# Linux 校验版本与编码器支持
ffmpeg -version
ffmpeg -encoders | grep -E "libx264|libx265|libvpx-vp9|libaom-av1"

ffmpeg -hwaccels
# 常见输出：cuda、qsv、vaapi、videotoolbox

# 仅当宽高均大于 1280 时才缩放至 720p
-vf "scale='if(gt(iw,1280),1280,-1)':'if(gt(ih,720),720,-1)':flags=lanczos,fps=30"

ffmpeg -y -hwaccel auto -i input.zoom 
  -map 0:v:0 -map 0:a:0 
  -c:v libx264 -preset medium -crf 20 -profile:v high -level 4.1 
  -g 60 -keyint_min 60 -sc_threshold 0 
  -c:a aac -b:a 128k -ac 2 -ar 48000 
  -movflags +faststart 
  -metadata title="Team_Weekly_$(date +%Y%m%d)" 
  output_archive.mp4

ffmpeg -i input.mp4 -vf 
"hqdn3d=4:3:6:4.5,unsharp=5:5:0.8:5:5:0.4,eq=contrast=1.1:brightness=0.05:saturation=1.05" 
-c:v libx265 -preset slow -crf 22 -tag:v hvc1 
-c:a copy enhanced.mp4

ffmpeg -i input.mp4 
  -map 0:a:0 -af "afftdn=nr=12:nf=-25, loudnorm=I=-16:TP=-1.5:LRA=11" -c:a libopus -b:a 48k speech_track.opus 
  -map 0:a:1 -c:a copy original_track.aac 
  -map 0:v -c:v copy video_only.mp4

ffmpeg -i input.mp4 
  -filter_complex 
"[v:0]split=3[v1][v2][v3]; 
 [v1]scale=1920:1080[v1out]; 
 [v2]scale=1280:720[v2out]; 
 [v3]scale=640:360[v3out]" 
  -map "[v1out]" -c:v:0 libx264 -b:v:0 4500k -maxrate:v:0 4800k -bufsize:v:0 9000k 
  -map "[v2out]" -c:v:1 libx264 -b:v:1 2500k -maxrate:v:1 2800k -bufsize:v:1 5000k 
  -map "[v3out]" -c:v:2 libx264 -b:v:2 800k  -maxrate:v:2 900k  -bufsize:v:2 1800k 
  -map 0:a -c:a aac -b:a 128k -ac 2 
  -f hls -hls_time 6 -hls_playlist_type vod -master_pl_name master.m3u8 
  -hls_segment_filename "stream_%v/data%03d.ts" stream_%v.m3u8

# 伪代码：Python + Celery + Redis
@app.task(bind=True, max_retries=3)
def transcode_meeting(self, src_path, meeting_id):
    dst_dir = f"/storage/processed/{meeting_id}"
    os.makedirs(dst_dir, exist_ok=True)
    
    # 1. 标准化归档
    run_ffmpeg(f"-i {src_path} ... {dst_dir}/archive.mp4")
    # 2. 生成预览码流
    run_ffmpeg(f"-i {dst_dir}/archive.mp4 ... HLS输出")
    # 3. 提取音频供 ASR
    run_ffmpeg(f"-i {src_path} -vn -ac 1 -ar 16000 {dst_dir}/asr.wav")
    # 4. 回写元数据至 CMDB
    update_cmdb(meeting_id, status="ready", assets=[...])

ffmpeg -i input.mp4 -vf "libvmaf=model_path=/usr/share/model/vmaf_v0.6.1.pkl:log_fmt=json:log_path=/var/log/vmaf_${MEETING_ID}.json" -f null -

-vf "zscale=t=linear:npl=100,format=gbrpf32le,zscale=p=bt709,tonemap=hable:desat=0,zscale=t=bt709:m=bt709:r=tv,format=yuv420p"

# 1. 导出模型为 ONNX (动态批次、动态分辨率)
# 2. FFmpeg 调用
ffmpeg -i lowres.mp4 -vf "dnn=model=realesrgan_x2.onnx:inputs=input:outputs=output:backend=auto" -c:v libx265 -crf 22 enhanced.mp4

# 1. 先转标准容器修复时间戳
ffmpeg -err_detect ignore_err -i "double_click_to_convert.zoom" -c copy -fflags +genpts fixed.mkv

# 2. 若需分离共享屏与摄像头（需厂商 SDK 或裁剪坐标）
# 假设共享屏占左 2/3，摄像头占右 1/3
ffmpeg -i fixed.mkv -filter_complex 
"[0:v]crop=iw*2/3:ih:0:0[share];[0:v]crop=iw/3:ih:iw*2/3:0[cam]" 
-map "[share]" -map 0:a -c:v libx264 share.mp4 
-map "[cam]"  -map 0:a -c:v libx264 cam.mp4

ffmpeg -i exported.mp4 
  -vsync cfr -filter:v "fps=25,settb=1/90000"   # 强制 CFR 25fps，重置时间基
  -c:v libx264 -preset fast -crf 21 -g 50 -keyint_min 50 -sc_threshold 0 
  -af "aresample=48000:resampler=soxr:precision=28,highpass=f=80,lowpass=f=12000"  # 音频重采样+带通
  -c:a aac -b:a 96k -ac 2 
  normalized.mp4

