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| import gradio as gr | |
| import whisper | |
| from pytube import YouTube | |
| loaded_model = whisper.load_model("base") | |
| def inference(link): | |
| yt = YouTube(link) | |
| path = yt.streams.filter(only_audio=True)[0].download(filename="audio.mp4") | |
| options = whisper.DecodingOptions(without_timestamps=True) | |
| results = loaded_model.transcribe(path) | |
| return results['text'] | |
| def change_model(size): | |
| loaded_model = whisper.load_model(size) | |
| title="Youtube Whisperer" | |
| description="Speech to text transcription of Youtube videos using OpenAI's Whisper" | |
| block = gr.Blocks() | |
| with block: | |
| gr.HTML( | |
| """ | |
| <div style="text-align: center; max-width: 500px; margin: 0 auto;"> | |
| <div> | |
| <h1>Youtube Whisperer</h1> | |
| </div> | |
| <p style="margin-bottom: 10px; font-size: 94%"> | |
| Speech to text transcription of Youtube videos using OpenAI's Whisper | |
| </p> | |
| </div> | |
| """ | |
| ) | |
| with gr.Group(): | |
| with gr.Box(): | |
| sz = gr.Dropdown(label="Model Size", choices=['base','small', 'medium', 'large'], value='base') | |
| sz.change(change_model, inputs=[sz], outputs=[]) | |
| link = gr.Textbox(label="YouTube Link") | |
| text = gr.Textbox( | |
| label="Transcription", | |
| placeholder="Transcription Output", | |
| lines=5) | |
| with gr.Row().style(mobile_collapse=False, equal_height=True): | |
| btn = gr.Button("Transcribe") | |
| btn.click(inference, inputs=[link], outputs=[text]) | |
| block.launch() | |