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• Fallback input for ffmpeg

  22 septembre 2018, par Daniel Cantarin

  I’m doing some transcoding from a third-party remote input stream that I do not control.

  This input stream has errors from time to time, that I would like to mitigate before sending the stream to my transcoding pipeline, avoiding this way some possible problems in the output.

  I have several ideas regarding different problems. But the most basic scenario I would like to set up is as follows : when the stream is down, or it somehow loses some frames, I want to fill that video gap with a secondary input (like a blank screen, for example).

  For this simple task, I would like to use ffmpeg. I know it can mix, let’s say, an input stream with a fullscreen black square static image. However, I have to deal with this other condition : ffmpeg would run in the same infraestructure for the actual transcoding pipeline. That infraestructure must use its computing power for rendering the output. So, whatever ffmpeg command I end up using should use the minimum possible computing power.

  My actual problem : if I use -vcodec copy, in order to use minimum CPU, I can’t alter the original stream. But if I alter the original stream (by mixing it with some other stream), the operation uses CPU.

  My question : Is there a way to use -vcodec copy, but with a fallback input (instead of a mixed one) for when there are video gaps in the primary stream ?

  Thanks in advance.

• lavfi/vf_libvmaf : add warning when color ranges differ

  1er avril 2023, par Chema Gonzalez

  lavfi/vf_libvmaf : add warning when color ranges differ
  The VMAF filter uses the pixel values without considering
  
  the color ranges. This is incorrect. Patch adds a warning
  
  so at least the user knows it.
  Let's see an example.
  (1) Let's get FR and LR versions of the same image.
  ```
  
  $ ffmpeg -y -i /tmp/lena.490x490.ppm -vf scale="out_range=full" -pix_fmt yuv420p /tmp/lena.full.y4m
  
  $ xxd /tmp/lena.full.y4m |head
  
  00000000 : 5955 5634 4d50 4547 3220 5734 3930 2048  YUV4MPEG2 W490 H
  
  00000010 : 3439 3020 4632 353a 3120 4970 2041 303a  490 F25:1 Ip A0 :
  
  00000020 : 3020 4334 3230 6a70 6567 2058 5953 4353  0 C420jpeg XYSCS
  
  00000030 : 533d 3432 304a 5045 4720 5843 4f4c 4f52  S=420JPEG XCOLOR
  
  00000040 : 5241 4e47 453d 4655 4c4c 0a46 5241 4d45  RANGE=FULL.FRAME
  
  00000050 : 0a72 7271 7070 706f 6f6e 6d6d 6c6d 6d6d  .rrqpppoonmmlmmm
  
  00000060 : 6c6e 6e6d 6d6e 6e6e 6d6c 6d6d 6d6d 6d6d  lnnmmnnnmlmmmmmm
  
  00000070 : 6d6e 6d6b 6c6d 6e6e 6d6c 6d6d 6e6e 6f6f  mnmklmnnmlmmnnoo
  
  00000080 : 6f6f 6e6e 6e6e 6f70 7172 7375 7676 7370  oonnnnopqrsuvvsp
  
  00000090 : 6d69 6662 5e59 534d 4845 3d35 302e 2d2c  mifb^YSMHE=50.-,
  
  ```
  ```
  
  $ ffmpeg -y -i /tmp/lena.490x490.ppm -vf scale="out_range=limited" -pix_fmt yuv420p /tmp/lena.limited.y4m
  
  $ xxd /tmp/lena.limited.y4m | head
  
  00000000 : 5955 5634 4d50 4547 3220 5734 3930 2048  YUV4MPEG2 W490 H
  
  00000010 : 3439 3020 4632 353a 3120 4970 2041 303a  490 F25:1 Ip A0 :
  
  00000020 : 3020 4334 3230 6a70 6567 2058 5953 4353  0 C420jpeg XYSCS
  
  00000030 : 533d 3432 304a 5045 4720 5843 4f4c 4f52  S=420JPEG XCOLOR
  
  00000040 : 5241 4e47 453d 4c49 4d49 5445 440a 4652  RANGE=LIMITED.FR
  
  00000050 : 414d 450a 7272 7170 7070 6f6f 6e6e 6e6d  AME.rrqpppoonnnm
  
  00000060 : 6e6e 6e6d 6f6e 6e6e 6e6e 6e6e 6d6e 6e6e  nnnmonnnnnnnmnnn
  
  00000070 : 6e6e 6e6e 6f6e 6c6d 6e6f 6e6e 6d6e 6e6f  nnnnonlmnonnmnno
  
  00000080 : 6f6f 6f6f 6f6f 6f6f 6f6f 7071 7273 7576  oooooooooopqrsuv
  
  00000090 : 7673 706e 6a68 6461 5c57 524e 4b44 3d39  vspnjhda\WRNKD=9
  
  ```
  Note that the 2x images are the same. Only difference is the range,
  
  and the precision issues related to range conversion.
  (2) Let's calculate the VMAF score :
  
  ```
  
  $ ./ffmpeg -filter_threads 1 -filter_complex_threads 1 -i /tmp/lena.full.y4m -i /tmp/lena.limited.y4m -lavfi libvmaf="model=path=/usr/share/model/vmaf_v0.6.1neg.json" -report -f null -
  
  ...
  
  [Parsed_libvmaf_0 @ 0x3cc9b40] VMAF score : 85.530109
  
  ```
  As we are comparing an image with itself, we expect the score to
  
  be close to 100. Issue here is that the VMAF filter just uses the
  
  pixel values, ignoring the color ranges.
  Proposed solution is to add a warning.
  
  ```
  
  $ ./ffmpeg -filter_threads 1 -filter_complex_threads 1 -i /tmp/lena.full.y4m -i /tmp/lena.limited.y4m -lavfi libvmaf="model=path=/us
  
  r/share/model/vmaf_v0.6.1neg.json" -report -f null -
  
  ...
  
  [Parsed_libvmaf_0 @ 0x3cc9b40] distorted and reference frames use different color ranges (pc != tv)
  
  ...
  
  [Parsed_libvmaf_0 @ 0x3cc9b40] VMAF score : 85.530109
  
  ```
  Tested :
  Ran fate.
  
  ```
  
  $ make fate -j
  
  ...
  
  TEST    seek-lavf-ppmpipe
  
  TEST    seek-lavf-pgmpipe
  
  TEST    seek-lavf-mxf_opatom
  
  ```
  

  • [DH] libavfilter/vf_libvmaf.c

• Cannot resolve method 'encodeImage' in SequenceEncoder

  20 décembre 2022, par Santhosh Reddy

  File file = new File(dir, "video.mp4");
        SequenceEncoder encoder = new SequenceEncoder(file);


  


  im getting this error :'SequenceEncoder(org.jcodec.common.io.SeekableByteChannel, org.jcodec.common.model.Rational, org.jcodec.common.Format, org.jcodec.common.Codec, org.jcodec.common.Codec)' in 'org.jcodec.api.SequenceEncoder' cannot be applied to '(java.io.File)'

  


  encoder.encodeImage(frame);


  


  for this getting error:Cannot resolve method 'encodeImage' in 'SequenceEncoder'
could you please help us