Spaces:
Sleeping
Sleeping
File size: 2,994 Bytes
9857383 be67e91 5ef121d 9857383 be67e91 9857383 fec5702 35ee7d1 be67e91 9857383 35ee7d1 be67e91 9857383 35ee7d1 be67e91 9857383 35ee7d1 be67e91 35ee7d1 be67e91 35ee7d1 be67e91 35ee7d1 be67e91 35ee7d1 be67e91 5ef121d be67e91 35ee7d1 fec5702 9857383 be67e91 35ee7d1 be67e91 9857383 fec5702 9857383 35ee7d1 9857383 35ee7d1 9857383 35ee7d1 9857383 35ee7d1 be67e91 9857383 88eef70 be67e91 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 |
import gradio as gr
import moviepy.editor as mp
import numpy as np
import librosa
import matplotlib.pyplot as plt
from PIL import Image
import tempfile
import os
import io # Importar el m贸dulo 'io'
def generate_waveform_video(audio_file, image_file):
try:
# Validar que los archivos existan
if not os.path.exists(audio_file):
raise ValueError("Archivo de audio no encontrado")
if not os.path.exists(image_file):
raise ValueError("Archivo de imagen no encontrado")
# 1. Cargar audio
y, sr = librosa.load(audio_file)
duration = librosa.get_duration(y=y, sr=sr)
# 2. Cargar imagen
img_clip = mp.ImageClip(image_file).set_duration(duration)
img_w, img_h = img_clip.size
# 3. Crear efecto de waveform
audio_envelope = np.abs(y)
audio_envelope = (audio_envelope / np.max(audio_envelope)) * (img_h // 3)
def make_frame(t):
fig, ax = plt.subplots(figsize=(img_w/100, img_h/100), dpi=100)
ax.set_xlim(0, duration)
ax.set_ylim(-img_h//2, img_h//2)
ax.axis('off')
time_idx = int(t * sr)
start = max(0, time_idx - sr//10)
end = min(len(audio_envelope), time_idx + sr//10)
wave_slice = audio_envelope[start:end]
x = np.linspace(t-0.1, t+0.1, len(wave_slice))
ax.fill_between(x, wave_slice - img_h//4, -wave_slice + img_h//4,
facecolor='red', alpha=0.7)
# Convertir figura a numpy array usando io.BytesIO
buf = io.BytesIO()
plt.savefig(buf, format='png', bbox_inches='tight', pad_inches=0)
plt.close(fig)
return np.array(Image.open(buf))
# Crear video
effect_clip = mp.VideoClip(make_frame, duration=duration).set_fps(24)
final_clip = mp.CompositeVideoClip([img_clip, effect_clip.set_pos("center")])
final_clip = final_clip.set_audio(mp.AudioFileClip(audio_file))
# Guardar en archivo temporal
with tempfile.NamedTemporaryFile(suffix=".mp4", delete=False) as tmpfile:
final_clip.write_videofile(tmpfile.name, fps=24, codec="libx264",
audio_codec="aac", logger=None)
return tmpfile.name
except Exception as e:
# Lanzar excepci贸n para que Gradio muestre el error
raise Exception(f"Error durante la generaci贸n: {str(e)}")
# Interfaz Gradio
iface = gr.Interface(
fn=generate_waveform_video,
inputs=[
gr.Audio(type="filepath", label="Audio (WAV/MP3)"),
gr.Image(type="filepath", label="Imagen de Fondo"),
],
outputs=gr.Video(label="Video Resultante", format="mp4"),
title="Generador de Video con Efectos de Audio",
description="Crea videos con efectos visuales sincronizados con el audio. Actualmente soporta efecto de waveform."
)
if __name__ == "__main__":
iface.queue().launch() |