Visualizzatore Musicale con Python.Jupyter Notebook in descrizione

import librosa
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
from moviepy.editor import VideoFileClip, AudioFileClip
import tempfile
import os
from scipy.signal import savgol_filter
def load_and_preprocess_music(file_path):
y, sr = librosa.load(file_path)
n_fft = 2048
hop_length = 512
mel_spec = librosa.feature.melspectrogram(y=y, sr=sr, n_mels=128, n_fft=n_fft, hop_length=hop_length)
mel_spec_db = librosa.power_to_db(mel_spec, ref=np.max)
mel_spec_db = savgol_filter(mel_spec_db, window_length=15, polyorder=3, axis=1)
return y, sr, mel_spec_db
def create_base_animation():
fig, ax = plt.subplots(figsize=(16, 9), facecolor='black')
ax.set_facecolor('black')
ax.axis('off')
Create a gradient background
gradient = np.linspace(0, 1, 256).reshape(1, -1)
gradient = np.repeat(gradient, 512, axis=0)
ax.imshow(gradient, cmap='cool', aspect='auto', extent=[0, 1, 0, 1], alpha=0.3)
Frequency bars
freq_bars = ax.bar(np.linspace(0.2, 0.8, 64), np.zeros(64), color='cyan', alpha=0.8, width=0.008)
Waveform
waveform, = ax.plot([], [], color='white', alpha=0.8, linewidth=2)
Time text
text_obj = ax.text(0.02, 0.98, "", transform=ax.transAxes, fontsize=16, color='white',
verticalalignment='top')
Scatter particles
scatter = ax.scatter([], [], s=50, c=[], cmap='viridis', alpha=0.6)
Pulsing circle
circle = plt.Circle((0.5, 0.5), 0.4, color='cyan', fill=False, linewidth=2, alpha=0.8)
ax.add_patch(circle)
return fig, ax, freq_bars, waveform, text_obj, scatter, circle
def update_animation(frame, mel_spec_db, y, sr, freq_bars, waveform, text_obj, scatter, circle):
spec_slice = mel_spec_db[:, frame]
bar_heights = np.interp(spec_slice, (spec_slice.min(), spec_slice.max()), (0, 1))
Update frequency bars
for bar, h in zip(freq_bars, bar_heights[:64]):
bar.set_height(h)
energy = np.mean(bar_heights)
Update bar colors
for bar in freq_bars:
bar.set_color(plt.cm.viridis(energy))
start = int(frame / 30 * sr)
end = start + sr // 30
waveform_data = y[start:end]
waveform_x = np.linspace(0, 1, len(waveform_data))
waveform_y = waveform_data * 0.3 + 0.5
waveform.set_data(waveform_x, waveform_y)
Update time text
current_time = frame / 30
minutes = int(current_time // 60)
seconds = int(current_time % 60)
text_obj.set_text(f"{minutes:02d}:{seconds:02d}")
Update scatter plot
scatter.set_offsets(np.c_[np.random.rand(100), np.random.rand(100)])
scatter.set_array(np.random.rand(100))
Update pulsing circle
circle.set_radius(0.3 + 0.1 * np.sin(2 * np.pi * frame / 30))
circle.set_edgecolor(plt.cm.viridis(energy))
return list(freq_bars) + [waveform, text_obj, scatter, circle]
def create_animation(mel_spec_db, y, sr):
fig, ax, freq_bars, waveform, text_obj, scatter, circle = create_base_animation()
duration = len(y) / sr
anim = FuncAnimation(fig, update_animation, frames=int(duration * 30),
fargs=(mel_spec_db, y, sr, freq_bars, waveform, text_obj, scatter, circle),
interval=33.33, blit=True)
return anim, fig
def render_animation(anim, fig, audio_path, output_path):
with tempfile.NamedTemporaryFile(suffix='.mp4', delete=False) as temp_video:
anim.save(temp_video.name, fps=30, bitrate=5000, extra_args=['-vcodec', 'libx264'])
plt.close(fig)
video = VideoFileClip(temp_video.name)
audio = AudioFileClip(audio_path)
video = video.set_duration(audio.duration)
final_video = video.set_audio(audio)
final_video.write_videofile(output_path, codec='libx264', audio_codec='aac')
video.close()
audio.close()
final_video.close()
os.unlink(temp_video.name)
def main(audio_path, output_path):
y, sr, mel_spec_db = load_and_preprocess_music(audio_path)
anim, fig = create_animation(mel_spec_db, y, sr)
render_animation(anim, fig, audio_path, output_path)
print(f"Animation saved to {output_path}")
if _name_ == "__main__":
audio_path = "/content/drive/MyDrive/Shadow20ext%20v2.mp3" # Replace with your audio file path
output_path = "enhanced_music_visualizer.mp4"
main(audio_path, output_path)