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#Grab cad download#

You can use the Amazon CloudWatch Console to watch the Fargate task in progress.

Press the Run Task button to run the task.

Add the both of the available Subnets to the Cluster VPC.

Select the Task Definition and from the Actions button select Run Task.

Navigate to the Task Definition section.

OutputFolder/resultFile.xxx with output/Waste_Container.glb My-output-bucket-name with pixyz-example-20211117 Input/inputFile.step with input/Waste_Container.step

My-input-bucket-name with pixyz-example-20211117 image url: /pixyz-software/scenario-processor:2021.1.0.79.Create a container with the Add container button and configure with:.For Task Execution role, again, use the IAM role you created: pixyz-example-role-20211117.For Task role, use the IAM role you created above: pixyz-example-role-20211117.Give it a name, I used: pixyz-example-task.Choose the Fargate option and select the Next step button.Navigate to the Task Definition section and select the button to Create new Task Definition.Enable Create a new VPC for this cluster.Select Networking Only and then the Next step button.Navigate to the Clusters section and select the button to Create Cluster.Permissions policies applied to IAM Role pixyz-example-role-20211117 Step 3: Create the Network Only Cluster I will be using the file, Waste_Container.step, but you can use your own visual assets. Estimated cost of completing this exercise is $0.25 – $1.00. Current pricing information is available on the AWS Marketplace product page for Pixyz Scenario Processor. For this example, you will be charged for using Pixyz Scenario Processor with usage based pricing.A subscription to Pixyz Scenario Processor on AWS Marketplace.

#Grab cad download#

(Optional) Download the glTF file and view itįor this walkthrough, the following are prerequisites:.

Create an IAM Role for running Amazon ECS Tasks with the Pixyz Scenario Processor.

Upload the source files to an S3 Bucket.

This requires adjusting the default IAM policy for running tasks on Amazon ECS to allow for metering usage of the AWS Marketplace solution. The Fargate Task will use the Pixyz Scenario Processor from the AWS Marketplace. In this walkthrough I will demonstrate the creation of an AWS Fargate Task that will grab a CAD file from an S3 bucket, convert it to a GLB (binary glTF format) file and store it back in that S3 bucket. After running the task, you will download the resulting file from Amazon S3 to inspect it in a glTF compatible viewer. You will also create and run an AWS Fargate Task that uses the Pixyz Scenario Composer container image to convert the CAD file to glTF. You will create an Amazon S3 bucket and upload your CAD file for conversion. In this walkthrough, you will setup Amazon Elastic Container Service (ECS) to run the Pixyz Scenario Processor on a file stored in Amazon Simple Storage Service (Amazon S3). It has options for setting the desired polygon count, determining if objects should be merged together, and determining if hidden objects should be deleted. This scenario uses the most common settings for converting CAD assets to realtime assets for use in game engines and WebGL views. In this example, I will be using the GenericPolygonTarget scenario. It can be configured for several different scenarios. Pixyz Scenario Processor is a solution provided by Pixyz that is available in AWS Marketplace.

In this post, I will demonstrate a workflow for using Pixyz Scenario Processor to convert a CAD file in the STEP format to a realtime 3D file in the glTF format. Customers will need to convert their CAD assets to the glTF format before importing those assets to AWS IoT TwinMaker. They are not usually compatible with realtime WebGL viewports like those used in AWS IoT TwinMaker, which supports the glTF format. CAD files are either proprietary formats optimized for use in proprietary applications or interchange formats designed for moving CAD data from one application to another. Customers often have existing 3D CAD (Computer-aided Design) assets that they would like to use with AWS IoT TwinMaker.