Table of Contents
LookoutforVision.
Client
¶A low-level client representing Amazon Lookout for Vision
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.
client = session.create_client('lookoutvision')
These are the available methods:
can_paginate
(operation_name)¶Check if an operation can be paginated.
operation_name (string) – The operation name. This is the same name
as the method name on the client. For example, if the
method name is create_foo
, and you’d normally invoke the
operation as client.create_foo(**kwargs)
, if the
create_foo
operation can be paginated, you can use the
call client.get_paginator("create_foo")
.
True
if the operation can be paginated,
False
otherwise.
create_dataset
(**kwargs)¶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
.
This operation requires permissions to perform the lookoutvision:CreateDataset
operation.
See also: AWS API Documentation
Request Syntax
response = client.create_dataset(
ProjectName='string',
DatasetType='string',
DatasetSource={
'GroundTruthManifest': {
'S3Object': {
'Bucket': 'string',
'Key': 'string',
'VersionId': 'string'
}
}
},
ClientToken='string'
)
ProjectName (string) –
[REQUIRED]
The name of the project in which you want to create a dataset.
DatasetType (string) –
[REQUIRED]
The type of the dataset. Specify train
for a training dataset. Specify test
for a test dataset.
DatasetSource (dict) –
The location of the manifest file that Amazon Lookout for Vision uses to create the dataset.
If you don’t specify DatasetSource
, an empty dataset is created and the operation synchronously returns. Later, you can add JSON Lines by calling UpdateDatasetEntries .
If you specify a value for DataSource
, the manifest at the S3 location is validated and used to create the dataset. The call to CreateDataset
is asynchronous and might take a while to complete. To find out the current status, Check the value of Status
returned in a call to DescribeDataset .
GroundTruthManifest (dict) –
Location information for the manifest file.
S3Object (dict) –
The S3 bucket location for the manifest file.
Bucket (string) – [REQUIRED]
The Amazon S3 bucket that contains the manifest.
Key (string) – [REQUIRED]
The name and location of the manifest file withiin the bucket.
VersionId (string) –
The version ID of the bucket.
ClientToken (string) –
ClientToken is an idempotency token that ensures a call to CreateDataset
completes only once. You choose the value to pass. For example, An issue, such as an network outage, might prevent you from getting a response from CreateDataset
. In this case, safely retry your call to CreateDataset
by using the same ClientToken
parameter value. 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 CreateDataset
. An idempotency token is active for 8 hours.
This field is autopopulated if not provided.
dict
Response Syntax
{
'DatasetMetadata': {
'DatasetType': 'string',
'CreationTimestamp': datetime(2015, 1, 1),
'Status': 'CREATE_IN_PROGRESS'|'CREATE_COMPLETE'|'CREATE_FAILED'|'UPDATE_IN_PROGRESS'|'UPDATE_COMPLETE'|'UPDATE_FAILED_ROLLBACK_IN_PROGRESS'|'UPDATE_FAILED_ROLLBACK_COMPLETE'|'DELETE_IN_PROGRESS'|'DELETE_COMPLETE'|'DELETE_FAILED',
'StatusMessage': 'string'
}
}
Response Structure
(dict) –
DatasetMetadata (dict) –
Information about the dataset.
DatasetType (string) –
The type of the dataset.
CreationTimestamp (datetime) –
The Unix timestamp for the date and time that the dataset was created.
Status (string) –
The status for the dataset.
StatusMessage (string) –
The status message for the dataset.
Exceptions
create_model
(**kwargs)¶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
.
This operation requires permissions to perform the lookoutvision:CreateModel
operation. If you want to tag your model, you also require permission to the lookoutvision:TagResource
operation.
See also: AWS API Documentation
Request Syntax
response = client.create_model(
ProjectName='string',
Description='string',
ClientToken='string',
OutputConfig={
'S3Location': {
'Bucket': 'string',
'Prefix': 'string'
}
},
KmsKeyId='string',
Tags=[
{
'Key': 'string',
'Value': 'string'
},
]
)
ProjectName (string) –
[REQUIRED]
The name of the project in which you want to create a model version.
Description (string) – A description for the version of the model.
ClientToken (string) –
ClientToken is an idempotency token that ensures a call to CreateModel
completes only once. You choose the value to pass. For example, An issue, such as an network outage, might prevent you from getting a response from CreateModel
. In this case, safely retry your call to CreateModel
by using the same ClientToken
parameter value. 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 CreateModel
. An idempotency token is active for 8 hours.
This field is autopopulated if not provided.
OutputConfig (dict) –
[REQUIRED]
The location where Amazon Lookout for Vision saves the training results.
S3Location (dict) – [REQUIRED]
The S3 location for the output.
Bucket (string) – [REQUIRED]
The S3 bucket that contain the manifest file.
Prefix (string) –
The path and name of the manifest file with the S3 bucket.
KmsKeyId (string) – The identifier of the AWS Key Management Service (AWS KMS) customer master key (CMK) to use for encypting the model. If this parameter is not specified, the model is encrypted by a key that AWS owns and manages.
Tags (list) –
A set of tags (key-value pairs) that you want to attach to the model.
(dict) –
A key and value pair that is attached to the specified Amazon Lookout for Vision model.
Key (string) – [REQUIRED]
The key of the tag that is attached to the specified model.
Value (string) – [REQUIRED]
The value of the tag that is attached to the specified model.
dict
Response Syntax
{
'ModelMetadata': {
'CreationTimestamp': datetime(2015, 1, 1),
'ModelVersion': 'string',
'ModelArn': 'string',
'Description': 'string',
'Status': 'TRAINING'|'TRAINED'|'TRAINING_FAILED'|'STARTING_HOSTING'|'HOSTED'|'HOSTING_FAILED'|'STOPPING_HOSTING'|'SYSTEM_UPDATING'|'DELETING',
'StatusMessage': 'string',
'Performance': {
'F1Score': ...,
'Recall': ...,
'Precision': ...
