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import tempfile | |
import logging | |
import os | |
import asyncio | |
from moviepy.editor import * | |
import edge_tts | |
import gradio as gr | |
from pydub import AudioSegment | |
# Configuración de Logs | |
logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s") | |
# CONSTANTES DE ARCHIVOS | |
INTRO_VIDEO = "introvideo.mp4" | |
OUTRO_VIDEO = "outrovideo.mp4" | |
MUSIC_BG = "musicafondo.mp3" | |
GLITCH_SOUND = "fxsound.mp3" | |
EJEMPLO_VIDEO = "ejemplo.mp4" | |
# Validar existencia de archivos | |
for file in [INTRO_VIDEO, OUTRO_VIDEO, MUSIC_BG, GLITCH_SOUND, EJEMPLO_VIDEO]: | |
if not os.path.exists(file): | |
logging.error(f"Falta archivo necesario: {file}") | |
raise FileNotFoundError(f"Falta: {file}") | |
# Configuración de chunks | |
CHUNK_SIZE = 60 # 1 minuto por chunk | |
MAX_CHUNKS = 50 | |
def eliminar_archivo_tiempo(ruta, delay=1800): | |
def eliminar(): | |
try: | |
if os.path.exists(ruta): | |
os.remove(ruta) | |
logging.info(f"Archivo eliminado: {ruta}") | |
except Exception as e: | |
logging.error(f"Error al eliminar {ruta}: {e}") | |
from threading import Timer | |
Timer(delay, eliminar).start() | |
async def procesar_audio(texto, voz, duracion_video, audio_original=None): | |
temp_files = [] | |
try: | |
logging.info("Iniciando procesamiento de audio") | |
if not texto.strip(): | |
raise ValueError("El texto para TTS no puede estar vacío.") | |
def dividir_texto(texto, max_length=2000): | |
return [texto[i:i + max_length] for i in range(0, len(texto), max_length)] | |
fragmentos = dividir_texto(texto) | |
audios_tts = [] | |
for fragmento in fragmentos: | |
communicate = edge_tts.Communicate(fragmento, voz) | |
with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as tmp_tts: | |
await communicate.save(tmp_tts.name) | |
tts_audio = AudioFileClip(tmp_tts.name) | |
temp_files.append(tmp_tts.name) | |
audios_tts.append(tts_audio) | |
tts_audio_final = concatenate_audioclips(audios_tts) | |
if tts_audio_final.duration > duracion_video: | |
tts_audio_final = tts_audio_final.subclip(0, duracion_video) | |
needed_ms = int(duracion_video * 1000) | |
bg_music = AudioSegment.from_mp3(MUSIC_BG) | |
repeticiones = needed_ms // len(bg_music) + 1 | |
bg_music = bg_music * repeticiones | |
bg_music = bg_music[:needed_ms].fade_out(1000) | |
with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as tmp_bg: | |
bg_music.export(tmp_bg.name, format="mp3") | |
bg_audio = AudioFileClip(tmp_bg.name).volumex(0.15) | |
temp_files.append(tmp_bg.name) | |
audios = [bg_audio.set_duration(duracion_video)] | |
if audio_original: | |
audios.append(audio_original.volumex(0.7)) | |
audios.append(tts_audio_final.volumex(0.85).set_start(0)) | |
audio_final = CompositeAudioClip(audios).set_duration(duracion_video) | |
logging.info("Audio procesado exitosamente") | |
return audio_final, temp_files # Retornamos los archivos temporales para limpieza | |
except Exception as e: | |
logging.error(f"Fallo en procesamiento de audio: {str(e)}") | |
raise | |
def aplicar_glitch(video_clip): | |
def glitch_effect(frame): | |
import numpy as np | |
frame = frame.copy() | |
height, width, _ = frame.shape | |
offset = np.random.randint(3, 8) | |
if height > 0 and offset != 0: | |
frame[offset:, :] = np.roll(frame[:-offset, :], -offset, axis=0) | |
return frame | |
return video_clip.fl_image(glitch_effect) | |
async def procesar_fragmento(chunk, texto_tts, voz_seleccionada, start_time): | |
temp_files = [] | |
try: | |
audio_original = chunk.audio | |
duracion_chunk = chunk.duration | |
# Si el chunk es demasiado corto, devolver sin procesar | |
if duracion_chunk <= 18: | |
audio_final, temp_files = await procesar_audio( | |
texto_tts, | |
voz_seleccionada, | |
duracion_chunk, | |
audio_original | |
) | |
return chunk.set_audio(audio_final), temp_files | |
audio_final, temp_files = await procesar_audio( | |
texto_tts, | |
voz_seleccionada, | |
duracion_chunk, | |
audio_original | |
) | |
segment_duration = 18 | |
overlap = 2 | |
segments = [] | |
glitch_clips = [] | |
glitch_sound = AudioFileClip(GLITCH_SOUND).volumex(0.5) | |
