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• swscale/aarch64 : add hscale specializations

  26 mai 2022, par Swinney, Jonathan

  swscale/aarch64 : add hscale specializations
  This patch adds code to support specializations of the hscale function
  
  and adds a specialization for filterSize == 4.
  ff_hscale8to15_4_neon is a complete rewrite. Since the main bottleneck
  
  here is loading the data from src, this data is loaded a whole block
  
  ahead and stored back to the stack to be loaded again with ld4. This
  
  arranges the data for most efficient use of the vector instructions and
  
  removes the need for completion adds at the end. The number of
  
  iterations of the C per iteration of the assembly is increased from 4 to
  
  8, but because of the prefetching, there must be a special section
  
  without prefetching when dstW < 16.
  This improves speed on Graviton 2 (Neoverse N1) dramatically in the case
  
  where previously fs=8 would have been required.
  before : hscale_8_to_15__fs_8_dstW_512_neon : 1962.8
  
  after : hscale_8_to_15__fs_4_dstW_512_neon : 1220.9
  Signed-off-by : Jonathan Swinney <jswinney@amazon.com>
  
  Signed-off-by : Martin Storsjö <martin@martin.st>
  

  • [DH] libswscale/aarch64/hscale.S
  • [DH] libswscale/aarch64/swscale.c
  • [DH] libswscale/utils.c

• ffmpeg file conversion AWS Lamda

  10 avril 2021, par eartoolbox

  I want a .webm file to be converted to a .wav file after it hits my S3 bucket. I followed this tutorial and tried to adapt it from my use case using the .webm -> .wav ffmpeg command described here.

  


  My AWS Lambda function generally works, in that when my .webm file hits the source bucket, it is converted to .wav and ends up in the destination bucket. However, the resulting file .wav is always 0 bytes (though the .webm not, including the appropriate audio). Did I adapt the code wrong ? I only changed the ffmpeg_cmd line from the first link.

  


  import json
import os
import subprocess
import shlex
import boto3

S3_DESTINATION_BUCKET = "hmtm-out"
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 = s3_source_basename + ".wav"

    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 -i \"" + s3_source_signed_url + "\" -c:a pcm_f32le " + s3_destination_filename + " -"
    
    
    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')
    }
 


  


• ffmpeg file conversion AWS Lambda

  10 avril 2021, par eartoolbox

  I want a .webm file to be converted to a .wav file after it hits my S3 bucket. I followed this tutorial and tried to adapt it from my use case using the .webm -> .wav ffmpeg command described here.

  


  My AWS Lambda function generally works, in that when my .webm file hits the source bucket, it is converted to .wav and ends up in the destination bucket. However, the resulting file .wav is always 0 bytes (though the .webm not, including the appropriate audio). Did I adapt the code wrong ? I only changed the ffmpeg_cmd line from the first link.

  


  import json
import os
import subprocess
import shlex
import boto3

S3_DESTINATION_BUCKET = "hmtm-out"
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 = s3_source_basename + ".wav"

    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 -i \"" + s3_source_signed_url + "\" -c:a pcm_f32le " + s3_destination_filename + " -"
    
    
    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')
    }