With Amazon Lookout for Vision, you pay only for what you use. There is no up-front commitment or minimum fee. After you create a project and upload baseline images, Amazon Lookout for Vision lets you detect anomalies by training a customized defect detection machine learning (ML) model on your manufacturing lines.

You can choose to detect anomalies either by using Amazon Lookout for Vision’s cloud APIs or on the edge by deploying the trained model to a hardware device of your choice. Amazon Lookout for Vision models can be deployed on any NVIDIA Jetson edge appliance or x86 compute platform running Linux with an NVIDIA GPU accelerator. We use Amazon SageMaker Neo to compile our models to be edge compatible. See the list of supported devices here. You can use AWS IoT Greengrass to deploy, and manage your edge compatible customized models on your fleet of devices. You will pay separately for the AWS IoT Greengrass service.

There are three components that determine your bill: charges for training the model (training hours), charges for detecting anomalies on the cloud (cloud inference hours), and/or charges for detecting anomalies on the edge (edge inference units). 

Training Hours

You pay for the number of hours it takes to train your defect detection model. Amazon Lookout for Vision can provision multiple compute resources in parallel to quickly train your model. For example, Lookout for Vision might provision three compute resources to run simultaneously. Each resource, using three different algorithms, runs for 30 minutes. You then pick the best algorithm for your model. This means that you will have a trained model ready for use within 30 minutes, but the number of hours billed will be 1.5 hours (30 minutes x 3 resources).

Cloud Inference Hours

You pay for the number of hours you detect anomalies or defects with your customized model. To find defects using your model, Lookout for Vision provisions a minimum of one compute resource, known as an inference unit. A single cloud inference unit represents 1 hour of processing and can support up to 5 Transaction Per Second (TPS). You can increase or decrease your defect detection capacity depending on the demands of your manufacturing line by requesting additional inference units. You are billed per inference unit * inference hours that you use your defect detection model. For example, if you are using 2 inference units and you use the model for 8 hours (start at 9 AM and stop at 5 PM), you would be billed 8 * 2 = 16 inference hours. If you do not explicitly stop using your model, you will continue to be charged even if you are not actively detecting anomalies using the model.

Edge Inference Units

You will be charged a monthly fee per Lookout for Vision edge inference unit used. One edge inference unit is the compute used by the Lookout for Vision model deployed on your edge appliance to process up to 120 inspections per minute from connected camera streams. You are billed monthly based on the number of edge inference units per edge appliance * number of edge appliances that are using the defect detection model. Lookout for Vision charges a minimum of one edge inference unit per month from one connected camera stream. For example, a Lookout for Vision model deployed on an edge appliance to detect defective silicon wafers from a production line that manufactures 100 silicon wafers per minute consumes one edge inference unit per month. The monthly charge in this example is 1 edge inference unit * 1 edge appliance = 1 edge inference unit.

We’ve seen that typically one active camera stream can support a maximum of 120 inspections per minute and would use one edge inference unit in one month. For example, if you have two active camera streams connected to an edge appliance running a Lookout for Vision anomaly detection model, you would be billed for 2 edge inference units for that month. Now, if you have 5 edge appliances, each using 2 edge inference units, you would be billed for 5*2 = 10 edge inference units for that month. Regardless of whether you’re actively using Lookout for Vision on your edge appliance for 4 hours a day or 24 hours a day, as long as the query rate in any given month is below 120 inspections/minute on that edge appliance you will be charged for one edge inference unit. 

AWS Free Tier

As part of the AWS Free Tier, you can get started with Amazon Lookout for Vision for free. The Free Tier lasts 3 months and includes 10 free training hours per month, up to 4 free cloud inference hours per month, and up to 5 free edge inference units per month. 

Pricing tables

Amazon Lookout for Vision Training and Inference usage is billed on minute increments, with a minimum of one minute.

* Amazon Lookout for Vision Training and Cloud Inference usage is billed on minute increments, with a minimum of 1 minute
**Amazon Lookout for Vision edge inference is billed in edge inference unit increments, with a minimum of 1 edge inference unit per month per edge appliance. 

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