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Copy file name to clipboardExpand all lines: CHANGELOG.md
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All notable changes to this project will be documented in this file.
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## version v0.0.8
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### Added
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- New compute family available Fargate with Graviton 2: You can run your applications using the Fargate (Serverless) launch type with the ARM64 architecture.
In this example we use the AWS SDK "Boto3" (Python) and I want to cut a specific part of a video. First of all, I uploaded a video in the Amazon S3 bucket created by the solution, and complete the parameters below :
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Parameters of this `input.json are:
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-`$.name`: metadata of this job for observability.
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-`$.compute`: Instances family used to compute the media asset : `intel`, `arm`, `amd`, `nvidia`, `xilinx`.
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-`$.compute`: Instances family used to compute the media asset : `intel`, `arm`, `amd`, `nvidia`, `xilinx`, `fargate`, `fargate-arm`.
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-`$.input.s3_bucket` and `$.input.s3_prefix`: S3 url of the list of Amazon S3 Objects to be processed by FFMPEG.
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-`$.input.file_options`: FFmpeg input file options described in the official documentation.
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-`$.output.s3_bucket` and `$.output.s3_prefix`: S3 url where all processed media assets will be stored on Amazon S3.
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## Performance and quality metrics
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AWS Customers also wants to use this solution to benchmark the video encoding performance and quality of Amazon EC2 instance families. I analyze performance and video quality metrics thanks to AWS X-Ray service. i define 3 segments : Amazon S3 download, FFmpeg Execution and Amazon S3 upload.
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AWS Customers also wants to use this solution to benchmark the video encoding performance and quality of Amazon EC2 instance families. I analyze performance and video quality metrics thanks to AWS X-Ray service. I define 3 segments : Amazon S3 download, FFmpeg Execution and Amazon S3 upload.
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If I switch the AWS SSM (Systems Manager) Parameter `/batch-ffmpeg/ffqm` to `TRUE`, quality metrics PSNR, SSIM, VMAF are calculated and exported as an AWS X-RAY metadata and as a JSON file in the Amazon S3 bucket with the key prefix `/metrics/ffqm`. Those metrics are available through AWS Athena views `batch_FFmpeg_ffqm_psnr`, `batch_FFmpeg_ffqm_ssim`, `batch_FFmpeg_ffqm_vmaf`.
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