# .gitlab-ci.yml 片段
stages:
  - quality_gate

vmaf_regression:
  stage: quality_gate
  image: ffmpeg:vmaf-latest
  script:
    - mkdir -p results
    - for f in golden_set/*.yuv; do
        name=$(basename $f .yuv);
        # 使用当前候选参数转码
        ffmpeg -y -s 1920x1080 -pix_fmt yuv420p -i $f -c:v libx264 -crf $CANDIDATE_CRF -preset $CANDIDATE_PRESET /tmp/cand_$name.mp4;
        # 计算 VMAF
        ffmpeg -i /tmp/cand_$name.mp4 -i $f -lavfi libvmaf="model_path=/models/vmaf_v0.6.1.pkl:log_fmt=json:log_path=results/$name.json" -f null -;
      done
    - python scripts/check_vmaf_threshold.py results/ --threshold 93 --output report.html
  artifacts:
    reports:
      metric: report.html
    when: always

# Argo Workflow 简化示例
apiVersion: argoproj.io/v1alpha1
kind: Workflow
metadata:
  generateName: meeting-transcode-
spec:
  entrypoint: main
  templates:
  - name: main
    dag:
      tasks:
      - name: normalize
        template: ffmpeg-task
        arguments:
          parameters: [{name: args, value: "-i {{inputs.parameters.src}} -vf fps=25 -c:v libx264 -crf 21 /work/normalized.mp4"}]
      - name: super-res
        depends: "normalize"
        template: ffmpeg-gpu-task
        arguments:
          parameters: [{name: args, value: "-i /work/normalized.mp4 -vf dnn=model=realesrgan.onnx /work/sr.mp4"}]
      - name: hls-package
        depends: "super-res"
        template: ffmpeg-task
        arguments:
          parameters: [{name: args, value: "-i /work/sr.mp4 -c:v libx264 -b:v 3000k -f hls /work/hls/master.m3u8"}]

# 转码吞吐 (帧/秒)
rate(ffmpeg_frames_encoded_total[5m])

# 单位视频时长处理耗时 (秒/分钟视频)
histogram_quantile(0.95, rate(ffmpeg_transcode_duration_seconds_bucket[5m]))

# GPU 显存利用率
DCGM_FI_DEV_FB_USED / DCGM_FI_DEV_FB_TOTAL

# 队列积压 (待处理会议数)
kafka_consumergroup_lag{topic="meeting-recorded"}

# 1. Whisper.cpp 生成逐字级 SRT (含时间戳、置信度)
whisper-cli -m ggml-large-v3.bin -f audio.wav -osrt -owts -l zh

# 2. Python 后处理：合并短句、修正术语、生成 ASS 样式
#    关键：设置 an2 (底部居中)、fs24 (字号)、c&HFFFFFF& (白字)、3c&H000000& (黑边)、alpha&H80& (半透明底框)

# 3. FFmpeg 硬烧录 (归档版/分发版)
ffmpeg -i video.mp4 -vf "subtitles=meeting.ass:fontsdir=/usr/share/fonts:force_style='FontName=Source Han Sans CN'" -c:v libx264 -crf 20 burned.mp4

# 4. 软字幕挂载 (播放器端切换语言)
ffmpeg -i video.mp4 -i zh.srt -i en.srt -map 0 -map 1 -map 2 
  -c:v copy -c:s mov_text 
  -metadata:s:s:0 language=chi -metadata:s:s:1 language=eng 
  output_softsub.mp4

# Python 伪代码：上传网关校验
ALLOWED_MAGIC = {
    b'ftyp': ['mp4', 'mov', 'm4v'],
    b'x1aExdfxa3': ['mkv', 'webm'],
    b'RIFF': ['avi'],
    b'FLV': ['flv']
}
def validate_upload(file_stream):
    header = file_stream.read(16)
    if not any(header.startswith(m) for m in ALLOWED_MAGIC):
        raise ValueError("容器格式不在白名单")
    # ClamAV 扫描
    if not clamd_scan(file_stream):
        raise SecurityError("病毒特征匹配")
    # ffprobe 深度探测：流数量、编码器、时长、旋转元数据
    probe = ffprobe(file_stream)
    if probe.video_codec not in ['h264','hevc','vp9','av1']:
        raise ValueError("不支持的视频编码")

# 1. Widevine/PlayReady 加密 (需 Shaka Packager / Bento4)
mp4dash --widevine-header provider:widevine_test#content_id:74657374 --encryption-key 1234:abcdef... input.mp4 -o dash_out/

# 2. 动态水印 (用户 ID + 时间戳 + IP 后两段) - 仅在播放时由 CDN Edge 注入
#    方案：Cloudflare Workers / AWS Lambda@Edge 实时改写 .ts 分片元数据或叠加不可见水印 (DCT 域扩频)