View Source aws_lookoutvision (aws v1.0.4)
This is the Amazon Lookout for Vision API Reference.
It provides descriptions of actions, data types, common parameters, and common errors.
Amazon Lookout for Vision enables you to find visual defects in industrial products, accurately and at scale. It uses computer vision to identify missing components in an industrial product, damage to vehicles or structures, irregularities in production lines, and even minuscule defects in silicon wafers — or any other physical item where quality is important such as a missing capacitor on printed circuit boards.Summary
Functions
Creates a new dataset in an Amazon Lookout for Vision project.
Creates a new version of a model within an an Amazon Lookout for Vision project.
Creates an empty Amazon Lookout for Vision project.
Deletes an existing Amazon Lookout for Vision dataset
.
Deletes an Amazon Lookout for Vision model.
Deletes an Amazon Lookout for Vision project.
Describe an Amazon Lookout for Vision dataset.
Describes a version of an Amazon Lookout for Vision model.
Describes an Amazon Lookout for Vision model packaging job.
Describes an Amazon Lookout for Vision project.
Detects anomalies in an image that you supply.
Lists the JSON Lines within a dataset.
Lists the model packaging jobs created for an Amazon Lookout for Vision project.
Lists the versions of a model in an Amazon Lookout for Vision project.
Lists the Amazon Lookout for Vision projects in your AWS account that are in the AWS Region in which you call ListProjects
.
Returns a list of tags attached to the specified Amazon Lookout for Vision model.
Starts the running of the version of an Amazon Lookout for Vision model.
Starts an Amazon Lookout for Vision model packaging job.
Stops the hosting of a running model.
Adds one or more key-value tags to an Amazon Lookout for Vision model.
Removes one or more tags from an Amazon Lookout for Vision model.
Adds or updates one or more JSON Line entries in a dataset.
Functions
Creates a new dataset in an Amazon Lookout for Vision project.
CreateDataset
can create a training or a test dataset from a valid dataset source (DatasetSource
).
If you want a single dataset project, specify train
for the value of DatasetType
.
To have a project with separate training and test datasets, call CreateDataset
twice. On the first call, specify train
for the value of DatasetType
. On the second call, specify test
for the value of DatasetType
.
lookoutvision:CreateDataset
operation.
Creates a new version of a model within an an Amazon Lookout for Vision project.
CreateModel
is an asynchronous operation in which Amazon Lookout for Vision trains, tests, and evaluates a new version of a model.
To get the current status, check the Status
field returned in the response from DescribeModel
.
If the project has a single dataset, Amazon Lookout for Vision internally splits the dataset to create a training and a test dataset. If the project has a training and a test dataset, Lookout for Vision uses the respective datasets to train and test the model.
After training completes, the evaluation metrics are stored at the location specified in OutputConfig
.
lookoutvision:CreateModel
operation. If you want to tag your model, you also require permission to the lookoutvision:TagResource
operation.
Creates an empty Amazon Lookout for Vision project.
After you create the project, add a dataset by calling CreateDataset
.
lookoutvision:CreateProject
operation.
Deletes an existing Amazon Lookout for Vision dataset
.
If your the project has a single dataset, you must create a new dataset before you can create a model.
If you project has a training dataset and a test dataset consider the following.
If you delete the test dataset, your project reverts to a single dataset project. If you then train the model, Amazon Lookout for Vision internally splits the remaining dataset into a training and test dataset.
If you delete the training dataset, you must create a training dataset before you can create a model.
lookoutvision:DeleteDataset
operation.
delete_dataset(Client, DatasetType, ProjectName, Input0, Options0)
View SourceDeletes an Amazon Lookout for Vision model.
You can't delete a running model. To stop a running model, use the StopModel
operation.
It might take a few seconds to delete a model. To determine if a model has been deleted, call ListModels
and check if the version of the model (ModelVersion
) is in the Models
array.
lookoutvision:DeleteModel
operation.
Deletes an Amazon Lookout for Vision project.
To delete a project, you must first delete each version of the model associated with the project. To delete a model use the DeleteModel
operation.
You also have to delete the dataset(s) associated with the model. For more information, see DeleteDataset
. The images referenced by the training and test datasets aren't deleted.
lookoutvision:DeleteProject
operation.
Describe an Amazon Lookout for Vision dataset.
This operation requires permissions to perform thelookoutvision:DescribeDataset
operation.
describe_dataset(Client, DatasetType, ProjectName, QueryMap, HeadersMap)
View Sourcedescribe_dataset(Client, DatasetType, ProjectName, QueryMap, HeadersMap, Options0)
View SourceDescribes a version of an Amazon Lookout for Vision model.
This operation requires permissions to perform thelookoutvision:DescribeModel
operation.
describe_model(Client, ModelVersion, ProjectName, QueryMap, HeadersMap)
View Sourcedescribe_model(Client, ModelVersion, ProjectName, QueryMap, HeadersMap, Options0)
View SourceDescribes an Amazon Lookout for Vision model packaging job.
