Sur d’autres sites (7621)

• ffmpeg copy stream preserving FPS

  10 mars 2017, par James Taylor

  I have a stream that I know is outputting at a certain frame rate (30 FPS). I want to use ffmpeg to make a copy of this stream and save it to disk.

  I have the following command :

  ffmpeg -i http://input/ -c copy -map 0 \
  
      -f segment -strftime 1 -segment_time 900 \
  
      -segment_atclocktime 1 -segment_format mp4 %Y-%m-%d_%H-%M-%S.mp4

  But when I run the command, I see the following :

  frame=   32 fps=3.9 q=-1.0 Lsize=N/A time=00:00:01.27 bitrate=N/A

  Where it appears the FPS is hovers around 4.0 FPS and time moves slower than real time.

  I tried added -re (copy the rate of the input stream) and -r 30 (manually set the rate to 30 FPS) flag specified before the input file, but it didn’t seem to work.

  I also read a similar question here using -framerate 30, but that option doesn’t exist in the man pages and is an Invalid option.

  Any help would be greatly appreciated !

  ---

  So I let the modified command (removing the flags -c copy -map 0) run for exactly 5 minutes. Running ffprobe yields :

  Input #0, mov,mp4,m4a,3gp,3g2,mj2, from '2017-03-10_01-09-12.mp4':
  
    Metadata:
  
      major_brand     : isom
  
      minor_version   : 512
  
      compatible_brands: isomiso2avc1mp41
  
      encoder         : Lavf57.2.100
  
    Duration: 00:00:15.43, start: 0.066016, bitrate: 13416 kb/s
  
      Stream #0:0(und): Video: h264 (High) (avc1 / 0x31637661), yuvj420p(pc), 1024x768, 13414 kb/s, 30 fps, 30 tbr, 15360 tbn, 60 tbc (default)
  
      Metadata:
  
        handler_name    : VideoHandler

  Again, this only produces 15 seconds of video and I can’t seem to get a 1:1 relationship between the input stream of 30 FPS and an output stream also in 30 FPS in real time. Playing the video yields something that’s sped up.

• FFMPEG to create an MPEG-DASH stream with VP8

  16 septembre 2019, par Kenny Worden

  I’m trying to use FFMPEG to stream a live video feed from my webcam /dev/video0. Following scattered tutorials and scarce documentation (is this a known problem for the encoding community ?) I arrived at the following bash script :

  #!/bin/bash
  
  
  
  ffmpeg \
  
      -y \
  
      -f v4l2 \
  
          -i /dev/video0 \
  
          -s 640x480 \
  
          -input_format mjpeg \
  
          -r 24 \
  
      -map 0:0 \
  
      -pix_fmt yuv420p \
  
      -codec:v libvpx \
  
          -s 640x480 \
  
          -threads 4 \
  
          -b:v 50k \
  
          -tile-columns 4 \
  
          -frame-parallel 1 \
  
          -keyint_min 24 -g 24 \
  
      -f webm_chunk \
  
          -header "stream.hdr" \
  
          -chunk_start_index 1 \
  
      stream_%d.chk &
  
  
  
  sleep 2
  
  
  
  ffmpeg \
  
      -f webm_dash_manifest -live 1 \
  
      -i stream.hdr \
  
      -c copy \
  
      -map 0 \
  
      -f webm_dash_manifest -live 1 \
  
          -adaptation_sets "id=0,streams=0" \
  
          -chunk_start_index 1 \
  
          -chunk_duration_ms 1000 \
  
          -time_shift_buffer_depth 30000 \
  
          -minimum_update_period 60000 \
  
      stream_manifest.mpd

  When I run this script, my webcam light turns on, the stream.hdr and stream_manifest.mpd files are written, and chunks start to be created (i.e. stream_1.chk, stream_2.chk, etc...). However, FFMPEG throws the following error :

  Could not write header for output file #0 (incorrect codec parameters
   ?) : Invalid data found when processing input

  I will explain what I think I am doing with this script, and hopefully this will expose any errors in my thinking.

