Operator Reference

HALCON Operator Reference / Matching / Deep Counting
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prepare_deep_counting_modelT_prepare_deep_counting_modelPrepareDeepCountingModelPrepareDeepCountingModelprepare_deep_counting_model (Operator)

prepare_deep_counting_modelT_prepare_deep_counting_modelPrepareDeepCountingModelPrepareDeepCountingModelprepare_deep_counting_model — Set templates of a Deep Counting model.

Signature

prepare_deep_counting_model(Templates : : DeepCountingHandle : )

Herror T_prepare_deep_counting_model(const Hobject Templates, const Htuple DeepCountingHandle)

void PrepareDeepCountingModel(const HObject& Templates, const HTuple& DeepCountingHandle)

void HDlModelCounting::PrepareDeepCountingModel(const HImage& Templates) const

static void HOperatorSet.PrepareDeepCountingModel(HObject templates, HTuple deepCountingHandle)

void HDlModelCounting.PrepareDeepCountingModel(HImage templates)

def prepare_deep_counting_model(templates: HObject, deep_counting_handle: HHandle) -> None

Description

prepare_deep_counting_modelprepare_deep_counting_modelPrepareDeepCountingModelPrepareDeepCountingModelprepare_deep_counting_model sets the templates of the objects that should be counted by the Deep Counting model DeepCountingHandleDeepCountingHandleDeepCountingHandledeepCountingHandledeep_counting_handle. When applying the Deep Counting model using apply_deep_counting_modelapply_deep_counting_modelApplyDeepCountingModelApplyDeepCountingModelapply_deep_counting_model, objects in the search images that are similar to the provided templates are detected and counted. Note that this operator overwrites any previously set templates.

To also count scaled and rotated variants of the provided templates, an automatic augmentation of the templates can be enabled by setting the parameters 'angle_start'"angle_start""angle_start""angle_start""angle_start", 'angle_end'"angle_end""angle_end""angle_end""angle_end", 'angle_step'"angle_step""angle_step""angle_step""angle_step", 'scale_min'"scale_min""scale_min""scale_min""scale_min", 'scale_max'"scale_max""scale_max""scale_max""scale_max", and 'scale_step'"scale_step""scale_step""scale_step""scale_step" using create_deep_counting_modelcreate_deep_counting_modelCreateDeepCountingModelCreateDeepCountingModelcreate_deep_counting_model or set_deep_counting_model_paramset_deep_counting_model_paramSetDeepCountingModelParamSetDeepCountingModelParamset_deep_counting_model_param before calling apply_deep_counting_modelapply_deep_counting_modelApplyDeepCountingModelApplyDeepCountingModelapply_deep_counting_model.

When changing parameters of the Deep Counting model that influence the template creation, prepare_deep_counting_modelprepare_deep_counting_modelPrepareDeepCountingModelPrepareDeepCountingModelprepare_deep_counting_model must be re-run before apply_deep_counting_modelapply_deep_counting_modelApplyDeepCountingModelApplyDeepCountingModelapply_deep_counting_model. The list of such parameters is provided in get_deep_counting_model_paramget_deep_counting_model_paramGetDeepCountingModelParamGetDeepCountingModelParamget_deep_counting_model_param.

Attention

System requirements: To run this operator on GPU (see get_deep_counting_model_paramget_deep_counting_model_paramGetDeepCountingModelParamGetDeepCountingModelParamget_deep_counting_model_param), cuDNN and cuBLAS are required. For further details, please refer to the “Installation Guide”, paragraph “Requirements for Deep Learning and Deep-Learning-Based Methods”. Alternatively, this operator can also be run on CPU.

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 modifies the state of the following input parameter:

During execution of this operator, access to the value of this parameter must be synchronized if it is used across multiple threads.

Parameters

TemplatesTemplatesTemplatestemplatestemplates (input_object)  (multichannel-)image(-array) → objectHImageHObjectHObjectHobject (byte / real)

Template image(s) with regions.

DeepCountingHandleDeepCountingHandleDeepCountingHandledeepCountingHandledeep_counting_handle (input_control, state is modified)  deep_counting → HDlModelCounting, HTupleHHandleHTupleHtuple (handle) (IntPtr) (HHandle) (handle)

Handle of the Deep Counting model.

Result

If the handle of the model is valid, the operator prepare_deep_counting_modelprepare_deep_counting_modelPrepareDeepCountingModelPrepareDeepCountingModelprepare_deep_counting_model returns the value 2 ( H_MSG_TRUE) . If necessary an exception is raised.

Possible Predecessors

create_deep_counting_modelcreate_deep_counting_modelCreateDeepCountingModelCreateDeepCountingModelcreate_deep_counting_model, set_deep_counting_model_paramset_deep_counting_model_paramSetDeepCountingModelParamSetDeepCountingModelParamset_deep_counting_model_param, get_deep_counting_model_paramget_deep_counting_model_paramGetDeepCountingModelParamGetDeepCountingModelParamget_deep_counting_model_param, read_deep_counting_modelread_deep_counting_modelReadDeepCountingModelReadDeepCountingModelread_deep_counting_model

Possible Successors

apply_deep_counting_modelapply_deep_counting_modelApplyDeepCountingModelApplyDeepCountingModelapply_deep_counting_model

Alternatives

read_deep_counting_modelread_deep_counting_modelReadDeepCountingModelReadDeepCountingModelread_deep_counting_model

See also

apply_deep_counting_modelapply_deep_counting_modelApplyDeepCountingModelApplyDeepCountingModelapply_deep_counting_model

Module

Matching

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