This operation requires permissions to perform the lookoutvision:DescribeModelPackagingJob
operation.
describe_model_packaging_job(Client, JobName, ProjectName, QueryMap, HeadersMap)
View Sourcedescribe_model_packaging_job(Client, JobName, ProjectName, QueryMap, HeadersMap, Options0)
View SourceDescribes an Amazon Lookout for Vision project.
This operation requires permissions to perform thelookoutvision:DescribeProject
operation.
describe_project(Client, ProjectName, QueryMap, HeadersMap, Options0)
View SourceDetects anomalies in an image that you supply.
The response from DetectAnomalies
includes a boolean prediction that the image contains one or more anomalies and a confidence value for the prediction. If the model is an image segmentation model, the response also includes segmentation information for each type of anomaly found in the image.
Before calling DetectAnomalies
, you must first start your model with the StartModel
operation. You are charged for the amount of time, in minutes, that a model runs and for the number of anomaly detection units that your model uses. If you are not using a model, use the StopModel
operation to stop your model.
For more information, see Detecting anomalies in an image in the Amazon Lookout for Vision developer guide.
This operation requires permissions to perform thelookoutvision:DetectAnomalies
operation.
detect_anomalies(Client, ModelVersion, ProjectName, Input0, Options0)
View SourceLists the JSON Lines within a dataset.
An Amazon Lookout for Vision JSON Line contains the anomaly information for a single image, including the image location and the assigned label.
This operation requires permissions to perform thelookoutvision:ListDatasetEntries
operation.
list_dataset_entries(Client, DatasetType, ProjectName, QueryMap, HeadersMap)
View Sourcelist_dataset_entries(Client, DatasetType, ProjectName, QueryMap, HeadersMap, Options0)
View SourceLists the model packaging jobs created for an Amazon Lookout for Vision project.
This operation requires permissions to perform the lookoutvision:ListModelPackagingJobs
operation.
list_model_packaging_jobs(Client, ProjectName, QueryMap, HeadersMap)
View Sourcelist_model_packaging_jobs(Client, ProjectName, QueryMap, HeadersMap, Options0)
View SourceLists the versions of a model in an Amazon Lookout for Vision project.
The ListModels
operation is eventually consistent. Recent calls to CreateModel
might take a while to appear in the response from ListProjects
.
lookoutvision:ListModels
operation.
Lists the Amazon Lookout for Vision projects in your AWS account that are in the AWS Region in which you call ListProjects
.
The ListProjects
operation is eventually consistent. Recent calls to CreateProject
and DeleteProject
might take a while to appear in the response from ListProjects
.
lookoutvision:ListProjects
operation.
Returns a list of tags attached to the specified Amazon Lookout for Vision model.
This operation requires permissions to perform thelookoutvision:ListTagsForResource
operation.
list_tags_for_resource(Client, ResourceArn, QueryMap, HeadersMap, Options0)
View SourceStarts 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
.
lookoutvision:StartModel
operation.
Starts an Amazon Lookout for Vision model packaging job.
A model packaging job creates an AWS IoT Greengrass component for a Lookout for Vision model. You can use the component to deploy your model to an edge device managed by Greengrass.
Use the DescribeModelPackagingJob
API to determine the current status of the job. The model packaging job is complete if the value of Status
is SUCCEEDED
.
To deploy the component to the target device, use the component name and component version with the AWS IoT Greengrass CreateDeployment: https://docs.aws.amazon.com/greengrass/v2/APIReference/API_CreateDeployment.html API.
This operation requires the following permissions:
lookoutvision:StartModelPackagingJob
s3:PutObject
s3:GetBucketLocation
kms:GenerateDataKey
greengrass:CreateComponentVersion
greengrass:DescribeComponent
(Optional)
greengrass:TagResource
. Only required if you want to tag the component.
Stops the hosting of a running model.
The operation might take a while to complete. To check the current status, call DescribeModel
.
After the model hosting stops, the Status
of the model is TRAINED
.
lookoutvision:StopModel
operation.
Adds one or more key-value tags to an Amazon Lookout for Vision model.
For more information, see Tagging a model in the Amazon Lookout for Vision Developer Guide.
This operation requires permissions to perform thelookoutvision:TagResource
operation.
Removes one or more tags from an Amazon Lookout for Vision model.
For more information, see Tagging a model in the Amazon Lookout for Vision Developer Guide.
This operation requires permissions to perform thelookoutvision:UntagResource
operation.
Adds or updates one or more JSON Line entries in a dataset.
A JSON Line includes information about an image used for training or testing an Amazon Lookout for Vision model.
To update an existing JSON Line, use the source-ref
field to identify the JSON Line. The JSON line that you supply replaces the existing JSON line. Any existing annotations that are not in the new JSON line are removed from the dataset.
For more information, see Defining JSON lines for anomaly classification in the Amazon Lookout for Vision Developer Guide.
The images you reference in the source-ref
field of a JSON line, must be in the same S3 bucket as the existing images in the dataset.
Updating a dataset might take a while to complete. To check the current status, call DescribeDataset
and check the Status
field in the response.
lookoutvision:UpdateDatasetEntries
operation.