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• Generating DASH manifest with ffmpeg works in Docker exec shell but not in os.exec golang

  22 février 2023, par Inquisitor

  I am trying to generate a DASH manifest with ffmpeg using this command

  


  /usr/bin/ffmpeg -f webm_dash_manifest -i ./480.webm -f webm_dash_manifest -i ./audio.webm -c copy -map 0:0 -map 1:0 -y -f webm_dash_manifest -adaptation_sets "id=0,streams=0 id=1,streams=1" ./manifest.mpd -loglevel repeat+level+verbose


  


  I run this in go, in a docker container as shown :

  


  func runFFmpeg(arguments []string) {
    arguments = append(arguments, "-loglevel", "repeat+level+verbose")
    cmd := exec.Command("ffmpeg", arguments...)

    fmt.Printf("cmd: %v\n", cmd)

    var out bytes.Buffer
    var stderr bytes.Buffer
    cmd.Stdout = &out
    cmd.Stderr = &stderr
    err := cmd.Run()

    if err != nil {
        log.Println(err)
        log.Println(stderr.String())
    }
}
runFFmpeg([]string{"-f", "webm_dash_manifest", "-i", "./480.webm", "-f", "webm_dash_manifest", "-i", "./audio.webm", "-c", "copy", "-map", "0:0", "-map", "1:0", "-y", "-f", "webm_dash_manifest", "-adaptation_sets", "\"id=0,streams=0 id=1,streams=1\"", "./manifest.mpd"})


  


  But I get this output :

  