  First, we invoke FFMPEG to use Video for Linux 2 (v4l2) to read from my webcam (/dev/video0) of a resolution 640x480. The input format is mjpeg with a framerate of 24fps.

  I then declare that FFMPEG should "map" (copy) the video stream output by v4l2 to a file. I specify the pixel format (YUV420P) and use libvpx (VP8 encoding) to encode the video stream. I set the size to be 640x480, use 4 threads, set the bitrate to be 50kbps, do some magic with tile-columns and frame-parallel options, and set the I-frames to be 24 frames apart.

  I then create a stream.hdr file. The starting index is 1. This command continues to run infinitely until I kill it, grabbing new video from my webcam and outputting it into chunks.

  I then sleep for 2 seconds to give the previous command time to generate a header file.

  And that’s really it. The next invocation of FFMPEG simply creates the MPEG-DASH manifest file given the header generated in the previous step.

  So what’s going on ? Why can I not view the video in a web browser (I’m using Dash.js) ? I serve the manifest, header, and chunks on a Node.js server so that trivial issue is not the problem.

  ---

  Edit : Here is my full console output.

  ffmpeg version 3.0.7-0ubuntu0.16.10.1 Copyright (c) 2000-2017 the FFmpeg developers
  
    built with gcc 6.2.0 (Ubuntu 6.2.0-5ubuntu12) 20161005
  
    configuration: --prefix=/usr --extra-version=0ubuntu0.16.10.1 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --cc=cc --cxx=g++ --enable-gpl --enable-shared --disable-stripping --disable-decoder=libopenjpeg --disable-decoder=libschroedinger --enable-avresample --enable-avisynth --enable-gnutls --enable-ladspa --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libmodplug --enable-libmp3lame --enable-libopenjpeg --enable-libopus --enable-libpulse --enable-librubberband --enable-librtmp --enable-libschroedinger --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvorbis --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx265 --enable-libxvid --enable-libzvbi --enable-openal --enable-opengl --enable-x11grab --enable-libdc1394 --enable-libiec61883 --enable-libzmq --enable-frei0r --enable-chromaprint --enable-libx264
  
    libavutil      55. 17.103 / 55. 17.103
  
    libavcodec     57. 24.102 / 57. 24.102
  
    libavformat    57. 25.100 / 57. 25.100
  
    libavdevice    57.  0.101 / 57.  0.101
  
    libavfilter     6. 31.100 /  6. 31.100
  
    libavresample   3.  0.  0 /  3.  0.  0
  
    libswscale      4.  0.100 /  4.  0.100
  
    libswresample   2.  0.101 /  2.  0.101
  
    libpostproc    54.  0.100 / 54.  0.100
  
  [video4linux2,v4l2 @ 0x55847e244ea0] The driver changed the time per frame from 1/24 to 1/30
  
  [mjpeg @ 0x55847e245c00] Changing bps to 8
  
  Input #0, video4linux2,v4l2, from '/dev/video0':
  
    Duration: N/A, start: 64305.102081, bitrate: N/A
  
      Stream #0:0: Video: mjpeg, yuvj422p(pc, bt470bg/unknown/unknown), 640x480, -5 kb/s, 30 fps, 30 tbr, 1000k tbn, 1000k tbc
  
  Codec AVOption frame-parallel (Enable frame parallel decodability features) specified for output file #0 (stream_%d.chk) has not been used for any stream. The most likely reason is either wrong type (e.g. a video option with no video streams) or that it is a private option of some encoder which was not actually used for any stream.
  
  Codec AVOption tile-columns (Number of tile columns to use, log2) specified for output file #0 (stream_%d.chk) has not been used for any stream. The most likely reason is either wrong type (e.g. a video option with no video streams) or that it is a private option of some encoder which was not actually used for any stream.
  
