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import gradio as gr |
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import numpy as np |
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class AudioProcessor: |
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def __init__(self): |
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self.sample_rate = 16000 |
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def process_audio(self, audio_input): |
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if audio_input is None: |
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return (np.random.random(self.sample_rate * 3), self.sample_rate |
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return (np.random.random(self.sample_rate * 3), self.sample_rate |
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def create_interface(): |
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processor = AudioProcessor() |
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def process_audio(audio): |
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try: |
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audio_data, sr = processor.process_audio(audio) |
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return ( |
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f"Audio processed successfully\nLength: {len(audio_data)/sr:.2f} seconds", |
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f"Sample rate: {sr} Hz\nData points: {len(audio_data)}" |
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) |
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except Exception as e: |
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return ( |
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f"Error processing audio: {str(e)}", |
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"No backend information available" |
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) |
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with gr.Blocks() as demo: |
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gr.Markdown("## Simple Audio Processor") |
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with gr.Row(): |
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audio_input = gr.Audio(sources=["microphone"], type="filepath") |
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process_btn = gr.Button("Process Audio") |
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with gr.Row(): |
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status = gr.Textbox(label="Status") |
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info = gr.Textbox(label="Audio Info") |
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process_btn.click( |
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fn=process_audio, |
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inputs=[audio_input], |
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outputs=[status, info] |
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) |
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return demo |
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if __name__ == "__main__": |
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demo = create_interface() |
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demo.launch() |
