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create_dl_transform_pipelineCreateDlTransformPipelineCreateDlTransformPipelinecreate_dl_transform_pipelineT_create_dl_transform_pipeline🔗

Short description🔗

create_dl_transform_pipelineCreateDlTransformPipelineCreateDlTransformPipelinecreate_dl_transform_pipelineT_create_dl_transform_pipeline — Create a pipeline of transforms for the training of a deep learning model.

Signature🔗

create_dl_transform_pipeline( dl_transform Transforms, attribute.name GenParamName, attribute.value GenParamValue, out dl_transform_pipeline TransformPipeline )void CreateDlTransformPipeline( const HTuple& Transforms, const HTuple& GenParamName, const HTuple& GenParamValue, HTuple* TransformPipeline )static void HOperatorSet.CreateDlTransformPipeline( HTuple transforms, HTuple genParamName, HTuple genParamValue, out HTuple transformPipeline )def create_dl_transform_pipeline( transforms: MaybeSequence[HHandle], gen_param_name: Sequence[str], gen_param_value: Sequence[Union[float, int]] ) -> HHandle

Herror T_create_dl_transform_pipeline( const Htuple Transforms, const Htuple GenParamName, const Htuple GenParamValue, Htuple* TransformPipeline )

void HDlTransformPipeline::HDlTransformPipeline( const HDlTransformArray& Transforms, const HTuple& GenParamName, const HTuple& GenParamValue )

void HDlTransformPipeline::HDlTransformPipeline( const HDlTransform& Transforms, const HTuple& GenParamName, const HTuple& GenParamValue )

public HDlTransformPipeline( HDlTransform[] transforms, HTuple genParamName, HTuple genParamValue )

public HDlTransformPipeline( HDlTransform transforms, HTuple genParamName, HTuple genParamValue )

static HDlTransformPipeline HDlTransform::CreateDlTransformPipeline( const HDlTransformArray& Transforms, const HTuple& GenParamName, const HTuple& GenParamValue )

HDlTransformPipeline HDlTransform::CreateDlTransformPipeline( const HTuple& GenParamName, const HTuple& GenParamValue ) const

void HDlTransformPipeline::CreateDlTransformPipeline( const HDlTransformArray& Transforms, const HTuple& GenParamName, const HTuple& GenParamValue )

void HDlTransformPipeline::CreateDlTransformPipeline( const HDlTransform& Transforms, const HTuple& GenParamName, const HTuple& GenParamValue )

static HDlTransformPipeline HDlTransform.CreateDlTransformPipeline( HDlTransform[] transforms, HTuple genParamName, HTuple genParamValue )

HDlTransformPipeline HDlTransform.CreateDlTransformPipeline( HTuple genParamName, HTuple genParamValue )

void HDlTransformPipeline.CreateDlTransformPipeline( HDlTransform[] transforms, HTuple genParamName, HTuple genParamValue )

void HDlTransformPipeline.CreateDlTransformPipeline( HDlTransform transforms, HTuple genParamName, HTuple genParamValue )

Description🔗

The operator create_dl_transform_pipelineCreateDlTransformPipeline creates a pipeline of transforms Transformstransformstransforms for transforming a batch of samples prior to their use in train_dl_model_batchTrainDlModelBatch and apply_dl_modelApplyDlModel. Transforms may include adaptation of image dimensions or gray value range as well as augmentation methods.

The execution order of the transforms is defined by their order in the tuple Transformstransformstransforms. The execution is performed with the operator transform_dl_sample_batchTransformDlSampleBatch.

The following generic parameters GenParamNamegenParamNamegen_param_name and the corresponding values GenParamValuegenParamValuegen_param_value are supported:

  • 'fill_value'"fill_value": Value used to fill the padded regions if required by the transforms.

    Restriction: Only values of type integer or float are allowed.

    Default: 0.00.0.

  • 'bbox_min_side_length'"bbox_min_side_length": Minimum allowed side length of a transformed box instance. Smaller box instances are not transferred to output.

    Default: 22

  • 'instance_min_visibility'"instance_min_visibility": Minimum allowed visibility fraction of a transformed instance. Instances with lower visibility are not transferred to output.

    Default: 0.50.5

  • 'ignore_direction'"ignore_direction": Determines whether directions of oriented bounding boxes shall be used ('false'"false") or ignored ('true'"true"). Only for transformation of samples for detection models of 'instance_type'"instance_type" = 'rectangle2'"rectangle2".

    List of values: 'true'"true", 'false'"false"

    Default: 'false'"false"

Note that additionally 'class_ids_no_orientation'"class_ids_no_orientation" can be set using set_dl_transform_pipeline_paramSetDlTransformPipelineParam.

Execution information🔗

Execution information
  • Multithreading type: reentrant (runs in parallel with non-exclusive operators).

  • Multithreading scope: global (may be called from any thread).

  • Automatically parallelized on internal data level.

This operator returns a handle. Note that the state of an instance of this handle type may be changed by specific operators even though the handle is used as an input parameter by those operators.

Parameters🔗

Transformstransformstransforms (input_control) dl_transform(-array) → (handle)HTuple (HHandle)HDlTransform, HTuple (IntPtr)MaybeSequence[HHandle]Htuple (handle)

Tuple with the transform handles

GenParamNamegenParamNamegen_param_name (input_control) attribute.name-array → (string)HTuple (HString)HTuple (string)Sequence[str]Htuple (char*)

Names of the generic parameters that can be adjusted for the transform pipeline.

Default: [][]
List of values: 'bbox_min_side_length', 'fill_value', 'ignore_direction', 'instance_min_visibility'"bbox_min_side_length", "fill_value", "ignore_direction", "instance_min_visibility"

GenParamValuegenParamValuegen_param_value (input_control) attribute.value-array → (real / integer)HTuple (double / Hlong)HTuple (double / int / long)Sequence[Union[float, int]]Htuple (double / Hlong)

Values of the generic parameters that can be adjusted for the transform pipeline.

Default: [][]
Suggested values: 0.00.0

TransformPipelinetransformPipelinetransform_pipeline (output_control) dl_transform_pipeline → (handle)HTuple (HHandle)HDlTransformPipeline, HTuple (IntPtr)HHandleHtuple (handle)

Transform pipeline handle

Combinations with other operators🔗

Combinations

Possible predecessors

create_dl_transform_flipCreateDlTransformFlip, create_dl_transform_normalizeCreateDlTransformNormalize, create_dl_transform_random_cropCreateDlTransformRandomCrop, create_dl_transform_random_geometricCreateDlTransformRandomGeometric, create_dl_transform_random_hsvCreateDlTransformRandomHsv, create_dl_transform_resizeCreateDlTransformResize

Possible successors

get_dl_transform_pipeline_paramGetDlTransformPipelineParam, set_dl_transform_pipeline_paramSetDlTransformPipelineParam, transform_dl_sample_batchTransformDlSampleBatch

Module🔗

Foundation