PNG  IHDR;IDATxܻn0K )(pA 7LeG{ §㻢|ذaÆ 6lذaÆ 6lذaÆ 6lom$^yذag5bÆ 6lذaÆ 6lذa{ 6lذaÆ `}HFkm,mӪôô! x|'ܢ˟;E:9&ᶒ}{v]n&6 h_tڠ͵-ҫZ;Z$.Pkž)!o>}leQfJTu іچ\X=8Rن4`Vwl>nG^is"ms$ui?wbs[m6K4O.4%/bC%t Mז -lG6mrz2s%9s@-k9=)kB5\+͂Zsٲ Rn~GRC wIcIn7jJhۛNCS|j08yiHKֶۛkɈ+;SzL/F*\Ԕ#"5m2[S=gnaPeғL lذaÆ 6l^ḵaÆ 6lذaÆ 6lذa; _ذaÆ 6lذaÆ 6lذaÆ RIENDB` package Paws::LookoutVision; use Moose; sub service { 'lookoutvision' } sub signing_name { 'lookoutvision' } sub version { '2020-11-20' } sub flattened_arrays { 0 } has max_attempts => (is => 'ro', isa => 'Int', default => 5); has retry => (is => 'ro', isa => 'HashRef', default => sub { { base => 'rand', type => 'exponential', growth_factor => 2 } }); has retriables => (is => 'ro', isa => 'ArrayRef', default => sub { [ ] }); with 'Paws::API::Caller', 'Paws::API::EndpointResolver', 'Paws::Net::V4Signature', 'Paws::Net::RestJsonCaller'; sub CreateDataset { my $self = shift; my $call_object = $self->new_with_coercions('Paws::LookoutVision::CreateDataset', @_); return $self->caller->do_call($self, $call_object); } sub CreateModel { my $self = shift; my $call_object = $self->new_with_coercions('Paws::LookoutVision::CreateModel', @_); return $self->caller->do_call($self, $call_object); } sub CreateProject { my $self = shift; my $call_object = $self->new_with_coercions('Paws::LookoutVision::CreateProject', @_); return $self->caller->do_call($self, $call_object); } sub DeleteDataset { my $self = shift; my $call_object = $self->new_with_coercions('Paws::LookoutVision::DeleteDataset', @_); return $self->caller->do_call($self, $call_object); } sub DeleteModel { my $self = shift; my $call_object = $self->new_with_coercions('Paws::LookoutVision::DeleteModel', @_); return $self->caller->do_call($self, $call_object); } sub DeleteProject { my $self = shift; my $call_object = $self->new_with_coercions('Paws::LookoutVision::DeleteProject', @_); return $self->caller->do_call($self, $call_object); } sub DescribeDataset { my $self = shift; my $call_object = $self->new_with_coercions('Paws::LookoutVision::DescribeDataset', @_); return $self->caller->do_call($self, $call_object); } sub DescribeModel { my $self = shift; my $call_object = $self->new_with_coercions('Paws::LookoutVision::DescribeModel', @_); return $self->caller->do_call($self, $call_object); } sub DescribeProject { my $self = shift; my $call_object = $self->new_with_coercions('Paws::LookoutVision::DescribeProject', @_); return $self->caller->do_call($self, $call_object); } sub DetectAnomalies { my $self = shift; my $call_object = $self->new_with_coercions('Paws::LookoutVision::DetectAnomalies', @_); return $self->caller->do_call($self, $call_object); } sub ListDatasetEntries { my $self = shift; my $call_object = $self->new_with_coercions('Paws::LookoutVision::ListDatasetEntries', @_); return $self->caller->do_call($self, $call_object); } sub ListModels { my $self = shift; my $call_object = $self->new_with_coercions('Paws::LookoutVision::ListModels', @_); return $self->caller->do_call($self, $call_object); } sub ListProjects { my $self = shift; my $call_object = $self->new_with_coercions('Paws::LookoutVision::ListProjects', @_); return $self->caller->do_call($self, $call_object); } sub ListTagsForResource { my $self = shift; my $call_object = $self->new_with_coercions('Paws::LookoutVision::ListTagsForResource', @_); return $self->caller->do_call($self, $call_object); } sub StartModel { my $self = shift; my $call_object = $self->new_with_coercions('Paws::LookoutVision::StartModel', @_); return $self->caller->do_call($self, $call_object); } sub StopModel { my $self = shift; my $call_object = $self->new_with_coercions('Paws::LookoutVision::StopModel', @_); return $self->caller->do_call($self, $call_object); } sub TagResource { my $self = shift; my $call_object = $self->new_with_coercions('Paws::LookoutVision::TagResource', @_); return $self->caller->do_call($self, $call_object); } sub UntagResource { my $self = shift; my $call_object = $self->new_with_coercions('Paws::LookoutVision::UntagResource', @_); return $self->caller->do_call($self, $call_object); } sub UpdateDatasetEntries { my $self = shift; my $call_object = $self->new_with_coercions('Paws::LookoutVision::UpdateDatasetEntries', @_); return $self->caller->do_call($self, $call_object); } sub ListAllDatasetEntries { my $self = shift; my $callback = shift @_ if (ref($_[0]) eq 'CODE'); my $result = $self->ListDatasetEntries(@_); my $next_result = $result; if (not defined $callback) { while ($next_result->NextToken) { $next_result = $self->ListDatasetEntries(@_, NextToken => $next_result->NextToken); push @{ $result->DatasetEntries }, @{ $next_result->DatasetEntries }; } return $result; } else { while ($result->NextToken) { $callback->($_ => 'DatasetEntries') foreach (@{ $result->DatasetEntries }); $result = $self->ListDatasetEntries(@_, NextToken => $result->NextToken); } $callback->($_ => 'DatasetEntries') foreach (@{ $result->DatasetEntries }); } return undef } sub ListAllModels { my $self = shift; my $callback = shift @_ if (ref($_[0]) eq 'CODE'); my $result = $self->ListModels(@_); my $next_result = $result; if (not defined $callback) { while ($next_result->NextToken) { $next_result = $self->ListModels(@_, NextToken => $next_result->NextToken); push @{ $result->Models }, @{ $next_result->Models }; } return $result; } else { while ($result->NextToken) { $callback->($_ => 'Models') foreach (@{ $result->Models }); $result = $self->ListModels(@_, NextToken => $result->NextToken); } $callback->($_ => 'Models') foreach (@{ $result->Models }); } return undef } sub ListAllProjects { my $self = shift; my $callback = shift @_ if (ref($_[0]) eq 'CODE'); my $result = $self->ListProjects(@_); my $next_result = $result; if (not defined $callback) { while ($next_result->NextToken) { $next_result = $self->ListProjects(@_, NextToken => $next_result->NextToken); push @{ $result->Projects }, @{ $next_result->Projects }; } return $result; } else { while ($result->NextToken) { $callback->($_ => 'Projects') foreach (@{ $result->Projects }); $result = $self->ListProjects(@_, NextToken => $result->NextToken); } $callback->($_ => 'Projects') foreach (@{ $result->Projects }); } return undef } sub operations { qw/CreateDataset CreateModel CreateProject DeleteDataset DeleteModel DeleteProject DescribeDataset DescribeModel DescribeProject DetectAnomalies ListDatasetEntries ListModels ListProjects ListTagsForResource StartModel StopModel TagResource UntagResource UpdateDatasetEntries / } 1; ### main pod documentation begin ### =head1 NAME Paws::LookoutVision - Perl Interface to AWS Amazon Lookout for Vision =head1 SYNOPSIS use Paws; my $obj = Paws->service('LookoutVision'); my $res = $obj->Method( Arg1 => $val1, Arg2 => [ 'V1', 'V2' ], # if Arg3 is an object, the HashRef will be used as arguments to the constructor # of the arguments type Arg3 => { Att1 => 'Val1' }, # if Arg4 is an array of objects, the HashRefs will be passed as arguments to # the constructor of the arguments type Arg4 => [ { Att1 => 'Val1' }, { Att1 => 'Val2' } ], ); =head1 DESCRIPTION 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 E or any other physical item where quality is important such as a missing capacitor on printed circuit boards. For the AWS API documentation, see L =head1 METHODS =head2 CreateDataset =over =item DatasetType => Str =item ProjectName => Str =item [ClientToken => Str] =item [DatasetSource => L] =back Each argument is described in detail in: L Returns: a L instance Creates a new dataset in an Amazon Lookout for Vision project. C can create a training or a test dataset from a valid dataset source (C). If you want a single dataset project, specify C for the value of C. To have a project with separate training and test datasets, call C twice. On the first call, specify C for the value of C. On the second call, specify C for the value of C. This operation requires permissions to perform the C operation. =head2 CreateModel =over =item OutputConfig => L =item ProjectName => Str =item [ClientToken => Str] =item [Description => Str] =item [KmsKeyId => Str] =item [Tags => ArrayRef[L]] =back Each argument is described in detail in: L Returns: a L instance Creates a new version of a model within an an Amazon Lookout for Vision project. C 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 C 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 C. This operation requires permissions to perform the C operation. If you want to tag your model, you also require permission to the C operation. =head2 CreateProject =over =item ProjectName => Str =item [ClientToken => Str] =back Each argument is described in detail in: L Returns: a L instance 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 C operation. =head2 DeleteDataset =over =item DatasetType => Str =item ProjectName => Str =item [ClientToken => Str] =back Each argument is described in detail in: L Returns: a L instance Deletes an existing Amazon Lookout for Vision C. 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. =over =item * 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. =item * If you delete the training dataset, you must create a training dataset before you can create a model. =back This operation requires permissions to perform the C operation. =head2 DeleteModel =over =item ModelVersion => Str =item ProjectName => Str =item [ClientToken => Str] =back Each argument is described in detail in: L Returns: a L instance Deletes 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 ListProjects and check if the version of the model (C) is in the C array. This operation requires permissions to perform the C operation. =head2 DeleteProject =over =item ProjectName => Str =item [ClientToken => Str] =back Each argument is described in detail in: L Returns: a L instance 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 C operation. =head2 DescribeDataset =over =item DatasetType => Str =item ProjectName => Str =back Each argument is described in detail in: L Returns: a L instance Describe an Amazon Lookout for Vision dataset. This operation requires permissions to perform the C operation. =head2 DescribeModel =over =item ModelVersion => Str =item ProjectName => Str =back Each argument is described in detail in: L Returns: a L instance Describes a version of an Amazon Lookout for Vision model. This operation requires permissions to perform the C operation. =head2 DescribeProject =over =item ProjectName => Str =back Each argument is described in detail in: L Returns: a L instance Describes an Amazon Lookout for Vision project. This operation requires permissions to perform the C operation. =head2 DetectAnomalies =over =item Body => Str =item ContentType => Str =item ModelVersion => Str =item ProjectName => Str =back Each argument is described in detail in: L Returns: a L instance Detects anomalies in an image that you supply. The response from C includes a boolean prediction that the image contains one or more anomalies and a confidence value for the prediction. Before calling C, 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 C operation. =head2 ListDatasetEntries =over =item DatasetType => Str =item ProjectName => Str =item [AfterCreationDate => Str] =item [AnomalyClass => Str] =item [BeforeCreationDate => Str] =item [Labeled => Bool] =item [MaxResults => Int] =item [NextToken => Str] =item [SourceRefContains => Str] =back Each argument is described in detail in: L Returns: a L instance 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 C operation. =head2 ListModels =over =item ProjectName => Str =item [MaxResults => Int] =item [NextToken => Str] =back Each argument is described in detail in: L Returns: a L instance Lists the versions of a model in an Amazon Lookout for Vision project. This operation requires permissions to perform the C operation. =head2 ListProjects =over =item [MaxResults => Int] =item [NextToken => Str] =back Each argument is described in detail in: L Returns: a L instance Lists the Amazon Lookout for Vision projects in your AWS account. This operation requires permissions to perform the C operation. =head2 ListTagsForResource =over =item ResourceArn => Str =back Each argument is described in detail in: L Returns: a L instance Returns a list of tags attached to the specified Amazon Lookout for Vision model. This operation requires permissions to perform the C operation. =head2 StartModel =over =item MinInferenceUnits => Int =item ModelVersion => Str =item ProjectName => Str =item [ClientToken => Str] =back Each argument is described in detail in: L Returns: a L instance 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 C. 