  [swscaler @ 0x55847e24b720] deprecated pixel format used, make sure you did set range correctly
  
  [libvpx @ 0x55847e248a20] v1.5.0
  
  Output #0, webm_chunk, to 'stream_%d.chk':
  
    Metadata:
  
      encoder         : Lavf57.25.100
  
      Stream #0:0: Video: vp8 (libvpx), yuv420p, 640x480, q=-1--1, 50 kb/s, 30 fps, 30 tbn, 30 tbc
  
      Metadata:
  
        encoder         : Lavc57.24.102 libvpx
  
      Side data:
  
        unknown side data type 10 (24 bytes)
  
  Stream mapping:
  
    Stream #0:0 -> #0:0 (mjpeg (native) -> vp8 (libvpx))
  
  Press [q] to stop, [?] for help
  
  frame=   21 fps=0.0 q=0.0 size=N/A time=00:00:00.70 bitrate=N/A dup=5 drop=frame=   36 fps= 35 q=0.0 size=N/A time=00:00:01.20 bitrate=N/A dup=5 drop=frame=   51 fps= 33 q=0.0 size=N/A time=00:00:01.70 bitrate=N/A dup=5 drop=ffmpeg version 3.0.7-0ubuntu0.16.10.1 Copyright (c) 2000-2017 the FFmpeg developers
  
    built with gcc 6.2.0 (Ubuntu 6.2.0-5ubuntu12) 20161005
  
    configuration: --prefix=/usr --extra-version=0ubuntu0.16.10.1 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --cc=cc --cxx=g++ --enable-gpl --enable-shared --disable-stripping --disable-decoder=libopenjpeg --disable-decoder=libschroedinger --enable-avresample --enable-avisynth --enable-gnutls --enable-ladspa --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libmodplug --enable-libmp3lame --enable-libopenjpeg --enable-libopus --enable-libpulse --enable-librubberband --enable-librtmp --enable-libschroedinger --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvorbis --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx265 --enable-libxvid --enable-libzvbi --enable-openal --enable-opengl --enable-x11grab --enable-libdc1394 --enable-libiec61883 --enable-libzmq --enable-frei0r --enable-chromaprint --enable-libx264
  
    libavutil      55. 17.103 / 55. 17.103
  
    libavcodec     57. 24.102 / 57. 24.102
  
    libavformat    57. 25.100 / 57. 25.100
  
    libavdevice    57.  0.101 / 57.  0.101
  
    libavfilter     6. 31.100 /  6. 31.100
  
    libavresample   3.  0.  0 /  3.  0.  0
  
    libswscale      4.  0.100 /  4.  0.100
  
    libswresample   2.  0.101 /  2.  0.101
  
    libpostproc    54.  0.100 / 54.  0.100
  
  Input #0, webm_dash_manifest, from 'stream.hdr':
  
    Metadata:
  
      encoder         : Lavf57.25.100
  
    Duration: N/A, bitrate: N/A
  
      Stream #0:0: Video: vp8, yuv420p, 640x480, SAR 1:1 DAR 4:3, 30 fps, 30 tbr, 1k tbn, 1k tbc (default)
  
      Metadata:
  
        webm_dash_manifest_file_name: stream.hdr
  
        webm_dash_manifest_track_number: 1
  
  Output #0, webm_dash_manifest, to 'stream_manifest.mpd':
  
    Metadata:
  
      encoder         : Lavf57.25.100
  
      Stream #0:0: Video: vp8, yuv420p, 640x480 [SAR 1:1 DAR 4:3], q=2-31, 30 fps, 30 tbr, 1k tbn, 1k tbc (default)
  
      Metadata:
  
        webm_dash_manifest_file_name: stream.hdr
  
        webm_dash_manifest_track_number: 1
  
  Stream mapping:
  
    Stream #0:0 -> #0:0 (copy)
  
  Could not write header for output file #0 (incorrect codec parameters ?): Invalid data found when processing input
  
  frame=   67 fps= 33 q=0.0 size
  
  frame=   82 fps= 32 q=0.0 size=N/A time=00:00:02.73 bitrate=N/A dup=5 drop=
  
  frame=   97 fps= 32 q=0.0 size=N/A time=00:00:03.23 bitrate=N/A dup=5 drop=
  
  frame=  112 fps= 32 q=0.0 size=N/A time=00:00:03.73 bitrate=N/A dup=5 ...

