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import gradio as gr
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
import matplotlib.colors as mcolors
import io
import librosa
import tempfile
def extract_waveform_animation(audio_file, window_seconds=5):
y, sr = librosa.load(audio_file, sr=None)
duration = librosa.get_duration(y=y, sr=sr)
FPS = 1
fig, ax = plt.subplots()
line, = ax.plot([], [], lw=2)
window_length = int(window_seconds * sr)
# Initialize with first window
first_window = y[:window_length]
x_vals = np.linspace(0, duration, num=len(y))
ax.set_axis_off()
waveform_color ="blue"
bg_color ="#00FFFF00"
ax.set_facecolor(waveform_color)
fig.set_facecolor(bg_color)
def init():
ax.set_xlim(0, window_seconds)
ax.set_ylim(np.min(y), np.max(y)) # Reduced max for visibility
return line,
def update(frame):
# Get current window
start = frame * sr
end = start + window_length
window = y[start:end]
# Update x and y limits
ax.set_xlim(frame, frame + window_seconds)
# Update line data
line.set_data(x_vals[start:end], window)
return line,
total_frames = int(duration) * FPS
ani = FuncAnimation(fig, update, frames=range(total_frames),
init_func=init, interval=window_seconds, blit=False)
with tempfile.NamedTemporaryFile(delete=False, suffix='.gif') as tmpfile:
ani.save(tmpfile.name, writer='ffmpeg', fps=FPS)
video_path = tmpfile.name
return video_path
# Modified interface with window controls
iface = gr.Interface(
fn=extract_waveform_animation,
inputs=[
gr.Audio(type="filepath"),
gr.Slider(1, 10, value=5, step=1, label="Window Size (seconds)")
],
outputs=gr.Image(),
description="Scroll through audio waveform with a moving window."
)
if __name__ == "__main__":
iface.launch() |