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Browse files- app.py +33 -0
- requirement.txt +2 -0
app.py
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from transformers import pipeline
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import gradio
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from gradio import Interface, Audio, Label, Number
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username = 'bvallegc' ## Complete your username
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model_id = f"{username}/distilhubert-finetuned-gtzan"
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pipe = pipeline("audio-classification", model=model_id)
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def classify_audio(filepath):
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"""
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Goes from
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[{'score': 0.8339303731918335, 'label': 'country'},
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{'score': 0.11914275586605072, 'label': 'rock'},]
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to
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{"country": 0.8339303731918335, "rock":0.11914275586605072}
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"""
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preds = pipe(filepath)
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classification = [{"label": p["label"], "score": p["score"]} for p in preds]
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label = classification[0]["label"]
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number = classification[0]["score"]
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return label, number
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interface_options = {
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"title": "Spoofing Classification",
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"description": "The audio classifier for those who are the best and only want and require the best",
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# Audio from validation file
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"allow_flagging": "never"
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}
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demo = Interface(
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fn=classify_audio, inputs= Audio(type="filepath"), outputs=[Label(), Number()], **interface_options
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)
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demo.launch(debug=False)
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requirement.txt
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torch
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git+https://github.com/huggingface/transformers
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