Run SAM2 on your own AWS on Serverless GPUs
Deploy serverless GPU applications on your AWS account
Built with developer experience in mind, Tensorkube simplifies the process of deploying serverless GPU apps. In this guide, we will walk you through the process of deploying SAM2 on your private cloud.
Meta recently unveiled Segment Anything Model 2 (SAM 2), a revolutionary advancement in object segmentation. SAM 2 integrates real-time, promptable object segmentation for both images and videos, enhancing accuracy and speed
Prerequisites
Before you begin, ensure you have configured Tensorkube on your AWS account. If you haven’t done that yet, follow the Getting Started guide.
Deploying SAM2 with Tensorfuse
Each tensorkube deployment requires two things - your code and your environment (as a Dockerfile). While deploying machine learning models, it is beneficial if your model is also a part of your container image. This reduces cold-start times by a significant margin. To enable this, along with the Fast API app, we will download the model weights and make them part of the Dockerfile
Code files
We will write a small FastAPI app that takes image as input and outputs predicted labels. The FastAPI app will have three endpoints - /readiness
, /
, and /segment
. Remember that the /readiness
endpoint is used by Tensorkube to check the health of your deployments.
Environment files (Dockerfile)
Next, create a Dockerfile for your FastAPI app. Given below is a simple Dockerfile that you can use:
Deploying the app
SAM2 is now ready to be deployed on Tensorkube. Navigate to your project root and run the following command:
SAM2 is now deployed on your AWS account. You can access your app at the URL provided in the output or using the following command:
And that’s it! You have successfully deployed SAM2 on serverless GPUs using Tensorkube. 🚀
To test it out you can run the following command by replacing the URL with the one provided in the output:
You can also use the readiness endpoint to wake up your nodes in case you are expecting incoming traffic