Create Project Version
rekognition_create_project_version | R Documentation |
Creates a new version of Amazon Rekognition project (like a Custom Labels model or a custom adapter) and begins training¶
Description¶
Creates a new version of Amazon Rekognition project (like a Custom
Labels model or a custom adapter) and begins training. Models and
adapters are managed as part of a Rekognition project. The response from
create_project_version
is an Amazon Resource Name (ARN) for the
project version.
The FeatureConfig operation argument allows you to configure specific
model or adapter settings. You can provide a description to the project
version by using the VersionDescription argment. Training can take a
while to complete. You can get the current status by calling
describe_project_versions
. Training completed successfully if the
value of the Status
field is TRAINING_COMPLETED
. Once training has
successfully completed, call describe_project_versions
to get the
training results and evaluate the model.
This operation requires permissions to perform the
rekognition:CreateProjectVersion
action.
The following applies only to projects with Amazon Rekognition Custom Labels as the chosen feature:
You can train a model in a project that doesn't have associated datasets
by specifying manifest files in the TrainingData
and TestingData
fields.
If you open the console after training a model with manifest files, Amazon Rekognition Custom Labels creates the datasets for you using the most recent manifest files. You can no longer train a model version for the project by specifying manifest files.
Instead of training with a project without associated datasets, we recommend that you use the manifest files to create training and test datasets for the project.
Usage¶
rekognition_create_project_version(ProjectArn, VersionName,
OutputConfig, TrainingData, TestingData, Tags, KmsKeyId,
VersionDescription, FeatureConfig)
Arguments¶
ProjectArn
[required] The ARN of the Amazon Rekognition project that will manage the project version you want to train.
VersionName
[required] A name for the version of the project version. This value must be unique.
OutputConfig
[required] The Amazon S3 bucket location to store the results of training. The bucket can be any S3 bucket in your AWS account. You need
s3:PutObject
permission on the bucket.TrainingData
Specifies an external manifest that the services uses to train the project version. If you specify
TrainingData
you must also specifyTestingData
. The project must not have any associated datasets.TestingData
Specifies an external manifest that the service uses to test the project version. If you specify
TestingData
you must also specifyTrainingData
. The project must not have any associated datasets.Tags
A set of tags (key-value pairs) that you want to attach to the project version.
KmsKeyId
The identifier for your AWS Key Management Service key (AWS KMS key). You can supply the Amazon Resource Name (ARN) of your KMS key, the ID of your KMS key, an alias for your KMS key, or an alias ARN. The key is used to encrypt training images, test images, and manifest files copied into the service for the project version. Your source images are unaffected. The key is also used to encrypt training results and manifest files written to the output Amazon S3 bucket (
OutputConfig
).If you choose to use your own KMS key, you need the following permissions on the KMS key.
kms:CreateGrant
kms:DescribeKey
kms:GenerateDataKey
kms:Decrypt
If you don't specify a value for
KmsKeyId
, images copied into the service are encrypted using a key that AWS owns and manages.VersionDescription
A description applied to the project version being created.
FeatureConfig
Feature-specific configuration of the training job. If the job configuration does not match the feature type associated with the project, an InvalidParameterException is returned.
Value¶
A list with the following syntax:
Request syntax¶
svc$create_project_version(
ProjectArn = "string",
VersionName = "string",
OutputConfig = list(
S3Bucket = "string",
S3KeyPrefix = "string"
),
TrainingData = list(
Assets = list(
list(
GroundTruthManifest = list(
S3Object = list(
Bucket = "string",
Name = "string",
Version = "string"
)
)
)
)
),
TestingData = list(
Assets = list(
list(
GroundTruthManifest = list(
S3Object = list(
Bucket = "string",
Name = "string",
Version = "string"
)
)
)
),
AutoCreate = TRUE|FALSE
),
Tags = list(
"string"
),
KmsKeyId = "string",
VersionDescription = "string",
FeatureConfig = list(
ContentModeration = list(
ConfidenceThreshold = 123.0
)
)
)
Examples¶
## Not run:
# Trains a version of an Amazon Rekognition Custom Labels model.
svc$create_project_version(
OutputConfig = list(
S3Bucket = "output_bucket",
S3KeyPrefix = "output_folder"
),
ProjectArn = "arn:aws:rekognition:us-east-1:111122223333:project/my-project/1690474772815",
VersionName = "1"
)
## End(Not run)