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• Rails Thumbnails for videos being uploaded to S3

  20 octobre 2015, par Dani

  I have a rails application where I need to upload videos to an amazon s3 bucket alongwith their thumbnails. I am using ffmpeg to generate thumbnails and I am using carrierwave to handle video uploads. Here is my video uploader class

   class VideoUploader < CarrierWave::Uploader::Base
  
    include CarrierWave::Video
  
    storage :fog
  
    def store_dir
  
       "uploads/#{model.class.to_s.underscore}/#{mounted_as}/#{model.id}"
  
    end
  
    def extension_white_list
  
      %w(mp4 flv)
  
    end
  
  end

  The video uploads fine and the column for video url is set in videos table but I want to generate thumbnail and upload it as well. I know I have to use ffmpeg here but don’t exactly know how to do it.

  Any help will be appreciated.

• Révision 24353 : Ajout d’un point d’entree dans la declaration des objets pour fournir un routeur ...

  29 juillet 2019, par cerdic -

  ’modeles’ doit lister les modeles qui passeront dans le routeur pour l’objet concerne
  ’modeles_styliser’ doit designer le nom de la fonction a appeler, qui recevra le nom initial du modele demande et l’id de l’objet que l’on veut afficher avec ce modele
  Le routeur est appele depuis inclure_modele() qui est utilise dans le traitement des raccourcis modeles dans le texte, et une seconde fois dans styliser pour les inclusions venant des squelettes via #INCLURE ou #MODELE

• FFmpeg dnn_processing with tensorflow backend : difficulties applying a filter on an image

  9 avril 2023, par ArnoBen

  I am trying to perform a video segmentation for background blurring similar to Google Meet or Zoom using FFmpeg, and I'm not very familiar with it.

  


  Google's MediaPipe model is available as a tensorflow .pb file here (using download_hhxwww.sh).

  


  I can load it in python and it works as expected, though I do need to format the input frames : scaling to the model input dimension, adding a batch dimension, dividing the pixel values by 255 to have a range 0-1.

  


  FFmpeg has a filter that can use tensorflow models thanks to dnn_processing, but I'm wondering about these preprocessing steps. I tried to read the dnn_backend_tf.c file in ffmpeg's github repo, but C is not my forte. I'm guessing it adds a batch dimension somewhere otherwise the model wouldn't run, but I'm not sure about the rest.

  


  Here is my current command :

  


  ffmpeg \
    -i $FILE -filter_complex \
    "[0:v]scale=160:96,format=rgb24,dnn_processing=dnn_backend=tensorflow:model=$MODEL:input=input_1:output=segment[masks];[masks]extractplanes=2[mask]" \
    -map "[mask]" output.png


  


  

  • I'm already applying a scaling to match the input dimension.

  


  • I wrote this [masks]extractplanes=2[mask] because the model outputs a HxWx2 tensor (background mask and foreground mask) and I want to keep the foreground mask.

  


  


  The result I get with this command is the following (input-output) :

  


  

  


  I'm not sure how to interpret the problems in this output. In python I can easily get a nice grayscale output :

  


  

  


  I'm trying to obtain something similar with FFmpeg.

  


  Any suggestion or insights to obtain a correct output with FFmpeg would be greatly appreciated.

  


  PS : If I try to apply this on a video file, it hits a Segmentation Fault somewhere before getting any output so I stick with testing on an image for now.