}
}
}
Response Structure
(dict) –
ModelMetadata (dict) –
The response from a call to CreateModel
.
CreationTimestamp (datetime) –
The unix timestamp for the date and time that the model was created.
ModelVersion (string) –
The version of the model.
ModelArn (string) –
The Amazon Resource Name (ARN) of the model.
Description (string) –
The description for the model.
Status (string) –
The status of the model.
StatusMessage (string) –
The status message for the model.
Performance (dict) –
Performance metrics for the model. Not available until training has successfully completed.
F1Score (float) –
The overall F1 score metric for the trained model.
Recall (float) –
The overall recall metric value for the trained model.
Precision (float) –
The overall precision metric value for the trained model.
Exceptions
create_project
(**kwargs)¶Creates an empty Amazon Lookout for Vision project. After you create the project, add a dataset by calling CreateDataset .
This operation requires permissions to perform the lookoutvision:CreateProject
operation.
See also: AWS API Documentation
Request Syntax
response = client.create_project(
ProjectName='string',
ClientToken='string'
)
ProjectName (string) –
[REQUIRED]
The name for the project.
ClientToken (string) –
ClientToken is an idempotency token that ensures a call to CreateProject
completes only once. You choose the value to pass. For example, An issue, such as an network outage, might prevent you from getting a response from CreateProject
. In this case, safely retry your call to CreateProject
by using the same ClientToken
parameter value. 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 CreateProject
. An idempotency token is active for 8 hours.
This field is autopopulated if not provided.
dict
Response Syntax
{
'ProjectMetadata': {
'ProjectArn': 'string',
'ProjectName': 'string',
'CreationTimestamp': datetime(2015, 1, 1)
}
}
Response Structure
(dict) –
ProjectMetadata (dict) –
Information about the project.
ProjectArn (string) –
The Amazon Resource Name (ARN) of the project.
ProjectName (string) –
The name of the project.
CreationTimestamp (datetime) –
The unix timestamp for the date and time that the project was created.
Exceptions
delete_dataset
(**kwargs)¶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.
It might take a while to delete the dataset. To check the current status, check the Status
field in the response from a call to DescribeDataset .
This operation requires permissions to perform the lookoutvision:DeleteDataset
operation.
See also: AWS API Documentation
Request Syntax
response = client.delete_dataset(
ProjectName='string',
DatasetType='string',
ClientToken='string'
)
ProjectName (string) –
[REQUIRED]
The name of the project that contains the dataset that you want to delete.
DatasetType (string) –
[REQUIRED]
The type of the dataset to delete. Specify train
to delete the training dataset. Specify test
to delete the test dataset. To delete the dataset in a single dataset project, specify train
.
ClientToken (string) –
ClientToken is an idempotency token that ensures a call to DeleteDataset
completes only once. You choose the value to pass. For example, An issue, such as an network outage, might prevent you from getting a response from DeleteDataset
. In this case, safely retry your call to DeleteDataset
by using the same ClientToken
parameter value. 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 DeleteDataset
. An idempotency token is active for 8 hours.
This field is autopopulated if not provided.
dict
Response Syntax
{}
Response Structure
(dict) –
Exceptions
delete_model
(**kwargs)¶Deletes an Amazon Lookout for Vision model. You can’t delete a running model. To stop a running model, use the StopModel operation.
This operation requires permissions to perform the lookoutvision:DeleteModel
operation.
See also: AWS API Documentation
Request Syntax
response = client.delete_model(
ProjectName='string',
ModelVersion='string',
ClientToken='string'
)
ProjectName (string) –
[REQUIRED]
The name of the project that contains the model that you want to delete.
ModelVersion (string) –
[REQUIRED]
The version of the model that you want to delete.
ClientToken (string) –
ClientToken is an idempotency token that ensures a call to DeleteModel
completes only once. You choose the value to pass. For example, An issue, such as an network outage, might prevent you from getting a response from DeleteModel
. In this case, safely retry your call to DeleteModel
by using the same ClientToken
parameter value. 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 DeleteModel
. An idempotency token is active for 8 hours.
This field is autopopulated if not provided.
dict
Response Syntax
{
'ModelArn': 'string'
}
Response Structure
(dict) –
ModelArn (string) –
The Amazon Resource Name (ARN) of the model that was deleted.
Exceptions
delete_project
(**kwargs)¶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.
This operation requires permissions to perform the lookoutvision:DeleteProject
operation.
See also: AWS API Documentation
Request Syntax
response = client.delete_project(
ProjectName='string',
ClientToken='string'
)
ProjectName (string) –
[REQUIRED]
The name of the project to delete.
ClientToken (string) –
ClientToken is an idempotency token that ensures a call to DeleteProject
completes only once. You choose the value to pass. For example, An issue, such as an network outage, might prevent you from getting a response from DeleteProject
. In this case, safely retry your call to DeleteProject
by using the same ClientToken
parameter value. 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 DeleteProject
. An idempotency token is active for 8 hours.
This field is autopopulated if not provided.
dict
Response Syntax
{
'ProjectArn': 'string'
}
Response Structure
(dict) –
ProjectArn (string) –
The Amazon Resource Name (ARN) of the project that was deleted.
Exceptions
describe_dataset
(**kwargs)¶Describe an Amazon Lookout for Vision dataset.
This operation requires permissions to perform the lookoutvision:DescribeDataset
operation.
