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import os |
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os.system("pip install git+https://github.com/openai/whisper.git") |
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import gradio as gr |
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import whisper |
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model = whisper.load_model("small") |
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current_size = 'small' |
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def change_model(size): |
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if size == current_size: |
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return |
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model = whisper.load_model(size) |
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current_size = size |
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def inference(audio): |
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audio = whisper.load_audio(audio) |
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audio = whisper.pad_or_trim(audio) |
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mel = whisper.log_mel_spectrogram(audio).to(model.device) |
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_, probs = model.detect_language(mel) |
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options = whisper.DecodingOptions(fp16 = False) |
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result = whisper.decode(model, mel, options) |
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print(result.text) |
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return result.text |
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title="Whisper OpenAI, deployed with jthteo" |
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description="Whisper is a general-purpose speech recognition model into English. It has been 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." |
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css = """ |
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.gradio-container { |
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font-family: 'IBM Plex Sans', sans-serif; |
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} |
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.gr-button { |
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color: white; |
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border-color: black; |
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background: black; |
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} |
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input[type='range'] { |
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accent-color: black; |
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} |
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.dark input[type='range'] { |
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accent-color: #dfdfdf; |
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} |
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.container { |
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max-width: 800px; |
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margin: auto; |
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padding-top: 1.5rem; |
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} |
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.details:hover { |
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text-decoration: underline; |
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} |
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.gr-button { |
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white-space: nowrap; |
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} |
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.gr-button:focus { |
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border-color: rgb(147 197 253 / var(--tw-border-opacity)); |
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outline: none; |
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box-shadow: var(--tw-ring-offset-shadow), var(--tw-ring-shadow), var(--tw-shadow, 0 0 #0000); |
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--tw-border-opacity: 1; |
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--tw-ring-offset-shadow: var(--tw-ring-inset) 0 0 0 var(--tw-ring-offset-width) var(--tw-ring-offset-color); |
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--tw-ring-shadow: var(--tw-ring-inset) 0 0 0 calc(3px var(--tw-ring-offset-width)) var(--tw-ring-color); |
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--tw-ring-color: rgb(191 219 254 / var(--tw-ring-opacity)); |
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--tw-ring-opacity: .5; |
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} |
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.footer { |
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margin-bottom: 45px; |
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margin-top: 35px; |
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text-align: center; |
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border-bottom: 1px solid #e5e5e5; |
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} |
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.footer>p { |
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font-size: .8rem; |
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display: inline-block; |
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padding: 0 10px; |
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transform: translateY(10px); |
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background: white; |
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} |
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.dark .footer { |
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border-color: #303030; |
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} |
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.dark .footer>p { |
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background: #0b0f19; |
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} |
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.prompt h4{ |
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margin: 1.25em 0 .25em 0; |
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font-weight: bold; |
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font-size: 115%; |
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} |
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""" |
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block = gr.Blocks(css=css) |
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with block: |
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gr.HTML( |
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""" |
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<div style="text-align: center; max-width: 800px; margin: 0 auto;"> |
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<div |
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style=" |
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display: inline-flex; |
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align-items: center; |
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gap: 0.8rem; |
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font-size: 1.75rem; |
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" |
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> |
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<svg |
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width="0.65em" |
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height="0.65em" |
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viewBox="0 0 115 115" |
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fill="none" |
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xmlns="http://www.w3.org/2000/svg" |
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> |
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<circle cx="62" cy="45" r="36" stroke="blue" stroke-width="4" fill="blue" /> |
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<polygon points="40, 30, 84, 30, 62, 69" style="fill:red;stroke:red;stroke-width:5;" /> |
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</svg> |
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<h1 style="font-weight: 900; margin-bottom: 7px; color:red;"> |
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Whisper |
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</h1> |
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<svg |
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width="0.65em" |
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height="0.65em" |
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viewBox="0 0 115 115" |
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fill="none" |
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xmlns="http://www.w3.org/2000/svg" |
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> |
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<circle cx="62" cy="45" r="36" stroke="blue" stroke-width="4" fill="blue" /> |
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<polygon points="40, 30, 84, 30, 62, 69" style="fill:red;stroke:red;stroke-width:5;" /> |
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</svg> |
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</div> |
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<p style="margin-bottom: 10px; font-size: 94%"> |
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Whisper is a general-purpose speech recognition model. It has been 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> |
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<p>This is a fork by JTHTEO.</p> |
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<p>The sizes of the different Whisper models can be found in this <a href="https://github.com/openai/whisper/blob/main/model-card.md">Model Card</a>. </p> |
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</p> |
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</div> |
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""" |
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) |
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with gr.Group(): |
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with gr.Box(): |
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wmodel = gr.Radio( |
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choices=["tiny", "base", "small", "medium", "large", "small.en", "medium.en"], |
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label="Model used", |
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value="small") |
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with gr.Row().style(mobile_collapse=False, equal_height=True): |
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audio = gr.Audio( |
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label="Input Audio", |
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show_label=False, |
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source="microphone", |
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type="filepath" |
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) |
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btn = gr.Button("Transcribe") |
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text = gr.Textbox(show_label=False) |
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wmodel.change(change_model, inputs=[wmodel], outputs=[]) |
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btn.click(inference, inputs=[audio], outputs=[text],api_name="audio_whisper") |
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gr.HTML(''' |
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<div class="footer"> |
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<p>Model by <a href="https://github.com/openai/whisper" style="text-decoration: underline;" target="_blank">OpenAI</a> - Gradio Demo by 🤗 Hugging Face, this is a fork by JTHTEO |
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</p> |
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</div> |
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''') |
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block.launch() |