   cmd: /usr/bin/ffmpeg -f webm_dash_manifest -i ./480.webm -f webm_dash_manifest -i ./audio.webm -c copy -map 0:0 -map 1:0 -y -copy_unknown -f webm_dash_manifest -adaptation_sets "id=0,streams=0 id=1,streams=1" ./manifest.mpd -loglevel repeat+level+verbose
 2023/02/22 04:45:17 exit status 1
 2023/02/22 04:45:17 [info] ffmpeg version 5.1.2 Copyright (c) 2000-2022 the FFmpeg developers
 [info]   built with gcc 12.2.1 (Alpine 12.2.1_git20220924-r3) 20220924
 [info]   configuration: --prefix=/usr --enable-avfilter --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-gnutls --enable-gpl --enable-libass --enable-libmp3lame --enable-libpulse --enable-libvorbis --enable-libvpx --enable-libxvid --enable-libx264 --enable-libx265 --enable-libtheora --enable-libv4l2 --enable-libdav1d --enable-lto --enable-postproc --enable-pic --enable-pthreads --enable-shared --enable-libxcb --enable-librist --enable-libsrt --enable-libssh --enable-libvidstab --disable-stripping --disable-static --disable-librtmp --disable-lzma --enable-libaom --enable-libopus --enable-libsoxr --enable-libwebp --enable-vaapi --enable-vdpau --enable-vulkan --enable-libdrm --enable-libzmq --optflags=-O2 --disable-debug --enable-libsvtav1
 [info]   libavutil      57. 28.100 / 57. 28.100
 [info]   libavcodec     59. 37.100 / 59. 37.100
 [info]   libavformat    59. 27.100 / 59. 27.100
 [info]   libavdevice    59.  7.100 / 59.  7.100
 [info]   libavfilter     8. 44.100 /  8. 44.100
 [info]   libswscale      6.  7.100 /  6.  7.100
 [info]   libswresample   4.  7.100 /  4.  7.100
 [info]   libpostproc    56.  6.100 / 56.  6.100
 [webm_dash_manifest @ 0x7fcec2836100] [warning] Could not find codec parameters for stream 0 (Video: vp9, 1 reference frame, none(tv, progressive, left), 640x480): unspecified pixel format
 Consider increasing the value for the 'analyzeduration' (0) and 'probesize' (5000000) options
 [info] Input #0, webm_dash_manifest, from './480.webm':
 [info]   Metadata:
 [info]     title           : Big Buck Bunny, Sunflower version
 [info]     GENRE           : Animation
 [info]     MAJOR_BRAND     : isom
 [info]     MINOR_VERSION   : 1
 [info]     COMPATIBLE_BRANDS: isomavc1
 [info]     COMPOSER        : Sacha Goedegebure
 [info]     ARTIST          : Blender Foundation 2008, Janus Bager Kristensen 2013
 [info]     COMMENT         : Creative Commons Attribution 3.0 - http://bbb3d.renderfarming.net
 [info]     ENCODER         : Lavf59.27.100
 [info]   Duration: 00:10:34.60, bitrate: 352 kb/s
 [info]   Stream #0:0: Video: vp9, 1 reference frame, none(tv, progressive, left), 640x480, SAR 853:640 DAR 853:480, 30 fps, 30 tbr, 1k tbn (default)
 [info]     Metadata:
 [info]       HANDLER_NAME    : GPAC ISO Video Handler
 [info]       VENDOR_ID       : [0][0][0][0]
 [info]       ENCODER         : Lavc59.37.100 libvpx-vp9
 [info]       DURATION        : 00:10:34.600000000
 [info]       webm_dash_manifest_duration: 634600
 [info]       webm_dash_manifest_initialization_range: 889
 [info]       webm_dash_manifest_file_name: 480.webm
 [info]       webm_dash_manifest_track_number: 1
 [info]       webm_dash_manifest_cues_start: 27924928
 [info]       webm_dash_manifest_cues_end: 27927508
 [info]       webm_dash_manifest_bandwidth: 738287
 [info]       webm_dash_manifest_cluster_keyframe: 1
 [info]       webm_dash_manifest_cue_timestamps: 67,5067,10067,15067,20067,25067,30067,35067,40067,45067,50067,55067,60067,65067,70067,75067,80067,85067,90067,95067,100067,105067,110067,115067,120067,125067,130067,135067,140067,145067,150067,155067,160067,165067,170067,175067,180067,185067,190067,195067
 [info] Input #1, webm_dash_manifest, from './audio.webm':
 [info]   Metadata:
 [info]     title           : Big Buck Bunny, Sunflower version
 [info]     GENRE           : Animation
 [info]     MAJOR_BRAND     : isom
 [info]     MINOR_VERSION   : 1
 [info]     COMPATIBLE_BRANDS: isomavc1
 [info]     COMPOSER        : Sacha Goedegebure
 [info]     ARTIST          : Blender Foundation 2008, Janus Bager Kristensen 2013
 [info]     COMMENT         : Creative Commons Attribution 3.0 - http://bbb3d.renderfarming.net
 [info]     ENCODER         : Lavf59.27.100
 [info]   Duration: 00:05:35.91, bitrate: 120 kb/s
 [info]   Stream #1:0: Audio: vorbis, 48000 Hz, 5.1, fltp (default)
 [info]     Metadata:
 [info]       HANDLER_NAME    : GPAC ISO Audio Handler
 [info]       VENDOR_ID       : [0][0][0][0]
 [info]       ENCODER         : Lavc59.37.100 libvorbis
 [info]       DURATION        : 00:05:35.907000000
 [info]       webm_dash_manifest_duration: 335907
 [info]       webm_dash_manifest_initialization_range: 7411
 [info]       webm_dash_manifest_file_name: audio.webm
 [info]       webm_dash_manifest_track_number: 1
 [info]       webm_dash_manifest_cues_start: 5047497
 [info]       webm_dash_manifest_cues_end: 5048846
 [info]       webm_dash_manifest_bandwidth: 126994
 [info]       webm_dash_manifest_cluster_keyframe: 1
 [info]       webm_dash_manifest_cue_timestamps: 0,4986,9980,14962,19959,24956,29946,34930,39916,44911,49908,54892,59874,64868,69858,74858,79855,84847,89834,94834,99826,104826,109826,114818,119812,124799,129780,134770,139756,144743,149727,154719,159714,164706,169698,174687,179668,184667,189658,194650,19
 HERE'S THE ERROR --> [error] Could not write header for output file #0 (incorrect codec parameters ?): Operation not permitted
 [error] Error initializing output stream 0:1 -- 
 [info] Stream mapping:
 [info]   Stream #0:0 -> #0:0 (copy)
 [info]   Stream #1:0 -> #0:1 (copy)
 [error] 
 [AVIOContext @ 0x7fcebe23a840] [verbose] Statistics: 0 bytes written, 0 seeks, 0 writeouts
 [AVIOContext @ 0x7fcebe23a980] [verbose] Statistics: 5940786 bytes read, 133 seeks
 [AVIOContext @ 0x7fcebe23acc0] [verbose] Statistics: 2260628 bytes read, 72 seeks


  


  It works perfectly however if I run it within docker exec (exec into the container and run the command in bash). Also, note in the last output that the command is well formed when I print it out from go. File permissions are also not the problem since the command to create the video variants works with os.exec i.e

  


  runFFmpeg([]string{"-i", originalFilePath, "-c:v", "libvpx-vp9", "-keyint_min", "150", "-g", "150", "-tile-columns", "4", "-frame-parallel", "1", "-f", "webm", "-dash", "1", "-an", "-vf", fmt.Sprintf("scale=%s:%s", width, height), "-b:v", bitRate, "-dash", "1", "-y", destinationFilePath})


  


• ffmpeg is failing to load shared libraries after a ./configure with a prefix inside a conda environment

  30 janvier 2024, par user3133806

  I am using conda and building ffmpeg from source within that environment.

