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import requests | |
import gradio as gr | |
API_URL = "https://api-inference.huggingface.co/models/MIT/ast-finetuned-audioset-10-10-0.4593" | |
headers = {"Authorization": f"Bearer {os.environ.get('HF_TOKEN')}"} | |
def classify_audio(audio_file): | |
""" | |
Classify the uploaded audio file using Hugging Face AST model | |
""" | |
if audio_file is None: | |
return "Please upload an audio file." | |
with open(audio_file.name, "rb") as f: | |
data = f.read() | |
response = requests.post(API_URL, headers=headers, data=data) | |
try: | |
results = response.json() | |
return results | |
except Exception as e: | |
return f"Error processing audio: {str(e)}" | |
# Create Gradio interface | |
iface = gr.Interface( | |
fn=classify_audio, | |
inputs=gr.Audio(type="filepath", label="Upload Audio File"), | |
outputs=gr.JSON(label="Classification Results"), | |
title="Audio Classification using AST Model", | |
description="Upload an audio file to get its classification results using the Audio Spectrogram Transformer model.", | |
examples=[], | |
) | |
# Launch the interface | |
iface.launch() | |