| # import whisper | |
| # from pytube import YouTube | |
| # from transformers import pipeline | |
| # import gradio as gr | |
| # import os | |
| # from speechbrain.inference.ASR import EncoderASR | |
| # import gradio as gr | |
| # model = EncoderASR.from_hparams("speechbrain/asr-wav2vec2-dvoice-wolof") | |
| # #model = whisper.load_model("base") | |
| # summarizer = pipeline("summarization") | |
| # def get_audio(url): | |
| # yt = YouTube(url) | |
| # video = yt.streams.filter(only_audio=True).first() | |
| # out_file=video.download(output_path=".") | |
| # base, ext = os.path.splitext(out_file) | |
| # new_file = base+'.mp3' | |
| # os.rename(out_file, new_file) | |
| # a = new_file | |
| # return a | |
| # def get_text(url): | |
| # result = model.transcribe(get_audio(url)) | |
| # return result['text'] | |
| # def get_summary(url): | |
| # article = get_text(url) | |
| # b = summarizer(article) | |
| # b = b[0]['summary_text'] | |
| # return b | |
| # with gr.Blocks() as demo: | |
| # gr.Markdown("<h1><center>Youtube video transcription with in wolof by Papa Sega</center></h1>") | |
| # gr.Markdown("<center>Enter the link of any youtube video to get the transcription of the video and a summary of the video in the form of text.</center>") | |
| # with gr.Tab('Get the transcription of any Youtube video'): | |
| # with gr.Row(): | |
| # input_text_1 = gr.Textbox(placeholder='Enter the Youtube video URL', label='URL') | |
| # output_text_1 = gr.Textbox(placeholder='Transcription of the video', label='Transcription') | |
| # result_button_1 = gr.Button('Get Transcription') | |
| # with gr.Tab('Summary of Youtube video'): | |
| # with gr.Row(): | |
| # input_text = gr.Textbox(placeholder='Enter the Youtube video URL', label='URL') | |
| # output_text = gr.Textbox(placeholder='Summary text of the Youtube Video', label='Summary') | |
| # result_button = gr.Button('Get Summary') | |
| # result_button.click(get_summary, inputs = input_text, outputs = output_text) | |
| # result_button_1.click(get_text, inputs = input_text_1, outputs = output_text_1) | |
| # demo.launch(debug=True) | |
| from pytube import YouTube | |
| from speechbrain.inference.ASR import EncoderASR | |
| import gradio as gr | |
| import os | |
| # Charger le modèle EncoderASR | |
| model = EncoderASR.from_hparams("speechbrain/asr-wav2vec2-dvoice-wolof") | |
| def get_audio(url): | |
| yt = YouTube(url) | |
| video = yt.streams.filter(only_audio=True).first() | |
| out_file = video.download(output_path=".") | |
| base, ext = os.path.splitext(out_file) | |
| new_file = base+'.mp3' | |
| os.rename(out_file, new_file) | |
| return new_file | |
| def get_text(url): | |
| audio_file = get_audio(url) | |
| result = model.transcribe_file(audio_file) | |
| os.remove(audio_file) # Supprimer le fichier audio temporaire | |
| # Ajout d'un débogage pour vérifier la structure de 'result' | |
| print(f"Transcription result: {result}") | |
| # Si result est une chaîne de caractères, la retourner directement | |
| if isinstance(result, str): | |
| return result | |
| # Sinon, retourner la valeur associée à la clé 'text' | |
| return result.get('text', 'Transcription failed') | |
| demo = gr.Interface( | |
| get_text, | |
| inputs=gr.Textbox(placeholder='Enter the Youtube video URL', label='URL'), | |
| outputs=gr.Textbox(placeholder='Transcription of the video', label='Transcription'), | |
| title="Youtube Video Transcription in Wolof by Papa Sega", | |
| description="Enter the link of any Youtube video to get the transcription of the video in Wolof.", | |
| ) | |
| demo.launch(debug=True) | |