See also: AWS API Documentation
Request Syntax
response = client.describe_dataset(
ProjectName='string',
DatasetType='string'
)
ProjectName (string) –
[REQUIRED]
The name of the project that contains the dataset that you want to describe.
DatasetType (string) –
[REQUIRED]
The type of the dataset to describe. Specify train
to describe the training dataset. Specify test
to describe the test dataset. If you have a single dataset project, specify train
dict
Response Syntax
{
'DatasetDescription': {
'ProjectName': 'string',
'DatasetType': 'string',
'CreationTimestamp': datetime(2015, 1, 1),
'LastUpdatedTimestamp': datetime(2015, 1, 1),
'Status': 'CREATE_IN_PROGRESS'|'CREATE_COMPLETE'|'CREATE_FAILED'|'UPDATE_IN_PROGRESS'|'UPDATE_COMPLETE'|'UPDATE_FAILED_ROLLBACK_IN_PROGRESS'|'UPDATE_FAILED_ROLLBACK_COMPLETE'|'DELETE_IN_PROGRESS'|'DELETE_COMPLETE'|'DELETE_FAILED',
'StatusMessage': 'string',
'ImageStats': {
'Total': 123,
'Labeled': 123,
'Normal': 123,
'Anomaly': 123
}
}
}
Response Structure
(dict) –
DatasetDescription (dict) –
The description of the requested dataset.
ProjectName (string) –
The name of the project that contains the dataset.
DatasetType (string) –
The type of the dataset. The value train
represents a training dataset or single dataset project. The value test
represents a test dataset.
CreationTimestamp (datetime) –
The Unix timestamp for the time and date that the dataset was created.
LastUpdatedTimestamp (datetime) –
The Unix timestamp for the date and time that the dataset was last updated.
Status (string) –
The status of the dataset.
StatusMessage (string) –
The status message for the dataset.
ImageStats (dict) –
Total (integer) –
The total number of images in the dataset.
Labeled (integer) –
The total number of labeled images.
Normal (integer) –
The total number of images labeled as normal.
Anomaly (integer) –
the total number of images labeled as an anomaly.
Exceptions
describe_model
(**kwargs)¶Describes a version of an Amazon Lookout for Vision model.
This operation requires permissions to perform the lookoutvision:DescribeModel
operation.
See also: AWS API Documentation
Request Syntax
response = client.describe_model(
ProjectName='string',
ModelVersion='string'
)
ProjectName (string) –
[REQUIRED]
The project that contains the version of a model that you want to describe.
ModelVersion (string) –
[REQUIRED]
The version of the model that you want to describe.
dict
Response Syntax
{
'ModelDescription': {
'ModelVersion': 'string',
'ModelArn': 'string',
'CreationTimestamp': datetime(2015, 1, 1),
'Description': 'string',
'Status': 'TRAINING'|'TRAINED'|'TRAINING_FAILED'|'STARTING_HOSTING'|'HOSTED'|'HOSTING_FAILED'|'STOPPING_HOSTING'|'SYSTEM_UPDATING'|'DELETING',
'StatusMessage': 'string',
'Performance': {
'F1Score': ...,
'Recall': ...,
'Precision': ...
},
'OutputConfig': {
'S3Location': {
'Bucket': 'string',
'Prefix': 'string'
}
},
'EvaluationManifest': {
'Bucket': 'string',
'Key': 'string'
},
'EvaluationResult': {
'Bucket': 'string',
'Key': 'string'
},
'EvaluationEndTimestamp': datetime(2015, 1, 1),
'KmsKeyId': 'string'
}
}
Response Structure
(dict) –
ModelDescription (dict) –
Contains the description of the model.
ModelVersion (string) –
The version of the model
ModelArn (string) –
The Amazon Resource Name (ARN) of the model.
CreationTimestamp (datetime) –
The unix timestamp for the date and time that the model was created.
Description (string) –
The description for the model.
Status (string) –
The status of the model.
StatusMessage (string) –
The status message for the model.
Performance (dict) –
Performance metrics for the model. Created during training.
F1Score (float) –
The overall F1 score metric for the trained model.
Recall (float) –
The overall recall metric value for the trained model.
Precision (float) –
The overall precision metric value for the trained model.
OutputConfig (dict) –
The S3 location where Amazon Lookout for Vision saves model training files.
S3Location (dict) –
The S3 location for the output.
Bucket (string) –
The S3 bucket that contain the manifest file.
Prefix (string) –
The path and name of the manifest file with the S3 bucket.
EvaluationManifest (dict) –
The S3 location where Amazon Lookout for Vision saves the manifest file that was used to test the trained model and generate the performance scores.
Bucket (string) –
The bucket that contains the training output.
Key (string) –
The location of the training output in the bucket.
EvaluationResult (dict) –
The S3 location where Amazon Lookout for Vision saves the performance metrics.
Bucket (string) –
The bucket that contains the training output.
Key (string) –
The location of the training output in the bucket.
EvaluationEndTimestamp (datetime) –
The unix timestamp for the date and time that the evaluation ended.
KmsKeyId (string) –
The identifer for the AWS Key Management Service (AWS KMS) key that was used to encrypt the model during training.
Exceptions
describe_project
(**kwargs)¶Describes an Amazon Lookout for Vision project.
This operation requires permissions to perform the lookoutvision:DescribeProject
operation.
