[ aws . lookoutvision ]



Starts the running of the version of an Amazon Lookout for Vision model. Starting a model takes a while to complete. To check the current state of the model, use DescribeModel .

A model is ready to use when its status is HOSTED .

Once the model is running, you can detect custom labels in new images by calling DetectAnomalies .


You are charged for the amount of time that the model is running. To stop a running model, call StopModel .

This operation requires permissions to perform the lookoutvision:StartModel operation.

See also: AWS API Documentation

See ‘aws help’ for descriptions of global parameters.


--project-name <value>
--model-version <value>
--min-inference-units <value>
[--client-token <value>]
[--max-inference-units <value>]
[--cli-input-json | --cli-input-yaml]
[--generate-cli-skeleton <value>]


--project-name (string)

The name of the project that contains the model that you want to start.

--model-version (string)

The version of the model that you want to start.

--min-inference-units (integer)

The minimum number of inference units to use. A single inference unit represents 1 hour of processing. Use a higher number to increase the TPS throughput of your model. You are charged for the number of inference units that you use.

--client-token (string)

ClientToken is an idempotency token that ensures a call to StartModel completes only once. You choose the value to pass. For example, An issue might prevent you from getting a response from StartModel . In this case, safely retry your call to StartModel by using the same ClientToken parameter value.

If you don’t supply a value for ClientToken , the AWS SDK you are using inserts a value for you. This prevents retries after a network error from making multiple start requests. You’ll need to provide your own value for other use cases.

An error occurs if the other input parameters are not the same as in the first request. Using a different value for ClientToken is considered a new call to StartModel . An idempotency token is active for 8 hours.

--max-inference-units (integer)

The maximum number of inference units to use for auto-scaling the model. If you don’t specify a value, Amazon Lookout for Vision doesn’t auto-scale the model.

--cli-input-json | --cli-input-yaml (string) Reads arguments from the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, those values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally. This may not be specified along with --cli-input-yaml.

--generate-cli-skeleton (string) Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input, prints a sample input JSON that can be used as an argument for --cli-input-json. Similarly, if provided yaml-input it will print a sample input YAML that can be used with --cli-input-yaml. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command. The generated JSON skeleton is not stable between versions of the AWS CLI and there are no backwards compatibility guarantees in the JSON skeleton generated.

See ‘aws help’ for descriptions of global parameters.


Status -> (string)

The current running status of the model.