  


  I ran the following commands :

  


  conda create --name my_conda_env
conda activate my_conda_env
# Now I am in the conda environment
# $CONDA_PREFIX is /home/myuser/.conda/envs/my_conda_env/bin/ffmpeg

# Checkout ffmpeg code
# git checkout ...

./configure --prefix=$CONDA_PREFIX --enable-shared --disable-static && make distclean && make -j 100 && make install

# The above command does install the newly built ffmpeg into:
# /home/myuser/.conda/envs/my_conda_env/bin/ffmpeg

# However it fails to execute:
ffmpeg
ffmpeg: error while loading shared libraries: libavdevice.so.58: cannot open shared object file: No such file or directory

# When I add the conda lib path to LD_LIBRARY_PATH it works:
LD_LIBRARY_PATH=$CONDA_PREFIX/lib:$LD_LIBRARY_PATH ffmpeg
ffmpeg version n4.2.9-4-gd7beb0c61f Copyright (c) 2000-2023 the FFmpeg developers

# I thought ./configure with a --prefix will build a binary that will search for libraries relative to itself, but that does not appear to be the case:

strace -o /tmp/strace.out ffmpeg
tail /tmp/strace.out

openat(AT_FDCWD, "/usr/lib64/haswell/x86_64/libavdevice.so.58", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
newfstatat(AT_FDCWD, "/usr/lib64/haswell/x86_64", 0x7fff65f56d90, 0) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "/usr/lib64/haswell/libavdevice.so.58", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
newfstatat(AT_FDCWD, "/usr/lib64/haswell", 0x7fff65f56d90, 0) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "/usr/lib64/avx512_1/x86_64/libavdevice.so.58", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
newfstatat(AT_FDCWD, "/usr/lib64/avx512_1/x86_64", 0x7fff65f56d90, 0) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "/usr/lib64/avx512_1/libavdevice.so.58", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
newfstatat(AT_FDCWD, "/usr/lib64/avx512_1", 0x7fff65f56d90, 0) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "/usr/lib64/x86_64/libavdevice.so.58", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
newfstatat(AT_FDCWD, "/usr/lib64/x86_64", 0x7fff65f56d90, 0) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "/usr/lib64/libavdevice.so.58", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
newfstatat(AT_FDCWD, "/usr/lib64", {st_mode=S_IFDIR|0555, st_size=49526, ...}, 0) = 0
writev(2, [{iov_base="ffmpeg", iov_len=6}, {iov_base=": ", iov_len=2}, {iov_base="error while loading shared libra"..., iov_len=36}, {i
ov_base=": ", iov_len=2}, {iov_base="libavdevice.so.58", iov_len=17}, {iov_base=": ", iov_len=2}, {iov_base="cannot open shared object file", iov_len=30}, {iov_base=": ", iov_len=2}, {iov_base="No such file or directory", iov_len=25}, {iov_base="\n", iov_len=1}], 10) = 
123


  


  Conda documentation says not to use LD_LIBRARY_PATH here :

  


  https://docs.conda.io/projects/conda-build/en/stable/resources/use-shared-libraries.html#shared-libraries-in-macos-and-linux

  


  How can I build ffmpeg from source in a conda environment and have the binary find the .so file relative to itself ?