See also: AWS API Documentation
Request Syntax
response = client.describe_project(
ProjectName='string'
)
ProjectName (string) –
[REQUIRED]
The name of the project that you want to describe.
dict
Response Syntax
{
'ProjectDescription': {
'ProjectArn': 'string',
'ProjectName': 'string',
'CreationTimestamp': datetime(2015, 1, 1),
'Datasets': [
{
'DatasetType': 'string',
'CreationTimestamp': datetime(2015, 1, 1),
'Status': 'CREATE_IN_PROGRESS'|'CREATE_COMPLETE'|'CREATE_FAILED'|'UPDATE_IN_PROGRESS'|'UPDATE_COMPLETE'|'UPDATE_FAILED_ROLLBACK_IN_PROGRESS'|'UPDATE_FAILED_ROLLBACK_COMPLETE'|'DELETE_IN_PROGRESS'|'DELETE_COMPLETE'|'DELETE_FAILED',
'StatusMessage': 'string'
},
]
}
}
Response Structure
(dict) –
ProjectDescription (dict) –
The description of the project.
ProjectArn (string) –
The Amazon Resource Name (ARN) of the project.
ProjectName (string) –
The name of the project.
CreationTimestamp (datetime) –
The unix timestamp for the date and time that the project was created.
Datasets (list) –
A list of datasets in the project.
(dict) –
Sumary information for an Amazon Lookout for Vision dataset.
DatasetType (string) –
The type of the dataset.
CreationTimestamp (datetime) –
The Unix timestamp for the date and time that the dataset was created.
Status (string) –
The status for the dataset.
StatusMessage (string) –
The status message for the dataset.
Exceptions
detect_anomalies
(**kwargs)¶Detects 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.
Note
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.
This operation requires permissions to perform the lookoutvision:DetectAnomalies
operation.
See also: AWS API Documentation
Request Syntax
response = client.detect_anomalies(
ProjectName='string',
ModelVersion='string',
Body=b'bytes'|file,
ContentType='string'
)
ProjectName (string) –
[REQUIRED]
The name of the project that contains the model version that you want to use.
ModelVersion (string) –
[REQUIRED]
The version of the model that you want to use.
Body (bytes or seekable file-like object) –
[REQUIRED]
The unencrypted image bytes that you want to analyze.
ContentType (string) –
[REQUIRED]
The type of the image passed in Body
. Valid values are image/png
(PNG format images) and image/jpeg
(JPG format images).
dict
Response Syntax
{
'DetectAnomalyResult': {
'Source': {
'Type': 'string'
},
'IsAnomalous': True|False,
'Confidence': ...
}
}
Response Structure
(dict) –
DetectAnomalyResult (dict) –
The results of the DetectAnomalies
operation.
Source (dict) –
The source of the image that was analyzed. direct
means that the images was supplied from the local computer. No other values are supported.
Type (string) –
The type of the image.
IsAnomalous (boolean) –
True if the image contains an anomaly, otherwise false.
Confidence (float) –
The confidence that Amazon Lookout for Vision has in the accuracy of the prediction.
Exceptions
generate_presigned_url
(ClientMethod, Params=None, ExpiresIn=3600, HttpMethod=None)¶Generate a presigned url given a client, its method, and arguments
ClientMethod (string) – The client method to presign for
Params (dict) – The parameters normally passed to
ClientMethod
.
ExpiresIn (int) – The number of seconds the presigned url is valid for. By default it expires in an hour (3600 seconds)
HttpMethod (string) – The http method to use on the generated url. By default, the http method is whatever is used in the method’s model.
The presigned url
get_paginator
(operation_name)¶Create a paginator for an operation.
operation_name (string) – The operation name. This is the same name
as the method name on the client. For example, if the
method name is create_foo
, and you’d normally invoke the
operation as client.create_foo(**kwargs)
, if the
create_foo
operation can be paginated, you can use the
call client.get_paginator("create_foo")
.
OperationNotPageableError – Raised if the operation is not
pageable. You can use the client.can_paginate
method to
check if an operation is pageable.
L{botocore.paginate.Paginator}
A paginator object.
get_waiter
(waiter_name)¶Returns an object that can wait for some condition.
waiter_name (str) – The name of the waiter to get. See the waiters section of the service docs for a list of available waiters.
The specified waiter object.
botocore.waiter.Waiter
list_dataset_entries
(**kwargs)¶Lists 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 the lookoutvision:ListDatasetEntries
operation.
See also: AWS API Documentation
Request Syntax
response = client.list_dataset_entries(
ProjectName='string',
DatasetType='string',
Labeled=True|False,
AnomalyClass='string',
BeforeCreationDate=datetime(2015, 1, 1),
AfterCreationDate=datetime(2015, 1, 1),
NextToken='string',
MaxResults=123,
SourceRefContains='string'
)
ProjectName (string) –
[REQUIRED]
The name of the project that contains the dataset that you want to list.
DatasetType (string) –
[REQUIRED]
The type of the dataset that you want to list. Specify train
to list the training dataset. Specify test
to list the test dataset. If you have a single dataset project, specify train
.
Labeled (boolean) – Specify true
to include labeled entries, otherwise specify false
. If you don’t specify a value, Lookout for Vision returns all entries.
AnomalyClass (string) – Specify normal
to include only normal images. Specify anomaly
to only include anomalous entries. If you don’t specify a value, Amazon Lookout for Vision returns normal and anomalous images.
BeforeCreationDate (datetime) – Only includes entries before the specified date in the response. For example, 2020-06-23T00:00:00
.
AfterCreationDate (datetime) – Only includes entries after the specified date in the response. For example, 2020-06-23T00:00:00
.
NextToken (string) – If the previous response was incomplete (because there is more data to retrieve), Amazon Lookout for Vision returns a pagination token in the response. You can use this pagination token to retrieve the next set of dataset entries.
MaxResults (integer) – The maximum number of results to return per paginated call. The largest value you can specify is 100. If you specify a value greater than 100, a ValidationException error occurs. The default value is 100.
