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• How to "extend" aws docker base image (.net core from scratch) by ... libs/ubuntu/ffmpeg ?

  26 avril 2022, par Nigrimmist

  i would like to use AWS Lambda through the image containers using .net core 3.1 and it is works fine for me in simplest code case. But i stucked with next scenario :

  


  By default, aws provide base image with .net core with aws libs based on "from scratch". So as i know, it minimal Linux that does not contains even package manager.

  


  I need to work with ffmpeg in the code, but to do it i need to install few packages and ... fmpeg. I have working code on image

  


  FROM mcr.microsoft.com/dotnet/runtime:3.1-bionic


  


  It is ubuntu with .net core runtime. But what is the right strategic in case of AWS Lambda image ? How can i ... merge them ?.

  


  Have few ideas, but not sure :

  


  

  1. use as is FROM public.ecr.aws/lambda/dotnet:core3.1 and try to install package manager, all depenendencies to use ffmpeg and so on ?

  


  2. Use mcr.microsoft.com/dotnet/runtime:3.1-bionic, somehow add required by amazon dependencies (how ? download content and attach from local ?) and configure it to run in Lambda runtime ?

  


  3. ... ?

  


  


  Will be glad to hear where is the solution here. Thanks !

  


• swscale : aarch64 : Optimize the final summation in the hscale routine

  20 avril 2022, par Martin Storsjö

  swscale : aarch64 : Optimize the final summation in the hscale routine
  Before :                     Cortex A53      A72      A73  Graviton 2  Graviton 3
  
  hscale_8_to_15_width8_neon :     8273.0   4602.5   4289.5      2429.7      1629.1
  
  hscale_8_to_15_width16_neon :   12405.7   6803.0   6359.0      3549.0      2378.4
  
  hscale_8_to_15_width32_neon :   21258.7  11491.7  11469.2      5797.2      3919.6
  
  hscale_8_to_15_width40_neon :   25652.0  14173.7  12488.2      6893.5      4810.4
  After :
  
  hscale_8_to_15_width8_neon :     7633.0   3981.5   3350.2      1980.7      1261.1
  
  hscale_8_to_15_width16_neon :   11666.7   5951.0   5512.0      3080.7      2131.4
  
  hscale_8_to_15_width32_neon :   20900.7  10733.2   9481.7      5275.2      3862.1
  
  hscale_8_to_15_width40_neon :   24826.0  13536.2  11502.0      6397.2      4731.9
  Thus, this gives overall a 8-29% speedup for the smaller filter
  
  sizes, around 1-8% for the larger filter sizes.
  Inspired by a patch by Jonathan Swinney <jswinney@amazon.com>.
  Signed-off-by : Martin Storsjö <martin@martin.st>
  

  • [DH] libswscale/aarch64/hscale.S

• net core and video transcoding on aws lambda

  14 septembre 2022, par user1765862

  I'm looking for a solution to :

  


  

  1. upload video to s3 bucket

  


  2. after video upload an aws lambda function will be triggered

  


  3. lambda function will use ffmpeg layer in order to transcode video (mainly cropping with other functionalities)

  


  4. save result (transcoded video into s3 bucket)

  


  


  My language of choice inside lambda is c# and net core runtime.

  


  I have found various resources for video manipulation with aws ffmpeg layer using lambda function but no examples in net core lambda.

  


  My question is :

  


  


  Can I use existing FFmpeg/FFprobe Lambda Layer for Amazon Linux such
as this one with lambda function written in c# and .net core ?

  


  


  Another question :

  


  


  Would you suggest Amazon Elastic Transcoder as a better choice with
lambda function .net core integration ?