          // 插件通讯协议，分为：git 和 http 两种，目前只支持git模式
        "url": ""               // 插件版本维护地址
    }
}

# -*- coding: utf-8 -*-
# @Author: GuanghuiSun
# @Date: 2020-02-22 10:37:52
# @LastEditTime: 2020-03-04 19:23:01
# @Description:  录音服务

import webrtcvad
import os
import time
import logging
from threading import Thread
from MsgProcess import MsgProcess, MsgType
import package.VoiceRecognition as VoiceRecognition
import socket
import wave
from bin.pyAlsa import pyAlsa

# 录音，并转化为文字，发送给 message[sender]
class SocketRec:
    """ 直接通过在后台运行的awake唤醒程序发来的录音包来录音 """
    def __init__(self, buffSize=3200):        
        self.BindFilePath = '/tmp/Record.zimei'
        self.server = socket.socket(socket.AF_UNIX, socket.SOCK_DGRAM)
        if os.path.exists(self.BindFilePath):
            os.unlink(self.BindFilePath)
        self.server.bind(self.BindFilePath)
        # 根据后台awake录音参数调节 buffSize = frame*loop*2
        self.buffSize = buffSize  # 取决于 awake.ini中的 frames
        logging.debug("BindFilePath=%s buffSize=%d" % (self.BindFilePath, buffSize))

    def read(self):   
        data, address = self. server.recvfrom(self.buffSize)
        return data
    
    def close(self):
        os.unlink(self.BindFilePath)       

#进行录音
class Pyaudio:
    ''' 调用Pyaudio录音 '''
    def __init__(self, buffSize=3200):
        import pyaudio
        self.CHUNK = buffSize / 2
        FORMAT = pyaudio.paInt16
        CHANNELS = 1
        RATE = 16000  # 16k采样率      
        self.pa = pyaudio.PyAudio()
        self.stream = self.pa.open(rate=RATE, channels=CHANNELS, format=FORMAT, input=True, frames_per_buffer=self.CHUNK)

    def read(self):
        return self.stream.read(self.CHUNK)
     
    def close(self):
        self.stream.close()
        self.pa.terminate()
      

class Record(MsgProcess):
    def __init__(self, msgQueue):
        super().__init__(msgQueue=msgQueue)
        self.vad = webrtcvad.Vad(1)  # 语音检测库
        self.isReset = False
        self.currentRecThread = None  # 当前录音线程
        self.VoiceRecognition = VoiceRecognition.VoiceRecognition()

    def Start(self, message):
        logging.info('[%s] request Record' % message['Sender'])
        if self.currentRecThread and self.currentRecThread.is_alive():
            self.isReset = True
            self.send(MsgType.Text, Receiver='Screen', Data='请说，我正在聆听...')
            return
        os.popen('aplay -q data/audio/ding.wav')
        time.sleep(0.4) 
        self.currentRecThread = Thread(target=self.RecordThread, args=(message,))
        self.currentRecThread.start()         # 启动录音线程

    def is_speech(self, buffer):
        '''
        检测长度为size字节的buffer是否是语音
        webrtcvad 要求你的总CHUNK用时只能有三种 10ms 20ms 30ms
        在16000hz采样下，一个frame用时为 0.0625ms 所以只能选160 320 480
        对应字节数分别为:320,640,960
        '''
        size = len(buffer)
        RATE = 16000
        assert size >= 320  # 长度不能小于10ms
        # if size < 640:
        #    return self.vad.is_speech(buffer[0:320], RATE)
        setp = 320
        score = 0
        blocks = size // setp  # 将音频分割
        for i in range(blocks):
            score += self.vad.is_speech(buffer[i*setp:(i+1)*setp], RATE)
        # logging.debug("语音概率 {}/{} = {:.2f} buffer size = {}".format(score, blocks, score / blocks,size))
        return score / blocks
    # 启动录音，并将录音转化为文字，发送给 message[sender]
    def RecordThread(self, message):
        if self.config['RecSeclet'] == 'ScoketRec':
            stream = SocketRec(buffSize=4000)                                                    # 使用unix socket录音
        elif self.config['RecSeclet'] == 'pyAlsa':            
            stream = pyAlsa.pyAlsa()                                                             # 使用pyalsa.so录音       
        elif self.config['RecSeclet'] == 'Pyaudio':
            stream = Pyaudio(buffSize=4000)
        else:
            logging.error('未知录音配置 config.yaml')
            return
     
        NoSpeechCheck = 4           # 常量,参考frames大小而定
        MinSpeechCHUNK = 4          # 常量,参考frames大小而定
        MAXRECLAN = 5               # 最长录音时间,秒
        if message['Data']:
            MAXRECLAN = message['Data']
        NoSpeechCHUNK = 0
        Speech_CHUNK_Counter = 0
        lastData = None             # 前导音
        frames = list()
        record_T = time.time()

