| import os | |
| os.system("pip install git+https://github.com/openai/whisper.git") | |
| import gradio as gr | |
| import whisper | |
| model = whisper.load_model("small") | |
| def inference(audio): | |
| audio = whisper.load_audio(audio) | |
| audio = whisper.pad_or_trim(audio) | |
| mel = whisper.log_mel_spectrogram(audio).to(model.device) | |
| _, probs = model.detect_language(mel) | |
| options = whisper.DecodingOptions(fp16 = False) | |
| result = whisper.decode(model, mel, options) | |
| print(result.text) | |
| return result.text | |
| block = gr.Blocks(css=css) | |
| with block: | |
| with gr.Group(): | |
| with gr.Box(): | |
| with gr.Row().style(mobile_collapse=False, equal_height=True): | |
| audio = gr.Audio( | |
| label="Input Audio", | |
| show_label=False, | |
| source="microphone", | |
| type="filepath" | |
| ) | |
| btn = gr.Button("Transcribe") | |
| text = gr.Textbox(show_label=False, elem_id="result-textarea") | |
| btn.click(inference, inputs=[audio], outputs=[text], api_name="transcribe") | |
| gr.HTML(''' | |
| <div class="footer"> | |
| <p>This space is used by VideoChain, the all-in-one API to generate video, audio and more.</p> | |
| </div> | |
| ''') | |
| block.launch() |