Rekognition / Client / describe_project_versions

describe_project_versions#

Rekognition.Client.describe_project_versions(**kwargs)#

Lists and describes the versions of an Amazon Rekognition project. You can specify up to 10 model or adapter versions in ProjectVersionArns. If you don’t specify a value, descriptions for all model/adapter versions in the project are returned.

This operation requires permissions to perform the rekognition:DescribeProjectVersions action.

See also: AWS API Documentation

Request Syntax

response = client.describe_project_versions(
    ProjectArn='string',
    VersionNames=[
        'string',
    ],
    NextToken='string',
    MaxResults=123
)
Parameters:

  • ProjectArn (string) –

    [REQUIRED]

    The Amazon Resource Name (ARN) of the project that contains the model/adapter you want to describe.

  • VersionNames (list) –

    A list of model or project version names that you want to describe. You can add up to 10 model or project version names to the list. If you don’t specify a value, all project version descriptions are returned. A version name is part of a project version ARN. For example, my-model.2020-01-21T09.10.15 is the version name in the following ARN. arn:aws:rekognition:us-east-1:123456789012:project/getting-started/version/my-model.2020-01-21T09.10.15/1234567890123.

    • (string) –

  • NextToken (string) – If the previous response was incomplete (because there is more results to retrieve), Amazon Rekognition returns a pagination token in the response. You can use this pagination token to retrieve the next set of results.

  • 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.

Return type:

dict

Returns:

Response Syntax

{
    'ProjectVersionDescriptions': [
        {
            'ProjectVersionArn': 'string',
            'CreationTimestamp': datetime(2015, 1, 1),
            'MinInferenceUnits': 123,
            'Status': 'TRAINING_IN_PROGRESS'|'TRAINING_COMPLETED'|'TRAINING_FAILED'|'STARTING'|'RUNNING'|'FAILED'|'STOPPING'|'STOPPED'|'DELETING'|'COPYING_IN_PROGRESS'|'COPYING_COMPLETED'|'COPYING_FAILED'|'DEPRECATED'|'EXPIRED',
            'StatusMessage': 'string',
            'BillableTrainingTimeInSeconds': 123,
            'TrainingEndTimestamp': datetime(2015, 1, 1),
            'OutputConfig': {
                'S3Bucket': 'string',
                'S3KeyPrefix': 'string'
            },
            'TrainingDataResult': {
                'Input': {
                    'Assets': [
                        {
                            'GroundTruthManifest': {
                                'S3Object': {
                                    'Bucket': 'string',
                                    'Name': 'string',
                                    'Version': 'string'
                                }
                            }
                        },
                    ]
                },
                'Output': {
                    'Assets': [
                        {
                            'GroundTruthManifest': {
                                'S3Object': {
                                    'Bucket': 'string',
                                    'Name': 'string',
                                    'Version': 'string'
                                }
                            }
                        },
                    ]
                },
                'Validation': {
                    'Assets': [
                        {
                            'GroundTruthManifest': {
                                'S3Object': {
                                    'Bucket': 'string',
                                    'Name': 'string',
                                    'Version': 'string'
                                }
                            }
                        },
                    ]
                }
            },
            'TestingDataResult': {
                'Input': {
                    'Assets': [
                        {
                            'GroundTruthManifest': {
                                'S3Object': {
                                    'Bucket': 'string',
                                    'Name': 'string',
                                    'Version': 'string'
                                }
                            }
                        },
                    ],
                    'AutoCreate': True|False
                },
                'Output': {
                    'Assets': [
                        {
                            'GroundTruthManifest': {
                                'S3Object': {
                                    'Bucket': 'string',
                                    'Name': 'string',
                                    'Version': 'string'
                                }
                            }
                        },
                    ],
                    'AutoCreate': True|False
                },
                'Validation': {
                    'Assets': [
                        {
                            'GroundTruthManifest': {
                                'S3Object': {
                                    'Bucket': 'string',
                                    'Name': 'string',
                                    'Version': 'string'
                                }
                            }
                        },
                    ]
                }
            },
            'EvaluationResult': {
                'F1Score': ...,
                'Summary': {
                    'S3Object': {
                        'Bucket': 'string',
                        'Name': 'string',
                        'Version': 'string'
                    }
                }
            },
            'ManifestSummary': {
                'S3Object': {
                    'Bucket': 'string',
                    'Name': 'string',
                    'Version': 'string'
                }
            },
            'KmsKeyId': 'string',
            'MaxInferenceUnits': 123,
            'SourceProjectVersionArn': 'string',
            'VersionDescription': 'string',
            'Feature': 'CONTENT_MODERATION'|'CUSTOM_LABELS',
            'BaseModelVersion': 'string',
            'FeatureConfig': {
                'ContentModeration': {
                    'ConfidenceThreshold': ...
                }
            }
        },
    ],
    'NextToken': 'string'
}

Response Structure

  • (dict) –

    • ProjectVersionDescriptions (list) –

      A list of project version descriptions. The list is sorted by the creation date and time of the project versions, latest to earliest.