  


• Ffmpeg HLS conversion error on AWS Lambda - ffmpeg was killed with signal SIGSEGV

  20 octobre 2023, par RtiM0

  I'm trying to convert video files into HLS streams on a AWS Lambda. The ffmpeg configuration I have setup works for normal (Non HLS) transcoding, but in case of HLS it throws the following error :

  


  stderr:
frame=  341 fps= 84 q=34.0 q=32.0 q=28.0 size=N/A time=00:00:12.52 bitrate=N/A speed= 3.1x    
frame=  385 fps= 85 q=34.0 q=31.0 q=27.0 size=N/A time=00:00:13.97 bitrate=N/A speed=3.08x    
frame=  433 fps= 86 q=33.0 q=30.0 q=27.0 size=N/A time=00:00:15.55 bitrate=N/A speed=3.08x    
[hls @ 0x702c480] Cannot use rename on non file protocol, this may lead to races and temporary partial files
[hls @ 0x702c480] Opening '/tmp/stream_0.m3u8' for writing
[hls @ 0x702c480] Opening '/tmp/stream_1.m3u8' for writing
[hls @ 0x702c480] Opening '/tmp/stream_2.m3u8' for writing
[hls @ 0x702c480] Opening '/tmp/master.m3u8' for writing
ffmpeg was killed with signal SIGSEGV


  


  And I error thrown by fluent-ffmpeg is this :

  


  2023-03-06T10:21:44.555Z    15a0a43b-5e24-42ac-ae72-fe04f0c72a3e    ERROR   Invoke Error    &#xA;{&#xA;    "errorType": "Error",&#xA;    "errorMessage": "ffmpeg was killed with signal SIGSEGV",&#xA;    "stack": [&#xA;        "Error: ffmpeg was killed with signal SIGSEGV",&#xA;        "    at ChildProcess.<anonymous> (/var/task/node_modules/fluent-ffmpeg/lib/processor.js:180:22)",&#xA;        "    at ChildProcess.emit (node:events:513:28)",&#xA;        "    at ChildProcess._handle.onexit (node:internal/child_process:291:12)"&#xA;    ]&#xA;}&#xA;</anonymous>

  


  This is the code I run on AWS Lambda to convert video files into HLS :

  


  export const compressToHLS = (sourcePath, outputFolder) =>
  new Promise((resolve, reject) => {
    Ffmpeg(sourcePath)
      .complexFilter([
        {
          filter: "split",
          options: "3",
          inputs: "v:0",
          outputs: ["v1", "v2", "v3"],
        },
        {
          filter: "scale",
          options: {
            w: 1280,
            h: 720,
          },
          inputs: "v1",
          outputs: "v1out",
        },
        {
          filter: "scale",
          options: {
            w: 960,
            h: 540,
          },
          inputs: "v2",
          outputs: "v2out",
        },
        {
          filter: "scale",
          options: {
            w: 640,
            h: 360,
          },
          inputs: "v3",
          outputs: "v3out",
        },
      ])
      .outputOptions([
        "-map [v1out]",
        "-c:v:0",
        "libx264",
        "-b:v 3000000",
        "-map [v2out]",
        "-c:v:1",
        "libx264",
        "-b:v 2000000",
        "-map [v3out]",
        "-c:v:2",
        "libx264",
        "-b:v 1000000",
      ])
      .outputOptions([
        "-map a:0",
        "-c:a:0 aac",
        "-b:a:0 96000",
        "-ar 48000",
        "-ac 2",
        "-map a:0",
        "-c:a:1 aac",
        "-b:a:1 96000",
        "-ar 48000",
        "-ac 2",
        "-map a:0",
        "-c:a:2 aac",
        "-b:a:2 96000",
        "-ar 48000",
        "-ac 2",
      ])
      .outputOptions([
        "-f hls",
        "-hls_time 10",
        "-hls_playlist_type vod",
        "-hls_flags independent_segments",
        "-hls_segment_type mpegts",
        `-hls_segment_filename ${outputFolder}/%v_%d.ts`,
        "-master_pl_name master.m3u8",
      ])
      .outputOption("-var_stream_map", "v:0,a:0 v:1,a:1 v:2,a:2")
      .outputOption("-preset veryfast")
      .output(`${outputFolder}/stream_%v.m3u8`)
      .on("start", (cmdline) => console.log(cmdline))
      .on("progress", (progress) => {
        let prog = Math.floor(progress.percent * 10) / 10;
        if (Math.round(prog) % 10 == 0) {
          console.log(`${prog}% complete`);
        }
      })
      .on("error", (err, stdout, stderr) => {
        if (err) {
          console.log(err.message);
          console.log("stdout:\n" + stdout);
          console.log("stderr:\n" + stderr);
          reject(err);
        }
      })
      .on("end", () => resolve())
      .run();
  });


  


  In this code the sourcePath is usually a presigned URL from S3 (But I have also tried to download a file on /tmp and setting sourcePath as the path to the downloaded file) and outputFolder is tmpdir() which is /tmp.

  


  I have the lambda settings configured to have 10GB of memory and 10GB of ephemeral storage (the maximum allowed).