CODEWITHSUNDEEP
amazon-web-servicesamazon-sagemaker
Daniel Gretzke
Daniel Gretzke

Reputation: 446

SageMaker deploy custom script

I'm pretty new to SageMaker, so I'm sorry if I miss something obvious.

I've trained a DL model which uses frames from a video to make a prediction. The current script, that runs in the SageMaker jupyter-notebook, takes a video URL as an input and uses an FFMPEG subprocess pipe to extract the frames and predict them afterwards. This works fine, but now I want to start that script from Lambda.

As far as I understood, I could deploy my model with sagemaker and make predictions for every single frame from Lambda, unfortunately this is not an option, as ffprobe, ffmpeg and numpy are too large to fit into the limited lambda space.

tl;dr: Is it possible to run my custom script (ffmpeg frame extraction + tensorflow model prediction) as an endpoint in SageMaker?

Upvotes: 0

Views: 741

Answers (1)

Tuan Vo
Tuan Vo

Reputation: 2065

Sagemaker allows you to use a custom Docker image (AWS document)

Build your own custom container image: If there is no pre-built Amazon SageMaker container image that you can use or modify for an advanced scenario, you can package your own script or algorithm to use with Amazon SageMaker.You can use any programming language or framework to develop your container

  • Create a docker image with your code (FFmpeg, TensorFlow)
  • Testing the docker container locally
  • Deploying the image on Amazon ECR (Elastic Container Repository)
  • Create a SageMaker model and point to the image

For details, you can learn more from this tutorial

Upvotes: 1

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