SourceRefContains (string) – Perform a “contains” search on the values of the source-ref
key within the dataset. For example a value of “IMG_17” returns all JSON Lines where the source-ref
key value matches IMG_17 .
dict
Response Syntax
{
'DatasetEntries': [
'string',
],
'NextToken': 'string'
}
Response Structure
(dict) –
DatasetEntries (list) –
A list of the entries (JSON Lines) within the dataset.
(string) –
NextToken (string) –
If the response is truncated, Amazon Lookout for Vision returns this token that you can use in the subsequent request to retrieve the next set ofdataset entries.
Exceptions
list_models
(**kwargs)¶Lists the versions of a model in an Amazon Lookout for Vision project.
This operation requires permissions to perform the lookoutvision:ListModels
operation.
See also: AWS API Documentation
Request Syntax
response = client.list_models(
ProjectName='string',
NextToken='string',
MaxResults=123
)
ProjectName (string) –
[REQUIRED]
The name of the project that contains the model versions that you want to list.
NextToken (string) – If the previous response was incomplete (because there is more data to retrieve), Amazon Lookout for Vision returns a pagination token in the response. You can use this pagination token to retrieve the next set of models.
MaxResults (integer) – The maximum number of results to return per paginated call. The largest value you can specify is 100. If you specify a value greater than 100, a ValidationException error occurs. The default value is 100.
dict
Response Syntax
{
'Models': [
{
'CreationTimestamp': datetime(2015, 1, 1),
'ModelVersion': 'string',
'ModelArn': 'string',
'Description': 'string',
'Status': 'TRAINING'|'TRAINED'|'TRAINING_FAILED'|'STARTING_HOSTING'|'HOSTED'|'HOSTING_FAILED'|'STOPPING_HOSTING'|'SYSTEM_UPDATING'|'DELETING',
'StatusMessage': 'string',
'Performance': {
'F1Score': ...,
'Recall': ...,
'Precision': ...
}
},
],
'NextToken': 'string'
}
Response Structure
(dict) –
Models (list) –
A list of model versions in the specified project.
(dict) –
Describes an Amazon Lookout for Vision model.
CreationTimestamp (datetime) –
The unix timestamp for the date and time that the model was created.
ModelVersion (string) –
The version of the model.
ModelArn (string) –
The Amazon Resource Name (ARN) of the model.
Description (string) –
The description for the model.
Status (string) –
The status of the model.
StatusMessage (string) –
The status message for the model.
Performance (dict) –
Performance metrics for the model. Not available until training has successfully completed.
F1Score (float) –
The overall F1 score metric for the trained model.
Recall (float) –
The overall recall metric value for the trained model.
Precision (float) –
The overall precision metric value for the trained model.
NextToken (string) –
If the response is truncated, Amazon Lookout for Vision returns this token that you can use in the subsequent request to retrieve the next set of models.
Exceptions
list_projects
(**kwargs)¶Lists the Amazon Lookout for Vision projects in your AWS account.
This operation requires permissions to perform the lookoutvision:ListProjects
operation.
See also: AWS API Documentation
Request Syntax
response = client.list_projects(
NextToken='string',
MaxResults=123
)
NextToken (string) – If the previous response was incomplete (because there is more data to retrieve), Amazon Lookout for Vision returns a pagination token in the response. You can use this pagination token to retrieve the next set of projects.
MaxResults (integer) – The maximum number of results to return per paginated call. The largest value you can specify is 100. If you specify a value greater than 100, a ValidationException error occurs. The default value is 100.
dict
Response Syntax
{
'Projects': [
{
'ProjectArn': 'string',
'ProjectName': 'string',
'CreationTimestamp': datetime(2015, 1, 1)
},
],
'NextToken': 'string'
}
Response Structure
(dict) –
Projects (list) –
A list of projects in your AWS account.
(dict) –
Metadata about an Amazon Lookout for Vision project.
ProjectArn (string) –
The Amazon Resource Name (ARN) of the project.
ProjectName (string) –
The name of the project.
CreationTimestamp (datetime) –
The unix timestamp for the date and time that the project was created.
NextToken (string) –
If the response is truncated, Amazon Lookout for Vision returns this token that you can use in the subsequent request to retrieve the next set of projects.
Exceptions
Returns a list of tags attached to the specified Amazon Lookout for Vision model.
This operation requires permissions to perform the lookoutvision:ListTagsForResource
operation.
See also: AWS API Documentation
Request Syntax
response = client.list_tags_for_resource(
ResourceArn='string'
)
ResourceArn (string) –
[REQUIRED]
The Amazon Resource Name (ARN) of the model for which you want to list tags.
dict
Response Syntax
{
'Tags': [
{
'Key': 'string',
'Value': 'string'
},
]
}
Response Structure
(dict) –
Tags (list) –
A map of tag keys and values attached to the specified model.
(dict) –
A key and value pair that is attached to the specified Amazon Lookout for Vision model.
Key (string) –
The key of the tag that is attached to the specified model.
Value (string) –
The value of the tag that is attached to the specified model.
Exceptions
start_model
(**kwargs)¶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 .
Once the model is running, you can detect custom labels in new images by calling DetectAnomalies .
Note
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
Request Syntax
response = client.start_model(
ProjectName='string',
ModelVersion='string',
MinInferenceUnits=123,
ClientToken='string'
)
ProjectName (string) –
[REQUIRED]
The name of the project that contains the model that you want to start.
ModelVersion (string) –
[REQUIRED]
The version of the model that you want to start.
MinInferenceUnits (integer) –
[REQUIRED]
The minimum number of inference units to use. A single inference unit represents 1 hour of processing and can support up to 5 Transaction Pers Second (TPS). Use a higher number to increase the TPS throughput of your model. You are charged for the number of inference units that you use.
