# 引用whisper模块
import whisper
from flask import Flask,request
import datetime
import requests
import torch
import os# 语音识别模型
# model = whisper.load_model("large", download_root="/opt/Whisper/models")    # 同时下载模型
#device = torch.device("cpu")    
device = torch.device("cuda:0")                                                  # 使用CPU加载模型
model = whisper.load_model("/opt/Whisper/models/tiny.pt", device=device)  # 加载模型
#model = whisper.load_model("D:\\whisper\\models\\tiny\\tiny.pt", device=device)  # 加载本地模型# 实例化一个web服务对象
app = Flask(__name__)
# 构造一个接受post请求的响应
@app.route('/',methods=['POST'])
def postRequest():data = {}data['data'] = {'text':'Not Found!'}data['code'] = 404# # 验证秘钥是否通过# key = request.form.get('key')# if key != "OpenAI Whisper":#     data['data'] = {'text':'No permissions!'}#     data['code'] = 400#     return data# 判断翻译类型lang = 'zh'lang_ = request.form.get('lang')if lang_ == 'en':lang = 'en'# 验证是否上传文件，未上传文件使用远程地址或本地地址if 'file' not in request.files:# 获取路径path = request.form.get('path')if path.lower().endswith((".wav", ".WAV",".mp3",".MP3")) is False:data['data'] = {'text':'No wav or mp3!'}data['code'] = 400return datatyp = request.form.get('typ') # url/path# 如果是使用连接，则远程拷贝链接文件到指定地址if typ == 'url':# 指定地址fileName = '/opt/Whisper/voice/' + datetime.datetime.now().strftime('%Y%m%d_%H%M%S') + '.wav'#fileName = 'D:\\whisper\\voice\\' + datetime.datetime.now().strftime('%Y%m%d_%H%M%S') + '.wav'downlaod(path, fileName)res = toLang(lang, fileName) # model.transcribe(fileName,language='Chinese')data['data'] = resdata['code'] = 200# 如果是使用本地文件，则直接读取elif typ == 'path':res = toLang(lang, path) # model.transcribe(path,language='Chinese')data['data'] = resdata['code'] = 200# 如果通过上传文件else:file = request.files['file']if file.filename == '':data['data'] = {'text':'No file!'}data['code'] = 400return data# 指定文件保存路径file_extension = file.filename.split(".")[-1]if file_extension != 'wav' and file_extension!= 'WAV' and file_extension != 'mp3' and file_extension!= 'MP3':data['data'] = {'text':'No Voice!'}data['code'] = 400return data# 指定地址fileName = '/opt/Whisper/voice/' + datetime.datetime.now().strftime('%Y%m%d_%H%M%S') + '.' + file_extension#fileName = 'D:\\whisper\\voice\\' + datetime.datetime.now().strftime('%Y%m%d_%H%M%S') + '.' + file_extensionfile.save(fileName)# 确保文件被写入磁盘with open(fileName, 'a') as f:f.flush()os.fsync(f.fileno())#语音钻文字    res = toLang(lang, fileName) # model.transcribe(fileName,language='Chinese')data['data'] = resdata['code'] = 200return data# 文件下载
def downlaod(url, file_path):headers = {"User-Agent": "Mozilla/5.0 (Windows NT 10.0; WOW64; rv:68.0) Gecko/20100101 Firefox/68.0"}r = requests.get(url=url, headers=headers)with open(file_path, "wb") as f:f.write(r.content)f.flush()# 识别
def toLang(lang, file_path):print(file_path)if lang == 'en':prompt = 'is English'transcription = model.transcribe(file_path, language='en',verbose=True, initial_prompt=prompt)print(transcription["text"])else:prompt = '以下是普通话的句子'transcription = model.transcribe(file_path, language='zh',verbose=True, initial_prompt=prompt)print(transcription["text"])# 删除临时文件try:os.remove(file_path)print(f"Deleted file: {file_path}")except Exception as e:print(f"Failed to delete file: {file_path}, Error: {str(e)}")return transcriptionif __name__ == '__main__':# 运行服务，并确定服务运行的IP和端口app.run('0.0.0.0', '8000')

nohup /home/wwwccczzz/anaconda3/envs/whisper/bin/python /opt/Whisper/speech.py > /opt/Whisper/speech.log 2>&1 &

  crontab -e

@reboot nohup /home/wwwccczzz/anaconda3/envs/whisper/bin/python /opt/Whisper/speech.py > /opt/Whisper/speech.log 2>&1 &