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 C operation. =head2 StopModel =over =item ModelVersion => Str =item ProjectName => Str =item [ClientToken => Str] =back Each argument is described in detail in: L Returns: a L instance 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 C of the model is C. This operation requires permissions to perform the C operation. =head2 TagResource =over =item ResourceArn => Str =item Tags => ArrayRef[L] =back Each argument is described in detail in: L Returns: a L instance Adds one or more key-value tags to an Amazon Lookout for Vision model. For more information, see I in the I. This operation requires permissions to perform the C operation. =head2 UntagResource =over =item ResourceArn => Str =item TagKeys => ArrayRef[Str|Undef] =back Each argument is described in detail in: L Returns: a L instance Removes one or more tags from an Amazon Lookout for Vision model. For more information, see I in the I. This operation requires permissions to perform the C operation. =head2 UpdateDatasetEntries =over =item Changes => Str =item DatasetType => Str =item ProjectName => Str =item [ClientToken => Str] =back Each argument is described in detail in: L Returns: a L instance 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 C field in the response. This operation requires permissions to perform the C operation. =head1 PAGINATORS Paginator methods are helpers that repetively call methods that return partial results =head2 ListAllDatasetEntries(sub { },DatasetType => Str, ProjectName => Str, [AfterCreationDate => Str, AnomalyClass => Str, BeforeCreationDate => Str, Labeled => Bool, MaxResults => Int, NextToken => Str, SourceRefContains => Str]) =head2 ListAllDatasetEntries(DatasetType => Str, ProjectName => Str, [AfterCreationDate => Str, AnomalyClass => Str, BeforeCreationDate => Str, Labeled => Bool, MaxResults => Int, NextToken => Str, SourceRefContains => Str]) If passed a sub as first parameter, it will call the sub for each element found in : - DatasetEntries, passing the object as the first parameter, and the string 'DatasetEntries' as the second parameter If not, it will return a a L instance with all the Cs; from all the responses. Please take into account that this mode can potentially consume vasts ammounts of memory. =head2 ListAllModels(sub { },ProjectName => Str, [MaxResults => Int, NextToken => Str]) =head2 ListAllModels(ProjectName => Str, [MaxResults => Int, NextToken => Str]) If passed a sub as first parameter, it will call the sub for each element found in : - Models, passing the object as the first parameter, and the string 'Models' as the second parameter If not, it will return a a L instance with all the Cs; from all the responses. Please take into account that this mode can potentially consume vasts ammounts of memory. =head2 ListAllProjects(sub { },[MaxResults => Int, NextToken => Str]) =head2 ListAllProjects([MaxResults => Int, NextToken => Str]) If passed a sub as first parameter, it will call the sub for each element found in : - Projects, passing the object as the first parameter, and the string 'Projects' as the second parameter If not, it will return a a L instance with all the Cs; from all the responses. Please take into account that this mode can potentially consume vasts ammounts of memory. =head1 SEE ALSO This service class forms part of L =head1 BUGS and CONTRIBUTIONS The source code is located here: L Please report bugs to: L =cut