Commit
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4cc54d7
1
Parent(s):
a9b4659
add initial files
Browse files- app.py +55 -0
- requirements.txt +4 -0
app.py
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import gradio as gr
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import numpy as np
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import matplotlib.pyplot as plt
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from matplotlib.animation import FuncAnimation
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import io
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import librosa
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def extract_waveform_animation(audio_file, duration):
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# Load audio file
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y, sr = librosa.load(audio_file, sr=None)
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# Determine the number of frames needed for the specified duration
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num_frames = int(duration * sr)
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y = y[:num_frames]
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# Create a figure and axis for the animation
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fig, ax = plt.subplots()
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line, = ax.plot([], [], lw=2)
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ax.set_xlim(0, duration)
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ax.set_ylim(np.min(y), np.max(y))
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# Function to initialize the animation
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def init():
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line.set_data([], [])
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return line,
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# Function to update the animation frame
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def update(frame):
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line.set_data(np.linspace(0, duration, num=len(y[:frame])), y[:frame])
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return line,
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# Create the animation
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ani = FuncAnimation(fig, update, frames=np.arange(0, num_frames, sr // 10), init_func=init, blit=True)
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# Save the animation to a buffer
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buf = io.BytesIO()
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ani.save(buf, format='gif')
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buf.seek(0)
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return buf
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# Define the Gradio interface
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iface = gr.Interface(
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fn=extract_waveform_animation,
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inputs=[
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gr.Audio(source="upload", type="file"),
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gr.Number(label="Duration (seconds)", value=5)
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],
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outputs=gr.Image(type="file", format="gif"),
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description="Upload an audio file to extract an animation from its waveform. Specify the duration of the animation."
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)
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# Launch the app
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if __name__ == "__main__":
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iface.launch()
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requirements.txt
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gradio
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numpy
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librosa
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matplotlib
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