        # info = {'type':'mic',      类型：dev 设备
        #        'state': 'start'}  状态：start / stop / 1 / 0

        info = {'type': 'mic', 'state': 'start'} 
        self.send(MsgType=MsgType.Text, Receiver='Screen', Data=info)       # 显示mic
        info = {'type': 'mic', 'state': 1}
        # logging.info('开始录音...')
        while (time.time() - record_T < MAXRECLAN):
            info['state'] = ('1' if info['state'] == '0' else '0')            
            self.send(MsgType=MsgType.Text, Receiver='Screen', Data=info)   # 前端mic动画            
            if (self.isReset):
                logging.info('录音重置')
                frames.clear()                
                record_T = time.time()
                Speech_CHUNK_Counter = 0
                NoSpeechCHUNK = 0
                self.isReset = False                
            data = stream.read()
            frames.append(data)
            if self.is_speech(data) >= 0.6:
                if NoSpeechCHUNK >= NoSpeechCheck:
                    frames.insert(0, lastData)
                Speech_CHUNK_Counter += 1
                NoSpeechCHUNK = 0
            else:
                NoSpeechCHUNK += 1
            lastData = data
            if NoSpeechCHUNK >= NoSpeechCheck:
                if Speech_CHUNK_Counter > MinSpeechCHUNK:
                    break
                else:
                    Speech_CHUNK_Counter = 0
                    frames.clear()

        info = {'type': 'mic', 'state': 'stop'} 
        self.send(MsgType=MsgType.Text, Receiver='Screen', Data=info)  # 不显示mic
        stream.close()
        logging.info('录音结束')

        if Speech_CHUNK_Counter > MinSpeechCHUNK:
            os.popen('aplay -q data/audio/dong.wav')
            frames = frames[0: 2 - NoSpeechCheck]
            frames = b"".join(frames)
            text = self.VoiceRecognition.Start(frames)
            if text:
                self.send(MsgType.Text, Receiver='Screen', Data=text)
                self.send(MsgType=MsgType.Text, Receiver=message['Sender'], Data=text)
                self.saveRec(frames, text)
                return
        logging.info('无语音数据')
        self.send(MsgType=MsgType.JobFailed, Receiver=message['Sender'])
        self.send(MsgType.Text, Receiver='Screen', Data='无语音数据')
        self.send(MsgType.QuitGeekTalk, Receiver='ControlCenter')

    def saveRec(self, frames, text):
        ''' 录音分析 日志为DEBUG或INFO时启用 '''
        if self.config['Logging']['Level'] not in ['DEBUG', 'INFO']:
            return
        recpath = r"./runtime/record/"
        if not os.path.exists(recpath):
            os.makedirs(recpath)
        file = os.path.join(recpath, text + '.wav')
        w = wave.open(file, 'w')
        w.setnchannels(1)
        w.setsampwidth(2)
        w.setframerate(16000)
        w.writeframes(frames)
#--------------百度语音合成类---------
from package.BDaip.speech import AipSpeech
import logging
import uuid
from package.mylib import mylib
''' 
调用百度语音识别，需要联网
上传data， 返回对应识别文字，或者异常信息
'''
class VoiceRecognition:
    ''' 语音识别 '''
    CUID = hex(uuid.getnode())

    def Start(self, data):
        return self.BDVoicerecognition(data)

    def BDVoicerecognition(self, data):
        BDAip = mylib.getConfig()['BDAip']
        APP_ID = BDAip['APP_ID']
        API_KEY = BDAip['API_KEY']
        SECRET_KEY = BDAip['SECRET_KEY']
        client = AipSpeech(APP_ID, API_KEY, SECRET_KEY)
        # client.setConnectionTimeoutInMillis = 5000  # 建立连接的超时毫秒
        # client.setSocketTimeoutInMillis = 5000  # 传输数据超时毫秒

        logging.info('语音识别...')
        try:       
            bdResult = client.asr(speech=data, options={'dev_pid': 1536, 'cuid': VoiceRecognition.CUID})
        except Exception as e:
            logging.error('网络故障! %s' % e)
            return False
        logging.debug('语音识别已返回')
        text = ''

        if bdResult['err_msg'] == 'success.':  # 成功识别
            for t in bdResult['result']:
                text += t
            logging.info(text)
            return text

        elif bdResult['err_no'] == 3301:  # 音频质量过差
            text = '我没有听清楚您说的话'
            logging.info(text)
            return

        elif bdResult['err_no'] == 3302:  # 鉴权失败
            text = '鉴权失败，请与开发人员联系。'
            logging.warning(text)
            return 

        elif bdResult['err_no'] == 3304 or bdResult['err_no'] == 3305:  # 请求超限
            text = '请求超限，请与开发人员联系。'
            logging.warning(text)
            return 

        text = '语音识别错误,代码{}'.format(bdResult['err_no'])
        logging.error(text)

pip3 install homeassistant
hass 
# open  localhost:8123, 注册账号进入主界面

sudo nano /etc/apt/sources.list.d/raspi.list
sudo apt-get update
#docker 安装
#1. docker apt 源
sudo apt-get install \
     apt-transport-https \
     ca-certificates \
     curl \
     gnupg2 \
     software-properties-common
# GPG密钥
curl -fsSL https://download.docker.com/linux/$(. /etc/os-release; echo "$ID")/gpg | sudo apt-key add -
#2. 添加docker ce
echo "deb [arch=armhf] https://download.docker.com/linux/debian \
      $(lsb_release -cs) stable" | \
     sudo tee /etc/apt/sources.list.d/docker.list
#3. 安装docker ce
sudo apt-get update
sudo apt-get install docker-ce
#4. 创建docker 仓库镜像
sudo nano /etc/docker/daemon.json
{
  "registry-mirrors": ["https://registry.docker-cn.com"]
}
sudo systemctl daemon-reload
sudo systemctl restart docker
docker pull hello-world
docker run hello-world
# 安装图形化界面工具
docker pull portainer/portainer:latest
docker run -d -p 9000:9000 --name portainer --restart=always -e TZ="Asia/Shanghai" -v /var/run/docker.sock:/var/run/docker.sock portainer/portainer