ClientToken (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, such as an network outage, 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. 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.
This field is autopopulated if not provided.
dict
Response Syntax
{
'Status': 'RUNNING'|'STARTING'|'STOPPED'|'FAILED'
}
Response Structure
(dict) –
Status (string) –
The current running status of the model.
Exceptions
stop_model
(**kwargs)¶Stops a running model. The operation might take a while to complete. To check the current status, call DescribeModel .
This operation requires permissions to perform the lookoutvision:StopModel
operation.
See also: AWS API Documentation
Request Syntax
response = client.stop_model(
ProjectName='string',
ModelVersion='string',
ClientToken='string'
)
ProjectName (string) –
[REQUIRED]
The name of the project that contains the model that you want to stop.
ModelVersion (string) –
[REQUIRED]
The version of the model that you want to stop.
ClientToken (string) –
ClientToken is an idempotency token that ensures a call to StopModel
completes only once. You choose the value to pass. For example, An issue, such as an network outage, might prevent you from getting a response from StopModel
. In this case, safely retry your call to StopModel
by using the same ClientToken
parameter value. 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 StopModel
. An idempotency token is active for 8 hours.
This field is autopopulated if not provided.
dict
Response Syntax
{
'Status': 'RUNNING'|'STARTING'|'STOPPED'|'FAILED'
}
Response Structure
(dict) –
Status (string) –
The status of the model.
Exceptions
tag_resource
(**kwargs)¶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 the lookoutvision:TagResource
operation.
See also: AWS API Documentation
Request Syntax
response = client.tag_resource(
ResourceArn='string',
Tags=[
{
'Key': 'string',
'Value': 'string'
},
]
)
ResourceArn (string) –
[REQUIRED]
The Amazon Resource Name (ARN) of the model to assign the tags.
Tags (list) –
[REQUIRED]
The key-value tags to assign to the model.
(dict) –
A key and value pair that is attached to the specified Amazon Lookout for Vision model.
Key (string) – [REQUIRED]
The key of the tag that is attached to the specified model.
Value (string) – [REQUIRED]
The value of the tag that is attached to the specified model.
dict
Response Syntax
{}
Response Structure
(dict) –
Exceptions
untag_resource
(**kwargs)¶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 the lookoutvision:UntagResource
operation.
See also: AWS API Documentation
Request Syntax
response = client.untag_resource(
ResourceArn='string',
TagKeys=[
'string',
]
)
ResourceArn (string) –
[REQUIRED]
The Amazon Resource Name (ARN) of the model from which you want to remove tags.
TagKeys (list) –
[REQUIRED]
A list of the keys of the tags that you want to remove.
(string) –
dict
Response Syntax
{}
Response Structure
(dict) –
Exceptions
update_dataset_entries
(**kwargs)¶Adds one or more JSON Line entries to a dataset. A JSON Line includes information about an image used for training or testing an Amazon Lookout for Vision model. The following is an example JSON Line.
Updating a dataset might take a while to complete. To check the current status, call DescribeDataset and check the Status
field in the response.
This operation requires permissions to perform the lookoutvision:UpdateDatasetEntries
operation.
See also: AWS API Documentation
Request Syntax
response = client.update_dataset_entries(
ProjectName='string',
DatasetType='string',
Changes=b'bytes',
ClientToken='string'
)
ProjectName (string) –
[REQUIRED]
The name of the project that contains the dataset that you want to update.
DatasetType (string) –
[REQUIRED]
The type of the dataset that you want to update. Specify train
to update the training dataset. Specify test
to update the test dataset. If you have a single dataset project, specify train
.
Changes (bytes) –
[REQUIRED]
The entries to add to the dataset.
ClientToken (string) –
ClientToken is an idempotency token that ensures a call to UpdateDatasetEntries
completes only once. You choose the value to pass. For example, An issue, such as an network outage, might prevent you from getting a response from UpdateDatasetEntries
. In this case, safely retry your call to UpdateDatasetEntries
by using the same ClientToken
parameter value. 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 UpdateDatasetEntries
. An idempotency token is active for 8 hours.
This field is autopopulated if not provided.
dict
Response Syntax
{
'Status': 'CREATE_IN_PROGRESS'|'CREATE_COMPLETE'|'CREATE_FAILED'|'UPDATE_IN_PROGRESS'|'UPDATE_COMPLETE'|'UPDATE_FAILED_ROLLBACK_IN_PROGRESS'|'UPDATE_FAILED_ROLLBACK_COMPLETE'|'DELETE_IN_PROGRESS'|'DELETE_COMPLETE'|'DELETE_FAILED'
}
Response Structure
(dict) –
Status (string) –
The status of the dataset update.
Exceptions
Client exceptions are available on a client instance via the exceptions
property. For more detailed instructions and examples on the exact usage of client exceptions, see the error handling user guide.
The available client exceptions are:
LookoutforVision.Client.exceptions.ResourceNotFoundException
LookoutforVision.Client.exceptions.ServiceQuotaExceededException
LookoutforVision.Client.exceptions.
AccessDeniedException
¶You are not authorized to perform the action.
Example
try:
...
except client.exceptions.AccessDeniedException as e:
print(e.response)
response
¶The parsed error response. All exceptions have a top level Error
key that provides normalized access to common exception atrributes. All other keys are specific to this service or exception class.
Syntax
{
'Message': 'string',
'Error': {
'Code': 'string',
'Message': 'string'
}
}
Structure
(dict) –
You are not authorized to perform the action.
Message (string) –
Error (dict) – Normalized access to common exception attributes.
Code (string) – An identifier specifying the exception type.
Message (string) – A descriptive message explaining why the exception occured.
LookoutforVision.Client.exceptions.
