| 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 | |
| title="Whisper" | |
| description="""Whisper is a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multi-task model that can perform multilingual speech recognition as well as speech translation and language identification. This demo cuts audio after around 30 secs.""" | |
| css = """ | |
| .gradio-container { | |
| font-family: 'IBM Plex Sans', sans-serif; | |
| } | |
| .gr-button { | |
| color: white; | |
| border-color: black; | |
| background: black; | |
| } | |
| input[type='range'] { | |
| accent-color: black; | |
| } | |
| .dark input[type='range'] { | |
| accent-color: #dfdfdf; | |
| } | |
| .container { | |
| max-width: 730px; | |
| margin: auto; | |
| padding-top: 1.5rem; | |
| } | |
| .details:hover { | |
| text-decoration: underline; | |
| } | |
| .gr-button { | |
| white-space: nowrap; | |
| } | |
| .gr-button:focus { | |
| border-color: rgb(147 197 253 / var(--tw-border-opacity)); | |
| outline: none; | |
| box-shadow: var(--tw-ring-offset-shadow), var(--tw-ring-shadow), var(--tw-shadow, 0 0 #0000); | |
| --tw-border-opacity: 1; | |
| --tw-ring-offset-shadow: var(--tw-ring-inset) 0 0 0 var(--tw-ring-offset-width) var(--tw-ring-offset-color); | |
| --tw-ring-shadow: var(--tw-ring-inset) 0 0 0 calc(3px var(--tw-ring-offset-width)) var(--tw-ring-color); | |
| --tw-ring-color: rgb(191 219 254 / var(--tw-ring-opacity)); | |
| --tw-ring-opacity: .5; | |
| } | |
| .footer { | |
| margin-bottom: 45px; | |
| margin-top: 35px; | |
| text-align: center; | |
| border-bottom: 1px solid #e5e5e5; | |
| } | |
| .footer>p { | |
| font-size: .8rem; | |
| display: inline-block; | |
| padding: 0 10px; | |
| transform: translateY(10px); | |
| background: white; | |
| } | |
| .dark .footer { | |
| border-color: #303030; | |
| } | |
| .dark .footer>p { | |
| background: #0b0f19; | |
| } | |
| .prompt h4{ | |
| margin: 1.25em 0 .25em 0; | |
| font-weight: bold; | |
| font-size: 115%; | |
| } | |
| """ | |
| block = gr.Blocks(css=css) | |
| with block: | |
| gr.HTML( | |
| """ | |
| <div style="text-align: center; max-width: 650px; margin: 0 auto;"> | |
| <div | |
| style=" | |
| display: inline-flex; | |
| align-items: center; | |
| gap: 0.8rem; | |
| font-size: 1.75rem; | |
| " | |
| > | |
| <svg | |
| width="0.65em" | |
| height="0.65em" | |
| viewBox="0 0 115 115" | |
| fill="none" | |
| xmlns="http://www.w3.org/2000/svg" | |
| > | |
| <rect width="23" height="23" fill="white"></rect> | |
| <rect y="69" width="23" height="23" fill="white"></rect> | |
| <rect x="23" width="23" height="23" fill="#AEAEAE"></rect> | |
| <rect x="23" y="69" width="23" height="23" fill="#AEAEAE"></rect> | |
| <rect x="46" width="23" height="23" fill="white"></rect> | |
| <rect x="46" y="69" width="23" height="23" fill="white"></rect> | |
| <rect x="69" width="23" height="23" fill="black"></rect> | |
| <rect x="69" y="69" width="23" height="23" fill="black"></rect> | |
| <rect x="92" width="23" height="23" fill="#D9D9D9"></rect> | |
| <rect x="92" y="69" width="23" height="23" fill="#AEAEAE"></rect> | |
| <rect x="115" y="46" width="23" height="23" fill="white"></rect> | |
| <rect x="115" y="115" width="23" height="23" fill="white"></rect> | |
| <rect x="115" y="69" width="23" height="23" fill="#D9D9D9"></rect> | |
| <rect x="92" y="46" width="23" height="23" fill="#AEAEAE"></rect> | |
| <rect x="92" y="115" width="23" height="23" fill="#AEAEAE"></rect> | |
| <rect x="92" y="69" width="23" height="23" fill="white"></rect> | |
| <rect x="69" y="46" width="23" height="23" fill="white"></rect> | |
| <rect x="69" y="115" width="23" height="23" fill="white"></rect> | |
| <rect x="69" y="69" width="23" height="23" fill="#D9D9D9"></rect> | |
| <rect x="46" y="46" width="23" height="23" fill="black"></rect> | |
| <rect x="46" y="115" width="23" height="23" fill="black"></rect> | |
| <rect x="46" y="69" width="23" height="23" fill="black"></rect> | |
| <rect x="23" y="46" width="23" height="23" fill="#D9D9D9"></rect> | |
| <rect x="23" y="115" width="23" height="23" fill="#AEAEAE"></rect> | |
| <rect x="23" y="69" width="23" height="23" fill="black"></rect> | |
| </svg> | |
| <h1 style="font-weight: 900; margin-bottom: 7px;"> | |
| Whisper | |
| </h1> | |
| </div> | |
| <p style="margin-bottom: 10px; font-size: 94%"> | |
| Whisper is a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multi-task model that can perform multilingual speech recognition as well as speech translation and language identification. | |
| </p> | |
| </div> | |
| """ | |
| ) | |
| 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) | |
| btn.click(inference, inputs=[audio], outputs=[text]) | |
| gr.HTML(''' | |
| <div class="footer"> | |
| <p>Model by <a href="https://github.com/openai/whisper" style="text-decoration: underline;" target="_blank">OpenAI</a> - Gradio Demo by 🤗 Hugging Face | |
| </p> | |
| </div> | |
| ''') | |
| block.launch() |