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• How to upload object to a bucket in Google Cloud Platform from Python script

  7 juillet 2016, par Bryan

  The goal of this script is to extract audio from a video file using ffmpeg and upload it into a bucket on Google Cloud Platform each time it is called. Eventually I will have to extract audio from a large list of videos, so ideally I would want my script to extract and subsequently upload it into the cloud.

  My confusion is how to use GCP API to upload my object into a bucket. Any advice would be greatly appreciated !

  Link for reference : https://cloud.google.com/storage/docs/json_api/v1/json-api-python-samples#setup-code

  import subprocess
  
  import sys
  
  import re 
  
  
  
  fullVideo = sys.argv[1]
  
  title = re.findall('^([^.]*).*', fullVideo)
  
  title = str(title[0])
  
  subprocess.call('ffmpeg -i ' + fullVideo + ' -vn -ab 128k ' + title + '.flac', shell = True)
  
  
  
  def upload_object(bucket, filename, readers, owners):
  
      service = create_service()
  
  
  
      # This is the request body as specified:
  
      # http://g.co/cloud/storage/docs/json_api/v1/objects/insert#request
  
      body = {
  
          'name': filename,
  
      }
  
  
  
      # If specified, create the access control objects and add them to the
  
      # request body
  
      if readers or owners:
  
          body['acl'] = []
  
  
  
      for r in readers:
  
          body['acl'].append({
  
              'entity': 'user-%s' % r,
  
              'role': 'READER',
  
              'email': r
  
          })
  
      for o in owners:
  
          body['acl'].append({
  
              'entity': 'user-%s' % o,
  
              'role': 'OWNER',
  
              'email': o
  
          })
  
  
  
      # Now insert them into the specified bucket as a media insertion.
  
      # http://g.co/dev/resources/api-libraries/documentation/storage/v1/python/latest/storage_v1.objects.html#insert
  
      with open(filename, 'rb') as f:
  
          req = service.objects().insert(
  
              bucket=bucket, body=body,
  
              # You can also just set media_body=filename, but # for the sake of
  
              # demonstration, pass in the more generic file handle, which could
  
              # very well be a StringIO or similar.
  
              media_body=http.MediaIoBaseUpload(f, 'application/octet-stream'))
  
          resp = req.execute()
  
  
  
      return resp

• Google AppEngine flex as a transcoder [closed]

  6 septembre 2021, par jACK

  Situation :

  


  

  • A Nodejs/Express application running on appengine flex.

  


  • Using FFmpeg to cut videos, and merge different types of videos. 1080p 30fps videos, merged video duration usually around 8 hours.

  


  • Need for a massive amout of processing power for those edits.

  


  • The express server needs to be reachable 24/7 & flex is incredibly expensive if run on a 24/7 basis.

  


  


  Goal :

  


  

  • To have a cost efficient ffmpeg transcoder on a private enviroment =>

  


  • Flex instance as a maximum spec, but as its idle reduce the price significantly.

  


  


  Or is this a situation where a redesign is imminent ? eg. Compute Engine

  


  Tried approach

  


  

  • B8 Standard instance => Since the payload is pretty big, its causing the B8 instance to crash.

  


  


  Thanks.

  


• How to transcode 50 H264 Streams with FFMPEG more efficient ?

  20 juin 2019, par Kevin

  i need to (Re-)Transcode 50 Live-Streams. These streams are in H264 with 720p to 1080p and bitrates up to 10M. I just want to reduce the quality and bitrate of the streams to up to 720p with max. 2M Bitrate.

  That’s what i’m doing right now :

  ffmpeg -re -i "http://domain.tld/path/file.ext" -vcodec libx264 -preset veryfast -vf scale=-2:720 -b:v 2M -maxrate 2M -bufsize 1M -acodec libfdk_aac -f flv "rtmp://127.0.0.1:1935/live/stream_xyz"

  My Server CPU (2 x Xeon E5-2630 v3) is already at 100% with just 12 streams. I will upgrade my server to 2 x Xeon Gold 5118 next month, but i don’t think, that this will give me that much more power.

  Can someone help me, to do this more efficient ?

  Would it be more efficient / cheaper to do this with GPUs ?

  Or any other ideas, to do that as efficient and cheap as possible ?

  Thanks