WorkBuddy
df56c2c137
内容分四块： 1、产品规划产出 —— MCN 短视频整合营销工作台的①段五份（1a 需求／1b 竞品／1c 画像／1d 策略／1e 场景）、②段两份（2a 功能／2b 布局）、③段界面（DESIGN.md 契约与令牌表 ＋ mcn-workbench.html 原型 ＋ 实测/会诊/审查三份 ＋ 23 张闸门截图）。 2、开源竞品调研 —— 5 个内容工作台项目的取证原始件与 1b 系列分析文档。 3、参考资料 —— 竞品视频抽帧 1145 张 ＋ 2 个源视频 ＋ 功能点截图。 4、机制侧 —— 协作脚本与状态台账、工作区记忆日志、抽帧/OCR 脚本。 .gitignore 只排运行时日志、脚本备份副本与一次性探针输出，其余按原样入库。
136 lines
5.2 KiB
Python
136 lines
5.2 KiB
Python
# -*- coding: utf-8 -*-
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"""按《视频抽帧与字幕规范》严格重抽关键帧。
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与 v1 的差异：
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- 字幕区 scene 检测严格使用底部 15%（B 站 1920x1080 -> 162px；按比例适配其他分辨率）。
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- 新增字幕区低阈值 0.05 作为安全网，防止缓变换句被漏检。
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- 输出 frame_times.json，记录每帧来自哪种检测（便于核对）。
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- 保留首帧 0s、尾帧 DUR-0.3s、>5s 长间隔补中点的规范步骤。
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用法：
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python extract_frames_v2.py --dir <视频目录> --out <帧输出目录> --ff <ffmpeg bin 目录>
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"""
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import argparse, glob, json, os, re, subprocess, sys
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def run(cmd):
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return subprocess.run(cmd, capture_output=True, text=True, encoding="utf-8", errors="replace")
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def probe(video, ffprobe):
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r = run([ffprobe, "-v", "error", "-select_streams", "v:0",
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"-show_entries", "stream=width,height", "-show_entries", "format=duration",
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"-of", "default=nk=1:nw=1", video])
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vals = [x.strip() for x in r.stdout.split("\n") if x.strip()]
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return int(vals[0]), int(vals[1]), float(vals[2])
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def scene_times(video, vf, ffmpeg):
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"""跑一次 scene 检测并返回所有 pts_time（秒）。"""
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r = run([ffmpeg, "-i", video, "-vf", vf + ",showinfo", "-vsync", "vfr", "-f", "null", "-"])
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out = set()
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for line in r.stderr.splitlines():
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m = re.search(r"pts_time:([0-9.]+)", line)
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if m:
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out.add(round(float(m.group(1)), 4))
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return sorted(out)
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def main():
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ap = argparse.ArgumentParser()
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ap.add_argument("--dir", required=True, help="含 .mp4 的目录")
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ap.add_argument("--out", required=True, help="帧输出目录")
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ap.add_argument("--ff", default=r"D:\ComfyUI_windows\ffmpeg-8.0.1-full_build\bin",
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help="ffmpeg/ffprobe 所在 bin 目录")
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args = ap.parse_args()
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ffmpeg = os.path.join(args.ff, "ffmpeg.exe")
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ffprobe = os.path.join(args.ff, "ffprobe.exe")
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vids = sorted(glob.glob(os.path.join(args.dir, "*.mp4")))
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if not vids:
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print("✗ 目录里没有 .mp4：%s" % args.dir)
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sys.exit(1)
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video = vids[0]
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print("视频：%s" % video)
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w, h, dur = probe(video, ffprobe)
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print("分辨率=%dx%d 时长=%.3fs" % (w, h, dur))
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# 字幕区用于 scene 检测：底部 15%（规范参考值）
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sub_h = max(1, int(round(h * 0.15)))
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sub_y = h - sub_h
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crop_vf = "crop=%d:%d:0:%d" % (w, sub_h, sub_y)
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print("字幕区裁剪（检测用）：%s" % crop_vf)
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# ① 画面变化
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t_scene_03 = scene_times(video, "select='gt(scene,0.3)'", ffmpeg)
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# ② 字幕变化（规范核心）
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t_sub_01 = scene_times(video, "%s,select='gt(scene,0.1)'" % crop_vf, ffmpeg)
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# ③ 低阈值补漏（规范标准步骤）
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t_scene_005 = scene_times(video, "select='gt(scene,0.05)'", ffmpeg)
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# 额外安全网：字幕区低阈值，捕获缓变换句
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t_sub_005 = scene_times(video, "%s,select='gt(scene,0.05)'" % crop_vf, ffmpeg)
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print("scene 0.3=%d 字幕区 0.1=%d 全局 0.05=%d 字幕区 0.05=%d"
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% (len(t_scene_03), len(t_sub_01), len(t_scene_005), len(t_sub_005)))
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# 合并 + 首尾
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all_times = sorted(set(t_scene_03) | set(t_sub_01) | set(t_scene_005) | set(t_sub_005))
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all_times.append(0.0)
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all_times.append(max(0.0, round(dur - 0.3, 3)))
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all_times = sorted(set(all_times))
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# >5s 长间隔补中点
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filled = []
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prev = None
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for t in all_times:
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if prev is not None and (t - prev) > 5:
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filled.append(round((t + prev) / 2, 3))
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filled.append(t)
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prev = t
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times = sorted(set(filled))
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print("最终帧数（含首尾+补帧）：%d" % len(times))
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# 记录来源（用于调试/核对）
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source_map = {}
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for t in times:
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tags = []
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if t == 0.0: tags.append("start")
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if abs(t - (dur - 0.3)) < 0.001: tags.append("end")
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if t in t_scene_03: tags.append("scene03")
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if t in t_sub_01: tags.append("sub01")
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if t in t_scene_005: tags.append("scene005")
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if t in t_sub_005: tags.append("sub005")
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if "start" not in tags and "end" not in tags and all(t not in s for s in (t_scene_03, t_sub_01, t_scene_005, t_sub_005)):
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tags.append("fill")
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source_map["%.3f" % t] = tags
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os.makedirs(args.out, exist_ok=True)
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for i, t in enumerate(times, 1):
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tt = t if t <= dur else max(0.0, dur - 0.3)
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outp = os.path.join(args.out, "c_%04d_%.3fs.jpg" % (i, t))
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r = run([ffmpeg, "-y", "-ss", "%.3f" % tt, "-i", video,
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"-frames:v", "1", "-q:v", "2", outp])
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if r.returncode != 0:
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print(" ✗ 帧 %d 失败：%s" % (i, r.stderr[-200:]))
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meta = {
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"video": video, "width": w, "height": h, "duration": dur,
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"subtitle_crop": crop_vf,
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"counts": {
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"scene_0.3": len(t_scene_03), "sub_0.1": len(t_sub_01),
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"scene_0.05": len(t_scene_005), "sub_0.05": len(t_sub_005),
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"final": len(times)
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},
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"frame_times": source_map
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}
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with open(os.path.join(args.out, "frame_times.json"), "w", encoding="utf-8", newline="\n") as f:
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json.dump(meta, f, ensure_ascii=False, indent=2)
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print("✓ 抽帧完成 → %s" % args.out)
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if __name__ == "__main__":
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main()
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