Spaces:
Running
Running
Update app.py
Browse files
app.py
CHANGED
@@ -3,64 +3,83 @@ import moviepy.editor as mp
|
|
3 |
import numpy as np
|
4 |
import librosa
|
5 |
import matplotlib.pyplot as plt
|
6 |
-
import
|
|
|
7 |
|
8 |
-
|
|
|
|
|
|
|
|
|
9 |
try:
|
10 |
-
# Cargar audio
|
11 |
-
|
|
|
12 |
duration = librosa.get_duration(y=y, sr=sr)
|
|
|
13 |
|
14 |
-
# Cargar imagen
|
15 |
-
|
16 |
-
|
17 |
-
|
18 |
-
if effect_type == "waveform":
|
19 |
-
audio_envelope = np.abs(y) # Envelope del audio
|
20 |
-
audio_envelope = (audio_envelope / np.max(audio_envelope)) * (img_clip.h / 2)
|
21 |
|
22 |
-
|
23 |
-
|
24 |
-
|
25 |
-
|
26 |
-
ax.axis('off')
|
27 |
-
|
28 |
-
time_index = int(t * sr)
|
29 |
-
wave_slice = audio_envelope[max(0, time_index - sr//10):min(len(audio_envelope), time_index + sr//10)]
|
30 |
-
ax.plot(np.linspace(t-0.1, t+0.1, len(wave_slice)), wave_slice - img_clip.h/4, color='red')
|
31 |
-
ax.plot(np.linspace(t-0.1, t+0.1, len(wave_slice)), -wave_slice + img_clip.h/4, color='red')
|
32 |
-
|
33 |
-
buf = io.BytesIO()
|
34 |
-
fig.savefig(buf, format='png', bbox_inches='tight', pad_inches=0)
|
35 |
-
plt.close(fig)
|
36 |
-
return np.array(Image.open(buf)) # Convertir a array de imagen
|
37 |
|
38 |
-
|
39 |
-
|
40 |
-
|
41 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
42 |
|
43 |
-
|
44 |
-
|
45 |
-
|
46 |
-
|
47 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
48 |
|
49 |
except Exception as e:
|
|
|
50 |
return f"Error: {str(e)}"
|
51 |
|
52 |
-
# Interfaz
|
53 |
iface = gr.Interface(
|
54 |
-
fn=
|
55 |
inputs=[
|
56 |
-
gr.Audio(type="filepath", label="
|
57 |
-
gr.Image(type="filepath", label="
|
58 |
-
gr.Radio(["waveform"], value="waveform", label="Efecto Visual")
|
59 |
],
|
60 |
-
outputs=gr.Video(label="Video
|
61 |
-
title="
|
62 |
-
description="
|
|
|
63 |
)
|
64 |
|
65 |
if __name__ == "__main__":
|
66 |
-
|
|
|
|
3 |
import numpy as np
|
4 |
import librosa
|
5 |
import matplotlib.pyplot as plt
|
6 |
+
from io import BytesIO
|
7 |
+
import logging
|
8 |
|
9 |
+
# Configuración de logging
|
10 |
+
logging.basicConfig(level=logging.INFO)
|
11 |
+
logger = logging.getLogger("audio_to_video")
|
12 |
+
|
13 |
+
def generate_waveform_video(audio_path, image_path):
|
14 |
try:
|
15 |
+
# 1. Cargar audio
|
16 |
+
logger.info("Cargando archivo de audio...")
|
17 |
+
y, sr = librosa.load(audio_path)
|
18 |
duration = librosa.get_duration(y=y, sr=sr)
|
19 |
+
logger.info(f"Duración del audio: {duration:.2f} segundos")
|
20 |
|
21 |
+
# 2. Cargar imagen
|
22 |
+
logger.info("Procesando imagen...")
|
23 |
+
img_clip = mp.ImageClip(image_path).set_duration(duration)
|
24 |
+
img_width, img_height = img_clip.size
|
|
|
|
|
|
|
25 |
|
26 |
+
# 3. Crear efecto de waveform
|
27 |
+
logger.info("Generando efecto visual...")
|
28 |
+
audio_envelope = np.abs(y) # Envelope del audio
|
29 |
+
audio_envelope = (audio_envelope / np.max(audio_envelope)) * (img_height // 3)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
30 |
|
31 |
+
def make_frame(t):
|
32 |
+
fig, ax = plt.subplots(figsize=(img_width/100, img_height/100), dpi=100)
|
33 |
+
ax.set_xlim(0, duration)
|
34 |
+
ax.set_ylim(-img_height//2, img_height//2)
|
35 |
+
ax.axis('off')
|
36 |
+
|
37 |
+
time_index = int(t * sr)
|
38 |
+
start = max(0, time_index - sr//10)
|
39 |
+
end = min(len(audio_envelope), time_index + sr//10)
|
40 |
+
wave_slice = audio_envelope[start:end]
|
41 |
+
|
42 |
+
x_values = np.linspace(t-0.1, t+0.1, len(wave_slice))
|
43 |
+
ax.fill_between(x_values, wave_slice - img_height//4, -wave_slice + img_height//4,
|
44 |
+
facecolor='red', alpha=0.7)
|
45 |
+
|
46 |
+
buf = BytesIO()
|
47 |
+
plt.savefig(buf, format='png', bbox_inches='tight', pad_inches=0)
|
48 |
+
plt.close(fig)
|
49 |
+
return mp.ImageClip(buf).get_frame(0)
|
50 |
|
51 |
+
logger.info("Renderizando video...")
|
52 |
+
effect_clip = mp.VideoClip(make_frame, duration=duration).set_fps(24)
|
53 |
+
final_clip = mp.CompositeVideoClip([img_clip, effect_clip.set_pos("center")])
|
54 |
+
|
55 |
+
# 4. Combinar con audio
|
56 |
+
final_clip = final_clip.set_audio(mp.AudioFileClip(audio_path))
|
57 |
+
|
58 |
+
# 5. Guardar en memoria
|
59 |
+
buffer = BytesIO()
|
60 |
+
final_clip.write_videofile(buffer, fps=24, codec="libx264",
|
61 |
+
audio_codec="aac", logger=None)
|
62 |
+
buffer.seek(0)
|
63 |
+
logger.info("Video generado exitosamente")
|
64 |
+
return buffer
|
65 |
|
66 |
except Exception as e:
|
67 |
+
logger.error(f"Error durante la generación: {str(e)}")
|
68 |
return f"Error: {str(e)}"
|
69 |
|
70 |
+
# Interfaz Gradio
|
71 |
iface = gr.Interface(
|
72 |
+
fn=generate_waveform_video,
|
73 |
inputs=[
|
74 |
+
gr.Audio(type="filepath", label="Audio (WAV/MP3)"),
|
75 |
+
gr.Image(type="filepath", label="Imagen de Fondo"),
|
|
|
76 |
],
|
77 |
+
outputs=gr.Video(label="Video Resultante", format="mp4"),
|
78 |
+
title="Generador de Video con Efectos de Audio",
|
79 |
+
description="Crea videos con efectos visuales sincronizados con el audio. Actualmente soporta efecto de waveform.",
|
80 |
+
allow_flagging="never"
|
81 |
)
|
82 |
|
83 |
if __name__ == "__main__":
|
84 |
+
logger.info("Iniciando aplicación Gradio...")
|
85 |
+
iface.queue().launch(share=False, debug=True)
|