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| from googleapiclient.discovery import build | |
| from google.oauth2 import service_account | |
| from googleapiclient.http import MediaFileUpload | |
| import pdb | |
| import gradio as gr | |
| # 来自Google Cloud控制台的JSON凭据文件 | |
| credentials_file = "./src/peerless-window-254907-b386b71c0d99.json" | |
| # "./client_secret_576367903492-diuopf97kn9eh1gte3vh65errtca1o64.apps.googleusercontent.com.json" | |
| # Google Drive API版本 | |
| api_version = 'v3' | |
| # 创建服务对象 | |
| credentials = service_account.Credentials.from_service_account_file( | |
| credentials_file, scopes=['https://www.googleapis.com/auth/drive']) | |
| service = build('drive', api_version, credentials=credentials) | |
| import gradio as gr | |
| from transformers import pipeline | |
| import numpy as np | |
| import librosa | |
| import torchaudio | |
| import datetime | |
| def generate_now_time_wav(): | |
| # Get the current date and time | |
| current_time = datetime.datetime.now() | |
| # Format the date and time as a string | |
| time_string = current_time.strftime("%Y-%m-%d_%H-%M-%S") | |
| # Create the WAV file name with the formatted time | |
| wavfile_name = f"audio_{time_string}.wav" | |
| return wavfile_name | |
| # transcriber = pipeline("automatic-speech-recognition", model="openai/whisper-base.en") | |
| def transcribe(audio_path): | |
| if audio_path == None: | |
| print("using ref audio as eval audio since it's empty") | |
| wav, sr = torchaudio.load(audio_path) | |
| if wav.shape[0] != 1: | |
| wav = wav[0, :] | |
| print(wav.shape) | |
| name = generate_now_time_wav() | |
| # 上传文件 | |
| media = MediaFileUpload(audio_path, mimetype='audio/wav') | |
| request = service.files().create( | |
| media_body=media, | |
| body={'name': name} | |
| ) | |
| response = request.execute() | |
| return response.get('id') | |
| demo = gr.Interface( | |
| fn = transcribe, | |
| inputs = gr.Audio(source="microphone", type='filepath'), | |
| outputs = "text", | |
| ) | |
| # file_path = 'data/3_michael_20230619_100/1st_session_ZOOM0015_002.wav' | |
| # x = gr.Audio(source="upload", type='filepath'), | |
| # pdb.set_trace() | |
| # x = transcribe(file_path) | |
| # pdb.set_trace() | |
| demo.launch() | |
| # # 要上传的文件 | |
| # file_name = '1st_session_ZOOM0015_001.wav' | |
| # # 上传文件 | |
| # media = MediaFileUpload(file_path, mimetype='audio/wav') | |
| # request = service.files().create( | |
| # media_body=media, | |
| # body={'name': file_name} | |
| # ) | |
| # response = request.execute() | |
| # # 列出文件 | |
| # results = service.files().list().execute() | |
| # files = results.get('files', []) | |
| # pdb.set_trace() | |
| # print('文件ID:%s' % response.get('id')) |