      • (dict) –

        A description of a version of a Amazon Rekognition project version.

        • ProjectVersionArn (string) –

          The Amazon Resource Name (ARN) of the project version.

        • CreationTimestamp (datetime) –

          The Unix datetime for the date and time that training started.

        • MinInferenceUnits (integer) –

          The minimum number of inference units used by the model. Applies only to Custom Labels projects. For more information, see StartProjectVersion.

        • Status (string) –

          The current status of the model version.

        • StatusMessage (string) –

          A descriptive message for an error or warning that occurred.

        • BillableTrainingTimeInSeconds (integer) –

          The duration, in seconds, that you were billed for a successful training of the model version. This value is only returned if the model version has been successfully trained.

        • TrainingEndTimestamp (datetime) –

          The Unix date and time that training of the model ended.

        • OutputConfig (dict) –

          The location where training results are saved.

          • S3Bucket (string) –

            The S3 bucket where training output is placed.

          • S3KeyPrefix (string) –

            The prefix applied to the training output files.

        • TrainingDataResult (dict) –

          Contains information about the training results.

          • Input (dict) –

            The training data that you supplied.

            • Assets (list) –

              A manifest file that contains references to the training images and ground-truth annotations.

              • (dict) –

                Assets are the images that you use to train and evaluate a model version. Assets can also contain validation information that you use to debug a failed model training.

                • GroundTruthManifest (dict) –

                  The S3 bucket that contains an Amazon Sagemaker Ground Truth format manifest file.

                  • S3Object (dict) –

                    Provides the S3 bucket name and object name.

                    The region for the S3 bucket containing the S3 object must match the region you use for Amazon Rekognition operations.

                    For Amazon Rekognition to process an S3 object, the user must have permission to access the S3 object. For more information, see How Amazon Rekognition works with IAM in the Amazon Rekognition Developer Guide.

                    • Bucket (string) –

                      Name of the S3 bucket.

                    • Name (string) –

                      S3 object key name.

                    • Version (string) –

                      If the bucket is versioning enabled, you can specify the object version.

          • Output (dict) –

            Reference to images (assets) that were actually used during training with trained model predictions.

            • Assets (list) –

              A manifest file that contains references to the training images and ground-truth annotations.

              • (dict) –

                Assets are the images that you use to train and evaluate a model version. Assets can also contain validation information that you use to debug a failed model training.

                • GroundTruthManifest (dict) –

                  The S3 bucket that contains an Amazon Sagemaker Ground Truth format manifest file.

                  • S3Object (dict) –

                    Provides the S3 bucket name and object name.

                    The region for the S3 bucket containing the S3 object must match the region you use for Amazon Rekognition operations.

                    For Amazon Rekognition to process an S3 object, the user must have permission to access the S3 object. For more information, see How Amazon Rekognition works with IAM in the Amazon Rekognition Developer Guide.

                    • Bucket (string) –

                      Name of the S3 bucket.

                    • Name (string) –

                      S3 object key name.

                    • Version (string) –

                      If the bucket is versioning enabled, you can specify the object version.

          • Validation (dict) –

            A manifest that you supplied for training, with validation results for each line.

            • Assets (list) –

              The assets that comprise the validation data.

              • (dict) –

                Assets are the images that you use to train and evaluate a model version. Assets can also contain validation information that you use to debug a failed model training.

                • GroundTruthManifest (dict) –

                  The S3 bucket that contains an Amazon Sagemaker Ground Truth format manifest file.

                  • S3Object (dict) –

                    Provides the S3 bucket name and object name.

                    The region for the S3 bucket containing the S3 object must match the region you use for Amazon Rekognition operations.

                    For Amazon Rekognition to process an S3 object, the user must have permission to access the S3 object. For more information, see How Amazon Rekognition works with IAM in the Amazon Rekognition Developer Guide.

                    • Bucket (string) –

                      Name of the S3 bucket.

                    • Name (string) –

                      S3 object key name.

                    • Version (string) –

                      If the bucket is versioning enabled, you can specify the object version.

        • TestingDataResult (dict) –

          Contains information about the testing results.

          • Input (dict) –

            The testing dataset that was supplied for training.

            • Assets (list) –

              The assets used for testing.

              • (dict) –

                Assets are the images that you use to train and evaluate a model version. Assets can also contain validation information that you use to debug a failed model training.

                • GroundTruthManifest (dict) –

                  The S3 bucket that contains an Amazon Sagemaker Ground Truth format manifest file.

                  • S3Object (dict) –

                    Provides the S3 bucket name and object name.

                    The region for the S3 bucket containing the S3 object must match the region you use for Amazon Rekognition operations.

                    For Amazon Rekognition to process an S3 object, the user must have permission to access the S3 object. For more information, see How Amazon Rekognition works with IAM in the Amazon Rekognition Developer Guide.

                    • Bucket (string) –

                      Name of the S3 bucket.

                    • Name (string) –

                      S3 object key name.