current_time = 0 | |
while current_time < duracion_chunk: | |
end_time = current_time + segment_duration | |
end_time = min(end_time, duracion_chunk) | |
full_segment = chunk.subclip(current_time, end_time) | |
if current_time > 0 and full_segment.duration >= 0.5: | |
glitch_part = full_segment.subclip(0, 0.5) | |
glitch_part = aplicar_glitch(glitch_part) | |
processed_segment = concatenate_videoclips([ | |
glitch_part, | |
full_segment.subclip(0.5) | |
], method="compose") | |
glitch_sound_clip = glitch_sound.set_start(start_time + current_time) | |
glitch_clips.append(glitch_sound_clip) | |
else: | |
processed_segment = full_segment | |
segments.append(processed_segment) | |
current_time += (segment_duration - overlap) | |
video_chunk = concatenate_videoclips(segments, method="compose") | |
video_chunk = video_chunk.set_audio(audio_final) | |
return video_chunk, temp_files | |
except Exception as e: | |
logging.error(f"Fallo procesando fragmento: {str(e)}") | |
raise | |
async def procesar_video(video_input, texto_tts, voz_seleccionada): | |
temp_files = [] | |
try: | |
logging.info("Iniciando procesamiento de video") | |
video_original = VideoFileClip(video_input, target_resolution=(720, 1280)) | |
total_duration = video_original.duration | |
# Dividir en chunks | |
chunks = [] | |
for start in range(0, int(total_duration), CHUNK_SIZE): | |
end = min(start + CHUNK_SIZE, total_duration) | |
chunk = video_original.subclip(start, end) | |
chunks.append((start, chunk)) | |
# Procesar cada chunk | |
processed_clips = [] | |
for i, (start_time, chunk) in enumerate(chunks): | |
logging.info(f"Procesando chunk {i+1}/{len(chunks)}") | |
processed_chunk, chunk_temp_files = await procesar_fragmento(chunk, texto_tts, voz_seleccionada, start_time) | |
processed_clips.append(processed_chunk) | |
temp_files.extend(chunk_temp_files) | |
# Combinar chunks | |
final_video = concatenate_videoclips(processed_clips, method="compose") | |
# Agregar intro y outro | |
intro = VideoFileClip(INTRO_VIDEO, target_resolution=(720, 1280)) | |
outro = VideoFileClip(OUTRO_VIDEO, target_resolution=(720, 1280)) | |
final_video = concatenate_videoclips([intro, final_video, outro], method="compose") | |
# Renderizado final | |
with tempfile.NamedTemporaryFile(suffix=".mp4", delete=False) as tmp: | |
final_video.write_videofile( | |
tmp.name, | |
codec="libx264", | |
audio_codec="aac", | |
fps=24, | |
threads=2, | |
bitrate="3M", | |
ffmpeg_params=[ | |
"-preset", "ultrafast", | |
"-crf", "28", | |
"-movflags", "+faststart", | |
"-vf", "scale=1280:720" | |
], | |
verbose=False | |
) | |
eliminar_archivo_tiempo(tmp.name, 1800) | |
logging.info(f"Video final guardado: {tmp.name}") | |
return tmp.name | |
except Exception as e: | |
logging.error(f"Fallo general: {str(e)}") | |
raise | |
finally: | |
try: | |
# Cerrar recursos solo después de completar todo el procesamiento | |
video_original.close() | |
intro.close() | |
outro.close() | |
for file in temp_files: | |
try: | |
os.remove(file) | |
except Exception as e: | |
logging.warning(f"Error limpiando {file}: {e}") | |
except Exception as e: | |
logging.warning(f"Error al cerrar recursos: {str(e)}") | |
# Interfaz Gradio | |
with gr.Blocks() as demo: | |
gr.Markdown("# Editor de Video con IA") | |
with gr.Tab("Principal"): | |
video_input = gr.Video(label="Subir video") | |
texto_tts = gr.Textbox( | |
label="Texto para TTS", | |
lines=3, | |
placeholder="Escribe aquí tu texto..." | |
) | |
voz_seleccionada = gr.Dropdown( | |
label="Voz", | |
choices=["es-ES-AlvaroNeural", "es-MX-BeatrizNeural"], | |
value="es-ES-AlvaroNeural" | |
) | |
procesar_btn = gr.Button("Generar Video") | |
video_output = gr.Video(label="Video Procesado") | |
with gr.Accordion("Ejemplos de Uso", open=False): | |
gr.Examples( | |
examples=[[EJEMPLO_VIDEO, "¡Hola! Esto es una prueba. Suscríbete al canal."]], | |
inputs=[video_input, texto_tts], | |
label="Ejemplos" | |
) | |
procesar_btn.click( | |
procesar_video, | |
inputs=[video_input, texto_tts, voz_seleccionada], | |
outputs=video_output | |
) | |
if __name__ == "__main__": | |
demo.queue().launch() |