Super Slow Motion Video Creation using Generative AI
Create high quality super slow motion video from regular framerate video
Overview
Traditionally producing super slow motion video requires special type of camera on the arena. This demo showcases an alternative to create super slow motion video clip with the use of Foundation AI model. It simplifies the broadcast workflow and also allows the customer to create short form slow motion clip at any time or at any camera angle.
The Super slow motion video creation demonstrates the ability of using Amazon SageMaker JumpStart with open source machine learning models (DAIN and FILM) to create a visually compelling super slow motion video from a normal framerate video file.
This demonstration focuses on how our customer can easily adapt state of the art open source machine learning models and algorithm using Amazon SageMaker JumpStart and innovate.
Architecture
The Super slow motion video creation uses serverless architecture approach where the AWS Step Functions state machine orchestrates the workflow. (1) Upload video to Amazon Simple Storage Service (Amazon S3) bucket. (2) Upon upload completed, an event trigger an AWS Step Functions state machine execution to process the request. (3) AWS Batch service is configured to use FFMPEG, an open source tool to extract video frames from the video, store the frames to Amazon S3 bucket, and invoke an Amazon SageMaker Batch Transform process. (4) The FILM (or DAIN) machine learning model, hosted on Amazon SageMaker, takes the video frames as an input to run the depth aware interpolation process and products the slow motion frames. (5) AWS Batch service then takes the interpolated frames and encodes the frames to create the super slow motion video (the final output).
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