视频音量忽大忽小不只是烦人：EBU R128 响度标准与批量校验

-23 LUFS 比 -14 LUFS 小 9 dB（听起来明显更小）

数字信号：采样点的值（比如 -0.5 dB）
模拟还原后（DAC）：采样点之间可能有更高的尖峰（插值过冲）

ffmpeg -i input.mp4 -af "loudnorm=I=-16:TP=-1.5:LRA=11" -c:v copy output.mp4

ffmpeg -i input.mp4 \
  -af "loudnorm=I=-16:TP=-1.5:LRA=11:print_format=json" \
  -f null - 2>&1 | tail -20

{
    "input_i" : "-27.34",
    "input_tp" : "-6.10",
    "input_lra" : "8.20",
    "input_thresh" : "-38.19",
    "output_i" : "-16.01",
    "output_tp" : "-1.50",
    "output_lra" : "7.60",
    "output_thresh" : "-26.98",
    "normalization_type" : "dynamic",
    "target_offset" : "0.01"
}

ffmpeg -i input.mp4 \
  -af "loudnorm=I=-16:TP=-1.5:LRA=11:measured_I=-27.34:measured_TP=-6.10:measured_LRA=8.20:measured_thresh=-38.19:offset=0.01:linear=true:print_format=summary" \
  -c:v copy -c:a aac -b:a 192k output.mp4

import json
import re
import subprocess
import shlex


def measure(path, target_i=-16, tp=-1.5, lra=11):
    """第一遍：测量响度参数。"""
    af = f'loudnorm=I={target_i}:TP={tp}:LRA={lra}:print_format=json'
    cmd = ['ffmpeg', '-hide_banner', '-i', path, '-af', af, '-f', 'null', '-']
    p = subprocess.run(cmd, capture_output=True, text=True)
    # 从 stderr 末尾抓 JSON
    m = re.search(r'\{[^{}]*"input_i"[^{}]*\}', p.stderr, re.S)
    if not m:
        raise RuntimeError('测量失败：ffmpeg 输出里没找到 JSON')
    return json.loads(m.group(0))


def normalize(path, out, target_i=-16, tp=-1.5, lra=11):
    m = measure(path, target_i, tp, lra)
    af = (
        f'loudnorm=I={target_i}:TP={tp}:LRA={lra}'
        f':measured_I={m["input_i"]}'
        f':measured_TP={m["input_tp"]}'
        f':measured_LRA={m["input_lra"]}'
        f':measured_thresh={m["input_thresh"]}'
        f':offset={m["target_offset"]}'
        f':linear=true:print_format=summary'
    )
    cmd = ['ffmpeg', '-hide_banner', '-y', '-i', path,
           '-af', af, '-c:v', 'copy', '-c:a', 'aac', '-b:a', '192k', out]
    subprocess.run(cmd, check=True, capture_output=True)
    return m

import csv
import subprocess
import re
from pathlib import Path


def ebur128_measure(path):
    """用 ebur128 测量综合响度、真峰值、LRA。"""
    cmd = ['ffmpeg', '-hide_banner', '-nostats', '-i', str(path),
           '-af', 'ebur128=peak=true:framelog=quiet', '-f', 'null', '-']
    p = subprocess.run(cmd, capture_output=True, text=True)
    err = p.stderr

    def grab(pattern, cast=float):
        m = re.search(pattern, err)
        return cast(m.group(1)) if m else None

    return {
        'integrated': grab(r'I:\s*(-?[\d.]+)\s*LUFS'),
        'true_peak': grab(r'Peak:\s*(-?[\d.]+)\s*dBFS'),
        'lra': grab(r'LRA:\s*(-?[\d.]+)\s*LU'),
    }


def batch_report(files, target_i=-16, tol=1.0, tp_limit=-1.0):
    rows = []
    for f in files:
        m = ebur128_measure(f)
        # 判定
        need_fix = False
        reasons = []
        if m['integrated'] is None:
            reasons.append('测量失败')
            need_fix = True
        else:
            if abs(m['integrated'] - target_i) > tol:
                reasons.append(f"响度 {m['integrated']:.1f} != 目标 {target_i}")
                need_fix = True
            if m['true_peak'] is not None and m['true_peak'] > tp_limit:
                reasons.append(f"真峰值 {m['true_peak']:.1f} > {tp_limit}")
                need_fix = True
        rows.append({'file': str(f), **m, 'need_fix': need_fix,
                     'reason': '; '.join(reasons)})
    return rows


if __name__ == '__main__':
    files = sorted(Path('videos').glob('*.mp4'))
    rows = batch_report(files)
    with open('loudness_report.csv', 'w', newline='', encoding='utf-8') as f:
        w = csv.DictWriter(f, fieldnames=['file', 'integrated', 'true_peak',
                                          'lra', 'need_fix', 'reason'])
        w.writeheader()
        w.writerows(rows)
    bad = [r for r in rows if r['need_fix']]
    print(f'共 {len(rows)} 个文件，需要处理 {len(bad)} 个')

母版（保留原始动态，响度 -23 左右或者不做处理）
   ↓
按平台归一化（各自的目标值）
   ↓
分发

# 只换音轨，视频流直接复制
ffmpeg -i master.mp4 -i normalized_audio.m4a \
  -map 0:v -map 1:a -c:v copy -c:a copy out_youtube.mp4