                    • Version (string) –

                      If the bucket is versioning enabled, you can specify the object version.

            • AutoCreate (boolean) –

              If specified, Rekognition splits training dataset to create a test dataset for the training job.

          • Output (dict) –

            The subset of the dataset that was actually tested. Some images (assets) might not be tested due to file formatting and other issues.

            • Assets (list) –

              The assets used for testing.

              • (dict) –

                Assets are the images that you use to train and evaluate a model version. Assets can also contain validation information that you use to debug a failed model training.

                • GroundTruthManifest (dict) –

                  The S3 bucket that contains an Amazon Sagemaker Ground Truth format manifest file.

                  • S3Object (dict) –

                    Provides the S3 bucket name and object name.

                    The region for the S3 bucket containing the S3 object must match the region you use for Amazon Rekognition operations.

                    For Amazon Rekognition to process an S3 object, the user must have permission to access the S3 object. For more information, see How Amazon Rekognition works with IAM in the Amazon Rekognition Developer Guide.

                    • Bucket (string) –

                      Name of the S3 bucket.

                    • Name (string) –

                      S3 object key name.

                    • Version (string) –

                      If the bucket is versioning enabled, you can specify the object version.

            • AutoCreate (boolean) –

              If specified, Rekognition splits training dataset to create a test dataset for the training job.

          • Validation (dict) –

            The location of the data validation manifest. The data validation manifest is created for the test dataset during model training.

            • Assets (list) –

              The assets that comprise the validation data.

              • (dict) –

                Assets are the images that you use to train and evaluate a model version. Assets can also contain validation information that you use to debug a failed model training.

                • GroundTruthManifest (dict) –

                  The S3 bucket that contains an Amazon Sagemaker Ground Truth format manifest file.

                  • S3Object (dict) –

                    Provides the S3 bucket name and object name.

                    The region for the S3 bucket containing the S3 object must match the region you use for Amazon Rekognition operations.

                    For Amazon Rekognition to process an S3 object, the user must have permission to access the S3 object. For more information, see How Amazon Rekognition works with IAM in the Amazon Rekognition Developer Guide.

                    • Bucket (string) –

                      Name of the S3 bucket.

                    • Name (string) –

                      S3 object key name.

                    • Version (string) –

                      If the bucket is versioning enabled, you can specify the object version.

        • EvaluationResult (dict) –

          The training results. EvaluationResult is only returned if training is successful.

          • F1Score (float) –

            The F1 score for the evaluation of all labels. The F1 score metric evaluates the overall precision and recall performance of the model as a single value. A higher value indicates better precision and recall performance. A lower score indicates that precision, recall, or both are performing poorly.

          • Summary (dict) –

            The S3 bucket that contains the training summary.

            • S3Object (dict) –

              Provides the S3 bucket name and object name.

              The region for the S3 bucket containing the S3 object must match the region you use for Amazon Rekognition operations.

              For Amazon Rekognition to process an S3 object, the user must have permission to access the S3 object. For more information, see How Amazon Rekognition works with IAM in the Amazon Rekognition Developer Guide.

              • Bucket (string) –

                Name of the S3 bucket.

              • Name (string) –

                S3 object key name.

              • Version (string) –

                If the bucket is versioning enabled, you can specify the object version.

        • ManifestSummary (dict) –

          The location of the summary manifest. The summary manifest provides aggregate data validation results for the training and test datasets.

          • S3Object (dict) –

            Provides the S3 bucket name and object name.

            The region for the S3 bucket containing the S3 object must match the region you use for Amazon Rekognition operations.

            For Amazon Rekognition to process an S3 object, the user must have permission to access the S3 object. For more information, see How Amazon Rekognition works with IAM in the Amazon Rekognition Developer Guide.

            • Bucket (string) –

              Name of the S3 bucket.

            • Name (string) –

              S3 object key name.

            • Version (string) –

              If the bucket is versioning enabled, you can specify the object version.

        • KmsKeyId (string) –

          The identifer for the AWS Key Management Service key (AWS KMS key) that was used to encrypt the model during training.

        • MaxInferenceUnits (integer) –

          The maximum number of inference units Amazon Rekognition uses to auto-scale the model. Applies only to Custom Labels projects. For more information, see StartProjectVersion.

        • SourceProjectVersionArn (string) –

          If the model version was copied from a different project, SourceProjectVersionArn contains the ARN of the source model version.

        • VersionDescription (string) –

          A user-provided description of the project version.

        • Feature (string) –

          The feature that was customized.

        • BaseModelVersion (string) –

          The base detection model version used to create the project version.

        • FeatureConfig (dict) –

          Feature specific configuration that was applied during training.

          • ContentModeration (dict) –

            Configuration options for Custom Moderation training.

            • ConfidenceThreshold (float) –

              The confidence level you plan to use to identify if unsafe content is present during inference.

    • NextToken (string) –

      If the previous response was incomplete (because there is more results to retrieve), Amazon Rekognition returns a pagination token in the response. You can use this pagination token to retrieve the next set of results.

Exceptions