| from transformers import pipeline | |
| model_id = "arham061/distilhubert-finetuned-RHD_Dataset" | |
| pipe = pipeline("audio-classification", model=model_id) | |
| def classify_audio(filepath): | |
| preds = pipe(filepath) | |
| outputs = {} | |
| for p in preds: | |
| outputs[p["label"]] = p["score"] | |
| return outputs | |
| import gradio as gr | |
| demo = gr.Interface( | |
| fn=classify_audio, | |
| inputs=gr.Audio(type="filepath"), | |
| outputs="label", | |
| examples = ['normal.wav', 'murmur.wav', 'extra_systole.wav', 'extra_hystole.wav', 'artifact.wav'], | |
| theme = "dark" | |
| ) | |
| demo.launch(debug=True) |