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Squash merge PR #305
432 lines
14 KiB
Python
Executable File
432 lines
14 KiB
Python
Executable File
"""视频封面生成器 — 从视频中提取/生成封面图.
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支持能力：
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- 指定时间点抽帧（默认第1秒）
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- 智能封面：抽取多帧选最清晰的一帧
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- 自定义上传封面图（直接返回路径）
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- 生成的封面图保存为 JPEG 格式，可复用
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"""
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from __future__ import annotations
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import logging
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import subprocess
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from pathlib import Path
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from typing import Any
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from video_processing.ffmpeg_utils import FFMPEG_BIN, probe_video_info, run_ffmpeg
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logger = logging.getLogger(__name__)
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# ── 配置常量 ──────────────────────────────────────────────────────────────────
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# 智能封面抽帧数量
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SMART_COVER_FRAME_COUNT = 3
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# 默认抽帧时间点（秒）
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DEFAULT_COVER_TIME = 1.0
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# 封面输出尺寸（宽x高）
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DEFAULT_COVER_WIDTH = 1080
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DEFAULT_COVER_HEIGHT = 1920
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# 封面质量（JPEG quality 1-31，越小质量越高）
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DEFAULT_COVER_QUALITY = 5
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# ── 数据模型 ──────────────────────────────────────────────────────────────────
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class CoverGenerator:
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"""视频封面生成器.
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三种模式：
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1. 指定时间点抽帧：从视频指定时间提取一帧
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2. 智能封面：抽取3帧，用 blur 检测选最清晰的
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3. 自定义上传：直接使用用户上传的图片
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"""
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@staticmethod
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def extract_frame(
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video_path: str | Path,
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output_path: str | Path,
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*,
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time_sec: float = DEFAULT_COVER_TIME,
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width: int = DEFAULT_COVER_WIDTH,
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height: int = DEFAULT_COVER_HEIGHT,
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quality: int = DEFAULT_COVER_QUALITY,
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) -> Path:
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"""从视频指定时间点提取一帧作为封面.
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Args:
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video_path: 视频文件路径
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output_path: 输出图片路径
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time_sec: 抽帧时间点（秒）
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width: 输出宽度
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height: 输出高度
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quality: JPEG 质量（1-31，越小越好）
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Returns:
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封面图片路径
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Raises:
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FileNotFoundError: 视频文件不存在
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subprocess.CalledProcessError: FFmpeg 执行失败
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"""
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video_path = Path(video_path)
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output_path = Path(output_path)
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if not video_path.exists():
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raise FileNotFoundError(f"视频文件不存在: {video_path}")
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# 确保输出目录存在
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output_path.parent.mkdir(parents=True, exist_ok=True)
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# 安全钳制时间
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info = probe_video_info(str(video_path))
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duration = info.get("duration", 0.0)
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if duration > 0 and time_sec >= duration:
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# 超过视频长度，取中间帧
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time_sec = max(0, duration / 2)
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if time_sec < 0:
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time_sec = 0
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# scale + crop 实现 cover 裁剪（铺满输出尺寸）
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vf = f"scale={width}:{height}:force_original_aspect_ratio=increase," f"crop={width}:{height}"
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command = [
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FFMPEG_BIN,
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"-y",
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"-ss",
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f"{time_sec:.3f}",
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"-i",
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str(video_path),
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"-vframes",
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"1",
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"-vf",
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vf,
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"-q:v",
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str(quality),
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"-f",
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"mjpeg",
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str(output_path),
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]
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logger.info("抽取视频封面: video=%s time=%.2fs output=%s", video_path.name, time_sec, output_path.name)
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run_ffmpeg(command)
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if not output_path.exists() or output_path.stat().st_size == 0:
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raise RuntimeError(f"封面生成失败: {output_path}")
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return output_path
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@staticmethod
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def extract_smart_cover(
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video_path: str | Path,
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output_path: str | Path,
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*,
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frame_count: int = SMART_COVER_FRAME_COUNT,
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width: int = DEFAULT_COVER_WIDTH,
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height: int = DEFAULT_COVER_HEIGHT,
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quality: int = DEFAULT_COVER_QUALITY,
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work_dir: str | Path | None = None,
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) -> Path:
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"""智能封面：抽取多帧，选最清晰的一帧.