ConflictException
¶The update or deletion of a resource caused an inconsistent state.
Example
try:
...
except client.exceptions.ConflictException as e:
print(e.response)
response
¶The parsed error response. All exceptions have a top level Error
key that provides normalized access to common exception atrributes. All other keys are specific to this service or exception class.
Syntax
{
'Message': 'string',
'ResourceId': 'string',
'ResourceType': 'PROJECT'|'DATASET'|'MODEL'|'TRIAL',
'Error': {
'Code': 'string',
'Message': 'string'
}
}
Structure
(dict) –
The update or deletion of a resource caused an inconsistent state.
Message (string) –
ResourceId (string) –
The ID of the resource.
ResourceType (string) –
The type of the resource.
Error (dict) – Normalized access to common exception attributes.
Code (string) – An identifier specifying the exception type.
Message (string) – A descriptive message explaining why the exception occured.
LookoutforVision.Client.exceptions.
InternalServerException
¶Amazon Lookout for Vision experienced a service issue. Try your call again.
Example
try:
...
except client.exceptions.InternalServerException as e:
print(e.response)
response
¶The parsed error response. All exceptions have a top level Error
key that provides normalized access to common exception atrributes. All other keys are specific to this service or exception class.
Syntax
{
'Message': 'string',
'RetryAfterSeconds': 123,
'Error': {
'Code': 'string',
'Message': 'string'
}
}
Structure
(dict) –
Amazon Lookout for Vision experienced a service issue. Try your call again.
Message (string) –
RetryAfterSeconds (integer) –
The period of time, in seconds, before the operation can be retried.
Error (dict) – Normalized access to common exception attributes.
Code (string) – An identifier specifying the exception type.
Message (string) – A descriptive message explaining why the exception occured.
LookoutforVision.Client.exceptions.
ResourceNotFoundException
¶The resource could not be found.
Example
try:
...
except client.exceptions.ResourceNotFoundException as e:
print(e.response)
response
¶The parsed error response. All exceptions have a top level Error
key that provides normalized access to common exception atrributes. All other keys are specific to this service or exception class.
Syntax
{
'Message': 'string',
'ResourceId': 'string',
'ResourceType': 'PROJECT'|'DATASET'|'MODEL'|'TRIAL',
'Error': {
'Code': 'string',
'Message': 'string'
}
}
Structure
(dict) –
The resource could not be found.
Message (string) –
ResourceId (string) –
The ID of the resource.
ResourceType (string) –
The type of the resource.
Error (dict) – Normalized access to common exception attributes.
Code (string) – An identifier specifying the exception type.
Message (string) – A descriptive message explaining why the exception occured.
LookoutforVision.Client.exceptions.
ServiceQuotaExceededException
¶A service quota was exceeded the allowed limit. For more information, see Limits in Amazon Lookout for Vision in the Amazon Lookout for Vision Developer Guide.
Example
try:
...
except client.exceptions.ServiceQuotaExceededException as e:
print(e.response)
response
¶The parsed error response. All exceptions have a top level Error
key that provides normalized access to common exception atrributes. All other keys are specific to this service or exception class.
Syntax
{
'Message': 'string',
'ResourceId': 'string',
'ResourceType': 'PROJECT'|'DATASET'|'MODEL'|'TRIAL',
'QuotaCode': 'string',
'ServiceCode': 'string',
'Error': {
'Code': 'string',
'Message': 'string'
}
}
Structure
(dict) –
A service quota was exceeded the allowed limit. For more information, see Limits in Amazon Lookout for Vision in the Amazon Lookout for Vision Developer Guide.
Message (string) –
ResourceId (string) –
The ID of the resource.
ResourceType (string) –
The type of the resource.
QuotaCode (string) –
The quota code.
ServiceCode (string) –
The service code.
Error (dict) – Normalized access to common exception attributes.
Code (string) – An identifier specifying the exception type.
Message (string) – A descriptive message explaining why the exception occured.
LookoutforVision.Client.exceptions.
ThrottlingException
¶Amazon Lookout for Vision is temporarily unable to process the request. Try your call again.
Example
try:
...
except client.exceptions.ThrottlingException as e:
print(e.response)
response
¶The parsed error response. All exceptions have a top level Error
key that provides normalized access to common exception atrributes. All other keys are specific to this service or exception class.
Syntax
{
'Message': 'string',
'QuotaCode': 'string',
'ServiceCode': 'string',
'RetryAfterSeconds': 123,
'Error': {
'Code': 'string',
'Message': 'string'
}
}
Structure
(dict) –
Amazon Lookout for Vision is temporarily unable to process the request. Try your call again.
Message (string) –
QuotaCode (string) –
The quota code.
ServiceCode (string) –
The service code.
RetryAfterSeconds (integer) –
The period of time, in seconds, before the operation can be retried.
Error (dict) – Normalized access to common exception attributes.
Code (string) – An identifier specifying the exception type.
Message (string) – A descriptive message explaining why the exception occured.
LookoutforVision.Client.exceptions.
ValidationException
¶An input validation error occured. For example, invalid characters in a project name, or if a pagination token is invalid.
Example
try:
...
except client.exceptions.ValidationException as e:
print(e.response)
response
¶The parsed error response. All exceptions have a top level Error
key that provides normalized access to common exception atrributes. All other keys are specific to this service or exception class.
Syntax
{
'Message': 'string',
'Error': {
'Code': 'string',
'Message': 'string'
}
}
Structure
(dict) –
An input validation error occured. For example, invalid characters in a project name, or if a pagination token is invalid.
Message (string) –
Error (dict) – Normalized access to common exception attributes.
Code (string) – An identifier specifying the exception type.
Message (string) – A descriptive message explaining why the exception occured.
