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• ffmpeg taking too much time to compress videos in a nest Js project [closed]

  30 août 2023, par Sheeraz

  I am trying to read a video as a stream from firebase and compress it using ffmpeg an it is too much time for the job to complete such that my call breaks before its done and I am getting socket hangup error. I have tried to increase the timeout of the call to 540s but it is still not enought for the job to be done. The framework I am using is nestJs with react as front-end. This is a web-app and the feature I am working on is a video recording functionality.

  


  Here is the code I am trying to run. The library I am using is "fluent-ffmpeg" : "^2.1.2", and
"ffmpeg" : "^0.0.4",

  


  const bucket = storage.bucket('my-bucket.appspot.com');
      const filePath = 'videos/video.mp4'; // Replace with the full path to your file
      const videoFile = bucket.file(filePath);
      const readStream = videoFile.createReadStream();
const ffmpegCommand = ffmpeg();
      ffmpegCommand.input(readStream);
      ffmpegCommand
        .outputOptions([
          '-preset ultrafast',
          '-c:v libx264',
          '-c:a aac',
          '-vf scale=640:480',
        ])
        .format('wav');
const outputStream = await ffmpegCommand.pipe();


  


• FileNotFoundError on aws Lambda when concatenating videos with ffmpeg

  2 juillet 2021, par Shibu Menon

  Goal :

  



  

  • Concat 2 videos (both are in an s3 bucket) via aws Lambda using ffmpeg

  


  • Upload the resultant output.mp4 to another S3 bucket

  


  • Python 3+

  


  



  I've already created a layer containing a static ffmpeg

  



  The Error :

  



  {
  "errorMessage": "[Errno 2] No such file or directory: '/tmp/output.mp4'",
  "errorType": "FileNotFoundError",
  "stackTrace": [
    [
      "/var/task/lambda_function.py",
      19,
      "lambda_handler",
      "s3.Object(bucketLowRes, mp4OutputFileName).put(Body=open(new_file_key, 'rb'))"
    ]
  ]
}


  



  My Lambda function :

  



  import json
import os
import subprocess
import boto3

s3 = boto3.resource('s3')
bucketLowRes = s3.Bucket("bucket-conc-lowres")

def lambda_handler(event, context):
    # TODO implement

    mp4OutputFileName = 'output.mp4'

    new_file_key = os.path.abspath(os.path.join(os.sep, 'tmp', mp4OutputFileName))
    subprocess.call( ['/opt/ffmpeg', '-i', 'concat:s3://bucket-word-clips/00th76kqwfs915hbixycb77y9v3riwsj30.mp4|s3://bucket-word-clips/00uoakp6jyafbu13ycvl6w2i9tj42eux30.mp4', new_file_key ] )

    s3.Object(bucketLowRes, mp4OutputFileName).put(Body=open(new_file_key, 'rb'))

    return {
        'statusCode': 200,
        'body': json.dumps('Hello from Lambda!')
    }


  



  Question :

  



  

  • FileNotFoundError : Where is the output mp4 file of my ffmpeg concat being saved ??

  


  • And if it is being saved to /tmp/output.mp4 , then why the FileNotFoundError ??

  


  



  thanks

  


• Lambda/ffmpeg timelapse generation - output zero bytes, can't debug ffmpeg

  25 août 2021, par GoOutside

  I am attempting to use an AWS Lambda FFMPEG layer to build a timelapse of static images in an S3 bucket. To begin, I am basing my project off of the tutorial located here.

  


  I can replicate the steps in the tutorial, so I know the FFMPEG layer is working in Lambda. I have replicated the FFMPEG commands on a standalone server, so I know they are correct.

  


  Here is my setup : I have two S3 buckets, lambda-source-bucket and lambda-destination-bucket. The contents of lambda-source-bucket are :

  


  1.jpg
2.jpg
3.jpg
4.jpg
5.jpg
6.jpg
7.jpg
files.txt


  


  The files.txt contains this :

  


  file 'https://lambda-source-bucket.s3.us-west-2.amazonaws.com/1.jpg'
file 'https://lambda-source-bucket.s3.us-west-2.amazonaws.com/2.jpg'
file 'https://lambda-source-bucket.s3.us-west-2.amazonaws.com/3.jpg'
file 'https://lambda-source-bucket.s3.us-west-2.amazonaws.com/4.jpg'
file 'https://lambda-source-bucket.s3.us-west-2.amazonaws.com/5.jpg'
file 'https://lambda-source-bucket.s3.us-west-2.amazonaws.com/6.jpg'
file 'https://lambda-source-bucket.s3.us-west-2.amazonaws.com/7.jpg'


  


  This is my Lambda function code (in Python) :

  


  import json
import os
import subprocess
import shlex
import boto3

S3_DESTINATION_BUCKET = "lambda-destination-bucket"
SIGNED_URL_TIMEOUT = 60

def lambda_handler(event, context):

    s3_source_bucket = event['Records'][0]['s3']['bucket']['name']
    s3_source_key = event['Records'][0]['s3']['object']['key']

    s3_source_basename = os.path.splitext(os.path.basename(s3_source_key))[0]
    s3_destination_filename = "timelapse.mp4"

    s3_client = boto3.client('s3')
    s3_source_signed_url = s3_client.generate_presigned_url('get_object',
        Params={'Bucket': s3_source_bucket, 'Key': s3_source_key},
        ExpiresIn=SIGNED_URL_TIMEOUT)

    ffmpeg_cmd = "/opt/bin/ffmpeg -y -r 24 -f concat -safe 0 -protocol_whitelist file,http,tcp,https,tls -I ""https://lambda-source-bucket.s3.us-west-2.amazonaws.com/files.txt"" -c copy -s 1024x576 -vcodec libx264 -"    
command1 = shlex.split(ffmpeg_cmd)
    p1 = subprocess.run(command1, stdout=subprocess.PIPE, stderr=subprocess.PIPE)

    resp = s3_client.put_object(Body=p1.stdout, Bucket=S3_DESTINATION_BUCKET, Key=s3_destination_filename)

    return {
        'statusCode': 200,
        'body': json.dumps('Processing complete successfully')
    }


  


  The trigger for the Lambda function is when a new files.txt file is added to lambda-source-bucket.

  


  So far I have been able to get the trigger to fire, the function supposedly runs without errors (in Cloudwatch), and the function creates a new timelapse.mp4 in the lambda-destination-bucket. But this file is 0 bytes. I see no FFMPEG errors in the Cloudwatch console, though I am not sure I know how to configure my Lambda function code to log FFMPEG errors.

  


  Also : if I'm going about this in a totally wrong way, I'd love to hear feedback. I'm guessing that the concat and files.txt method of looping through https:// is not the most efficient way to do this, but it's the only way I can figure this out so far.

  


  Any help is most sincerely and humbly appreciated.