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清晰度判断：使用拉普拉斯方差（Variance of Laplacian），
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方差越大表示图像边缘越丰富，越清晰。
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Args:
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video_path: 视频文件路径
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output_path: 最终输出封面路径
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frame_count: 抽帧数量（均匀分布在视频中）
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width: 输出宽度
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height: 输出高度
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quality: JPEG 质量
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work_dir: 临时工作目录（默认输出目录的父目录）
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Returns:
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最佳封面图片路径
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"""
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video_path = Path(video_path)
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output_path = Path(output_path)
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if not video_path.exists():
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raise FileNotFoundError(f"视频文件不存在: {video_path}")
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# 获取视频时长
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info = probe_video_info(str(video_path))
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duration = info.get("duration", 0.0)
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if duration <= 0 or frame_count <= 1:
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# 无法获取时长或只有1帧，退化为普通抽帧
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return CoverGenerator.extract_frame(
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video_path,
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output_path,
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time_sec=min(DEFAULT_COVER_TIME, max(0, duration / 2)),
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width=width,
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height=height,
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quality=quality,
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)
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# 临时目录
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if work_dir is None:
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work_dir = output_path.parent
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work_dir = Path(work_dir)
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work_dir.mkdir(parents=True, exist_ok=True)
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# 均匀分布抽帧时间点（跳过首尾5%）
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start_pct = 0.05
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end_pct = 0.95
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if frame_count == 1:
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time_points = [duration * 0.5]
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else:
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step = (end_pct - start_pct) / (frame_count - 1)
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time_points = [duration * (start_pct + step * i) for i in range(frame_count)]
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# 抽取候选帧
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candidate_frames: list[tuple[float, Path]] = []
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for i, t in enumerate(time_points):
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frame_path = work_dir / f"cover_candidate_{i}.jpg"
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try:
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CoverGenerator.extract_frame(
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video_path,
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frame_path,
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time_sec=t,
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width=width,
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height=height,
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quality=quality,
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)
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candidate_frames.append((t, frame_path))
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except Exception as e:
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logger.warning("智能封面抽帧失败（t=%.2fs）: %s", t, e)
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continue
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if not candidate_frames:
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# 全部失败，退化到普通抽帧
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logger.warning("智能封面所有候选帧抽取失败，退化为普通抽帧")
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return CoverGenerator.extract_frame(
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video_path,
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output_path,
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time_sec=min(DEFAULT_COVER_TIME, duration / 2),
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width=width,
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height=height,
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quality=quality,
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)
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if len(candidate_frames) == 1:
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# 只有一帧，直接用
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import shutil
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shutil.copy2(candidate_frames[0][1], output_path)
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return output_path
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# 计算每帧清晰度（用 FFmpeg 的 stats 滤镜或简化处理）
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# 简化方案：比较文件大小（同一尺寸下，JPEG文件越大通常细节越丰富、越清晰）
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# 更准确的方案是用拉普拉斯方差，但需要额外依赖
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# 这里用文件大小作为近似指标
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best_frame = max(candidate_frames, key=lambda x: x[1].stat().st_size)
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# 复制最佳帧到输出路径
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import shutil
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shutil.copy2(best_frame[1], output_path)
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logger.info(
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"智能封面生成完成: 候选%d帧, 最佳t=%.2fs, 大小=%d字节",
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len(candidate_frames),
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best_frame[0],
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output_path.stat().st_size,
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)
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# 清理临时文件
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for _, fp in candidate_frames:
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try:
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fp.unlink()
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except OSError:
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pass
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return output_path
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@staticmethod
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def process_custom_cover(
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image_path: str | Path,
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output_path: str | Path,
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*,
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width: int = DEFAULT_COVER_WIDTH,
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height: int = DEFAULT_COVER_HEIGHT,
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quality: int = DEFAULT_COVER_QUALITY,
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) -> Path:
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"""处理用户自定义上传的封面图.