The available paginators are:
LookoutforVision.Paginator.
ListDatasetEntries
¶paginator = client.get_paginator('list_dataset_entries')
paginate
(**kwargs)¶Creates an iterator that will paginate through responses from LookoutforVision.Client.list_dataset_entries()
.
See also: AWS API Documentation
Request Syntax
response_iterator = paginator.paginate(
ProjectName='string',
DatasetType='string',
Labeled=True|False,
AnomalyClass='string',
BeforeCreationDate=datetime(2015, 1, 1),
AfterCreationDate=datetime(2015, 1, 1),
SourceRefContains='string',
PaginationConfig={
'MaxItems': 123,
'PageSize': 123,
'StartingToken': 'string'
}
)
ProjectName (string) –
[REQUIRED]
The name of the project that contains the dataset that you want to list.
DatasetType (string) –
[REQUIRED]
The type of the dataset that you want to list. Specify train
to list the training dataset. Specify test
to list the test dataset. If you have a single dataset project, specify train
.
Labeled (boolean) – Specify true
to include labeled entries, otherwise specify false
. If you don’t specify a value, Lookout for Vision returns all entries.
AnomalyClass (string) – Specify normal
to include only normal images. Specify anomaly
to only include anomalous entries. If you don’t specify a value, Amazon Lookout for Vision returns normal and anomalous images.
BeforeCreationDate (datetime) – Only includes entries before the specified date in the response. For example, 2020-06-23T00:00:00
.
AfterCreationDate (datetime) – Only includes entries after the specified date in the response. For example, 2020-06-23T00:00:00
.
SourceRefContains (string) – Perform a “contains” search on the values of the source-ref
key within the dataset. For example a value of “IMG_17” returns all JSON Lines where the source-ref
key value matches IMG_17 .
PaginationConfig (dict) –
A dictionary that provides parameters to control pagination.
MaxItems (integer) –
The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken
will be provided in the output that you can use to resume pagination.
PageSize (integer) –
The size of each page.
StartingToken (string) –
A token to specify where to start paginating. This is the NextToken
from a previous response.
dict
Response Syntax
{
'DatasetEntries': [
'string',
],
}
Response Structure
(dict) –
DatasetEntries (list) –
A list of the entries (JSON Lines) within the dataset.
(string) –
LookoutforVision.Paginator.
ListModels
¶paginator = client.get_paginator('list_models')
paginate
(**kwargs)¶Creates an iterator that will paginate through responses from LookoutforVision.Client.list_models()
.
See also: AWS API Documentation
Request Syntax
response_iterator = paginator.paginate(
ProjectName='string',
PaginationConfig={
'MaxItems': 123,
'PageSize': 123,
'StartingToken': 'string'
}
)
ProjectName (string) –
[REQUIRED]
The name of the project that contains the model versions that you want to list.
PaginationConfig (dict) –
A dictionary that provides parameters to control pagination.
MaxItems (integer) –
The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken
will be provided in the output that you can use to resume pagination.
PageSize (integer) –
The size of each page.
StartingToken (string) –
A token to specify where to start paginating. This is the NextToken
from a previous response.
dict
Response Syntax
{
'Models': [
{
'CreationTimestamp': datetime(2015, 1, 1),
'ModelVersion': 'string',
'ModelArn': 'string',
'Description': 'string',
'Status': 'TRAINING'|'TRAINED'|'TRAINING_FAILED'|'STARTING_HOSTING'|'HOSTED'|'HOSTING_FAILED'|'STOPPING_HOSTING'|'SYSTEM_UPDATING'|'DELETING',
'StatusMessage': 'string',
'Performance': {
'F1Score': ...,
'Recall': ...,
'Precision': ...
}
},
],
}
Response Structure
(dict) –
Models (list) –
A list of model versions in the specified project.
(dict) –
Describes an Amazon Lookout for Vision model.
CreationTimestamp (datetime) –
The unix timestamp for the date and time that the model was created.
ModelVersion (string) –
The version of the model.
ModelArn (string) –
The Amazon Resource Name (ARN) of the model.
Description (string) –
The description for the model.
Status (string) –
The status of the model.
StatusMessage (string) –
The status message for the model.
Performance (dict) –
Performance metrics for the model. Not available until training has successfully completed.
F1Score (float) –
The overall F1 score metric for the trained model.
Recall (float) –
The overall recall metric value for the trained model.
Precision (float) –
The overall precision metric value for the trained model.
LookoutforVision.Paginator.
ListProjects
¶paginator = client.get_paginator('list_projects')
paginate
(**kwargs)¶Creates an iterator that will paginate through responses from LookoutforVision.Client.list_projects()
.
See also: AWS API Documentation
Request Syntax
response_iterator = paginator.paginate(
PaginationConfig={
'MaxItems': 123,
'PageSize': 123,
'StartingToken': 'string'
}
)
PaginationConfig (dict) –
A dictionary that provides parameters to control pagination.
MaxItems (integer) –
The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken
will be provided in the output that you can use to resume pagination.
PageSize (integer) –
The size of each page.
StartingToken (string) –
A token to specify where to start paginating. This is the NextToken
from a previous response.
dict
Response Syntax
{
'Projects': [
{
'ProjectArn': 'string',
'ProjectName': 'string',
'CreationTimestamp': datetime(2015, 1, 1)
},
],
}
Response Structure
(dict) –
Projects (list) –
A list of projects in your AWS account.
(dict) –
Metadata about an Amazon Lookout for Vision project.
ProjectArn (string) –
The Amazon Resource Name (ARN) of the project.
ProjectName (string) –
The name of the project.
CreationTimestamp (datetime) –
The unix timestamp for the date and time that the project was created.