Update app.py
Browse files
app.py
CHANGED
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import spaces
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import gradio as gr
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import tempfile
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import numpy as np
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import os
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import subprocess
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import shutil
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import
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try:
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start_video.save(video_tmpfile.name, format="MP4")
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video_path = video_tmpfile.name
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blurred_video_path = blur_tmpfile.name
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def check_ffmpeg():
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try:
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subprocess.run(
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return False
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if __name__ == "__main__":
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import spaces
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import gradio as gr
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import tempfile
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import os
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import subprocess
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import shutil
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import asyncio
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from pathlib import Path
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import uuid
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import logging
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# Настройка логирования
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logging.basicConfig(level=logging.INFO)
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logger = logging.getLogger(__name__)
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# Конфигурация
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MAX_PROCESS_TIMEOUT = 120
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TEMP_BASE_DIR = Path("/tmp/video_processing")
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TEMP_BASE_DIR.mkdir(exist_ok=True, parents=True)
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async def run_ffmpeg_async(cmd, timeout=120):
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"""Асинхронный запуск ffmpeg с таймаутом"""
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try:
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process = await asyncio.create_subprocess_exec(
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*cmd,
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stdout=asyncio.subprocess.PIPE,
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stderr=asyncio.subprocess.PIPE
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)
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try:
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stdout, stderr = await asyncio.wait_for(
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process.communicate(),
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timeout=timeout
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)
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if process.returncode != 0:
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error_msg = stderr.decode() if stderr else "Unknown error"
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logger.error(f"FFmpeg error: {error_msg}")
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raise Exception(f"FFmpeg failed: {error_msg}")
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return stdout, stderr
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except asyncio.TimeoutError:
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try:
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process.kill()
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except:
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pass
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raise Exception(f"FFmpeg timeout after {timeout} seconds")
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except Exception as e:
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logger.error(f"FFmpeg execution error: {e}")
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raise
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async def process_video_with_resources(start_video, job_id):
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"""Обработка видео с изоляцией ресурсов"""
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# Создаем уникальную рабочую директорию для каждого задания
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work_dir = TEMP_BASE_DIR / job_id
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work_dir.mkdir(exist_ok=True)
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# Пути к файлам
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input_path = work_dir / "input.mp4"
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audio_path = work_dir / "with_audio.mp4"
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blurred_path = work_dir / "blurred.mp4"
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try:
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# Шаг 1: Сохраняем входное видео
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if isinstance(start_video, str):
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shutil.copy(start_video, str(input_path))
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else:
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# Для объектов Gradio Video
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with open(input_path, "wb") as f:
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# Gradio Video возвращает временный файл
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if hasattr(start_video, "name"):
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with open(start_video.name, "rb") as src:
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f.write(src.read())
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else:
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# Fallback
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import io
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if isinstance(start_video, io.IOBase):
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f.write(start_video.read())
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# Шаг 2: Добавляем аудио
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cmd_add_audio = [
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'ffmpeg',
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'-f', 'lavfi',
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'-i', 'anullsrc=channel_layout=stereo:sample_rate=44100',
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'-i', str(input_path),
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'-c:v', 'copy',
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'-c:a', 'aac',
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'-shortest',
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'-threads', '2',
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'-loglevel', 'error',
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'-y',
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str(audio_path)
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]
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await run_ffmpeg_async(cmd_add_audio, timeout=MAX_PROCESS_TIMEOUT)
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# Шаг 3: Применяем размытие
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cmd_blur = [
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'ffmpeg',
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'-i', str(audio_path),
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'-vf', 'gblur=sigma=25',
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'-c:a', 'copy',
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'-threads', '2',
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'-loglevel', 'error',
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'-y',
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str(blurred_path)
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]
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await run_ffmpeg_async(cmd_blur, timeout=MAX_PROCESS_TIMEOUT)
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# Возвращаем пути к результатам
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return str(audio_path), str(blurred_path)
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except Exception as e:
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logger.error(f"Processing error for job {job_id}: {e}")
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# Удаляем рабочую директорию в случае ошибки
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try:
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shutil.rmtree(work_dir)
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except:
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pass
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raise
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finally:
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# Удаляем только входной файл, результаты остаются
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try:
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if input_path.exists():
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input_path.unlink()
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except:
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pass
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async def finalise_video(start_video):
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"""Основная функция обработки видео"""
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job_id = str(uuid.uuid4())
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logger.info(f"Starting video processing job: {job_id}")
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try:
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# Обрабатываем видео
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output_path1, output_path2 = await process_video_with_resources(
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start_video, job_id
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)
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logger.info(f"Completed video processing job: {job_id}")
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return output_path1, output_path2
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except Exception as e:
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logger.error(f"Finalise video error: {e}")
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raise gr.Error(f"Ошибка обработки видео: {str(e)}")
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def check_ffmpeg():
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"""Проверка доступности ffmpeg"""
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try:
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result = subprocess.run(
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['ffmpeg', '-version'],
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capture_output=True,
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text=True,
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timeout=5
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)
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return result.returncode == 0
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except Exception:
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return False
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def cleanup_old_files():
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"""Фоновая очистка старых файлов"""
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try:
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import time
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current_time = time.time()
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for item in TEMP_BASE_DIR.iterdir():
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try:
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if item.is_dir():
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# Удаляем директории старше 1 часа
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stat = item.stat()
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dir_age = current_time - stat.st_ctime
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if dir_age > 3600: # 1 час
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shutil.rmtree(item, ignore_errors=True)
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logger.info(f"Cleaned up old directory: {item}")
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except Exception as e:
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logger.warning(f"Failed to clean up {item}: {e}")
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except Exception as e:
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logger.error(f"Cleanup error: {e}")
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# Создаем интерфейс Gradio
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# ИСПРАВЛЕНИЕ: убрали theme из конструктора Blocks
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with gr.Blocks() as demo:
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gr.Markdown("# Видео Финализатор")
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with gr.Row():
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with gr.Column(scale=1):
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input_video = gr.Video(
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label="Входное видео",
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interactive=True
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)
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process_btn = gr.Button(
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"Обработать видео",
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variant="primary"
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)
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with gr.Column(scale=2):
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with gr.Row():
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output1 = gr.Video(
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label="Видео с аудио",
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autoplay=True,
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interactive=False
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)
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output2 = gr.Video(
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label="Размытое видео",
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autoplay=True,
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interactive=False
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)
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# Обработчик без ограничений параллелизма
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process_btn.click(
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fn=finalise_video,
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inputs=[input_video],
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outputs=[output1, output2]
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)
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if __name__ == "__main__":
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# Проверяем ffmpeg
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if not check_ffmpeg():
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logger.error("FFmpeg не найден! Установите ffmpeg.")
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print("Ошибка: FFmpeg не установлен.")
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# Периодическая очистка старых файлов
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import threading
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import time
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def cleanup_thread():
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while True:
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cleanup_old_files()
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time.sleep(3600) # Каждый час
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cleanup_thread = threading.Thread(target=cleanup_thread, daemon=True)
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cleanup_thread.start()
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# ИСПРАВЛЕНИЕ: правильный запуск для Gradio 4.0+
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# Убраны несовместимые параметры: enable_queue, max_threads
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demo.queue(max_size=100).launch(
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server_name="0.0.0.0",
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server_port=7860
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)
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