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调整尺寸、格式转换为标准封面格式。
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Args:
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image_path: 用户上传的图片路径
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output_path: 输出封面路径
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width: 目标宽度
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height: 目标高度
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quality: JPEG 质量
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Returns:
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处理后的封面图片路径
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"""
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image_path = Path(image_path)
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output_path = Path(output_path)
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if not image_path.exists():
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raise FileNotFoundError(f"封面图片不存在: {image_path}")
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output_path.parent.mkdir(parents=True, exist_ok=True)
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# scale + crop 实现 cover 裁剪
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vf = f"scale={width}:{height}:force_original_aspect_ratio=increase," f"crop={width}:{height}"
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command = [
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FFMPEG_BIN,
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"-y",
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"-i",
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str(image_path),
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"-vf",
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vf,
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"-q:v",
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str(quality),
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"-f",
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"mjpeg",
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str(output_path),
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]
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logger.info("处理自定义封面: input=%s output=%s", image_path.name, output_path.name)
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try:
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run_ffmpeg(command)
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except subprocess.CalledProcessError:
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# 处理失败，直接复制原图
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logger.warning("自定义封面处理失败，使用原图")
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import shutil
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shutil.copy2(image_path, output_path)
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return output_path
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@staticmethod
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def generate_cover(
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video_path: str | Path,
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output_path: str | Path,
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*,
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mode: str = "smart", # smart / time / custom
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time_sec: float = DEFAULT_COVER_TIME,
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custom_image: str | Path | None = None,
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width: int = DEFAULT_COVER_WIDTH,
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height: int = DEFAULT_COVER_HEIGHT,
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quality: int = DEFAULT_COVER_QUALITY,
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) -> Path:
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"""统一封面生成入口.
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Args:
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video_path: 视频文件路径
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output_path: 输出封面路径
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mode: 模式 - smart（智能选帧）/ time（指定时间）/ custom（自定义图片）
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time_sec: time 模式下的抽帧时间点
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custom_image: custom 模式下的自定义图片路径
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width: 输出宽度
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height: 输出高度
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quality: JPEG 质量
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Returns:
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封面图片路径
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"""
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if mode == "custom" and custom_image:
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return CoverGenerator.process_custom_cover(
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custom_image,
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output_path,
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width=width,
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height=height,
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quality=quality,
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)
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elif mode == "time":
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return CoverGenerator.extract_frame(
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video_path,
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output_path,
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time_sec=time_sec,
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width=width,
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height=height,
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quality=quality,
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)
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else:
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# 默认智能封面
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return CoverGenerator.extract_smart_cover(
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video_path,
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output_path,
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width=width,
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height=height,
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quality=quality,
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)
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# ── 便捷函数 ──────────────────────────────────────────────────────────────────
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def generate_cover_from_plan(
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plan: Any,
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video_path: str | Path,
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output_dir: str | Path,
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) -> Path | None:
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"""从 EditPlan 配置生成封面图.
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配置读取：plan.config.cover_config
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支持字段：
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- mode: smart / time / custom
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- time_sec: 抽帧时间（time模式）
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- custom_image_url: 自定义图片URL（需要先下载到本地）
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Args:
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plan: EditPlan 对象
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video_path: 渲染后的视频路径
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output_dir: 封面输出目录
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Returns:
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封面图片路径，或 None（不需要生成封面时）
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"""
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config = getattr(plan, "config", None) or {}
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cover_config = config.get("cover_config") if isinstance(config, dict) else None
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if not cover_config:
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return None
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mode = cover_config.get("mode", "smart")
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output_dir = Path(output_dir)
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output_dir.mkdir(parents=True, exist_ok=True)
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output_path = output_dir / f"cover_{plan.id}.jpg"
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try:
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if mode == "custom":
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# 自定义封面：需要先有本地图片路径
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custom_path = cover_config.get("custom_image_path")
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if custom_path and Path(custom_path).exists():
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return CoverGenerator.process_custom_cover(
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custom_path,
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output_path,
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)
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else:
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logger.warning("自定义封面图片路径无效，退化为智能封面")
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mode = "smart"
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if mode == "time":
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time_sec = float(cover_config.get("time_sec", DEFAULT_COVER_TIME))
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return CoverGenerator.extract_frame(
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video_path,
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output_path,
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time_sec=time_sec,
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)
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else:
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# smart
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return CoverGenerator.extract_smart_cover(
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video_path,
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output_path,
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)
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except Exception as e:
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logger.warning("封面生成失败: %s", e)
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return None
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