• What is Google Analytics data sampling and what’s so bad about it ?

  16 août 2019, par Joselyn Khor — Analytics Tips, Development
  What is Google Analytics data sampling, and what’s so bad about it ?

  Google (2019) explains what data sampling is :

  “In data analysis, sampling is the practice of analysing a subset of all data in order to uncover the meaningful information in the larger data set.”[1]

  This is basically saying instead of analysing all of the data, there’s a threshold on how much data is analysed and any data after that will be an assumption based on patterns.

  Google’s (2019) data sampling thresholds :

  Ad-hoc queries of your data are subject to the following general thresholds for sampling :
  [Google] Analytics Standard : 500k sessions at the property level for the date range you are using
  [Google] Analytics 360 : 100M sessions at the view level for the date range you are using (para. 3) [2]

  This threshold is limiting because your data in GA may become more inaccurate as the traffic to your website increases.

  Say you’re looking through all your traffic data from the last year and find you have 5 million page views. Only 500K of that 5 million is accurate ! The data for the remaining 4.5 million (90%) is an assumption based on the 500K sample size.

  This is a key weapon Google uses to sell to large businesses. In order to increase that threshold for more accurate reporting, upgrading to premium Google Analytics 360 for approximately US$150,000 per year seems to be the only choice.

  What’s so bad about data sampling ?

  It’s unfair to say sampled data is to be disregarded completely. There is a calculation ensuring it is representative and can allow you to get good enough insights. However, we don’t encourage it as we don’t just want “good enough” data. We want the actual facts.

  In a recent survey sent to Matomo customers, we found a large proportion of users switched from GA to Matomo due to the data sampling issue.

  The two reasons why data sampling isn’t preferable : 

  1. If the selected sample size is too small, you won’t get a good representative of all the data. 
  2. The bigger your website grows, the more inaccurate your reports will become.

  An example of why we don’t fully trust sampled data is, say you have an ecommerce store and see your GA revenue reports aren’t matching the actual sales data, due to data sampling. In GA you may be seeing revenue for the month as $1 million, instead of actual sales of $800K.

  The sampling here has caused an inaccuracy that could have negative financial implications. What you get in the GA report is an estimated dollar figure rather than the actual sales. Making decisions based on inaccurate data can be costly in this case. 

  Another disadvantage to sampled data is that you might be missing out on opportunities you would’ve noticed if you were given a view of the whole. E.g. not being able to see real patterns occurring due to the data already being predicted. 

  By not getting a chance to see things as they are and only being able to jump to the conclusions and assumptions made by GA is risky. The bigger your business grows, the less you can risk making business decisions based on assumptions that could be inaccurate. 

  If you feel you could be missing out on opportunities because your GA data is sampled data, get 100% accurately reported data. 

  The benefits of 100% accurate data

  Matomo doesn’t use data sampling on any of our products or plans. You get to see all of your data and not a sampled data set.

  Data quality is necessary for high impact decision-making. It’s hard to make strategic changes if you don’t have confidence that your data is reliable and accurate.

  Learn about how Matomo is a serious contender to Google Analytics 360. 

  Now you can import your Google Analytics data directly into your Matomo

  If you’re wanting to make the switch to Matomo but worried about losing all your historic Google Analytics data, you can now import this directly into your Matomo with the Google Analytics Importer tool.

  
  Take the challenge !

  Compare your Google Analytics data (sampled data) against your Matomo data, or if you don’t have Matomo data yet, sign up to our 30-day free trial and start tracking !

  References :

  [1 & 2] About data sampling. (2019). In Analytics Help About data sampling. Retrieved August 14, 2019, from https://support.google.com/analytics/answer/2637192