Skip to content

Deploy an Endpoint for Instance segmentation Mask R-CNN

1. Subscribe to the offering

  1. Log in to AWS with a user with administrative privileges
  2. Navigate to the Instance segmentation Mask R-CNN listing on the AWS Marketplace
  3. Click Continue to Subscribe
  4. Click on Accept offer (it might take 1 or 2 minutes for AWS to accept the offer)
    • Note that there is no charge for subscribing to this offering
    • Billing starts only when launching a Model Endpoint on SageMaker
  5. Once you are subscribed click Continue to Configuration
  6. On the Configure and launch page
    1. Select SageMaker console as the Launch Method (you can also use the AWS CLI)
    2. Select the version and region where you want to launch the model endpoint
    3. On Amazon SageMaker options select Create a real-time inference endpoint
  7. Click on View in Amazon SageMaker

2. Create the endpoint

In the Create endpoint page:

  1. Select a Model name e.g. my-instance-segmentation
  2. Select or create a new IAM role for executing the model
  3. Under Container definition:
    1. Verify Use a model package subscription from AWS Marketplace is selected
  4. Click on Next
  5. Select an Endpoint name e.g. my-instance-segmentation
  6. Under Attach endpoint configuration select: Create a new endpoint configuration
  7. Under New endpoint configuration:
    1. Verify the new model (e.g. my-instance-segmentation) is listed under Production variants
    2. Click on Edit in the Actions column to select the instance types you want for the endpoint. The minimun recommended is ml.c5.xlarge
    3. Click on Create endpoint configuration
  8. Finally click on Submit

A new endpoint will be created (this might take a couple of minutes):

SageMaker Endpoint

3. Making a query

With the endpoint ready you will have an URL to make predictions, for example:

SageMaker Endpoint URL

This endpoint requires authentication using the AWS Signature Version 4

We also provide example code to make a query to this Invocations endpoint on the API docs.