create_deep_counting_modelCreateDeepCountingModelCreateDeepCountingModelcreate_deep_counting_modelT_create_deep_counting_model🔗

Short description🔗

create_deep_counting_modelCreateDeepCountingModelCreateDeepCountingModelcreate_deep_counting_modelT_create_deep_counting_model — Create a Deep Counting model for counting objects.

Signature🔗

create_deep_counting_model( attribute.name GenParamName, attribute.value GenParamValue, out deep_counting DeepCountingHandle )

Description🔗

create_deep_counting_modelCreateDeepCountingModel creates a Deep Counting model and returns its handle in DeepCountingHandledeepCountingHandledeep_counting_handle.

Internally create_deep_counting_modelCreateDeepCountingModel builds a backbone based on the pretrained network 'pretrained_dl_classifier_resnet50.hdl'"pretrained_dl_classifier_resnet50.hdl", which must be available. See read_dl_modelReadDlModel for details on where the file is searched.

Additional parameters of the Deep Counting model can be set using the generic parameters GenParamNamegenParamNamegen_param_name and GenParamValuegenParamValuegen_param_value. See get_deep_counting_model_paramGetDeepCountingModelParam for a list of parameters and their possible values. The parameters can either be set during model creation, or later using set_deep_counting_model_paramSetDeepCountingModelParam.

Note that before using the returned Deep Counting model with apply_deep_counting_modelApplyDeepCountingModel, templates must be stored in the model using prepare_deep_counting_modelPrepareDeepCountingModel.

Execution information🔗

Execution information

Multithreading type: reentrant (runs in parallel with non-exclusive operators).
Multithreading scope: global (may be called from any thread).
Processed without parallelization.

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🔗

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

Parameter names.

Default: [][]
List of values: 'angle_end', 'angle_start', 'angle_step', 'device', 'max_overlap', 'min_score', 'scale_max', 'scale_min', 'scale_step'

GenParamValuegenParamValuegen_param_value (input_control) attribute.value(-array) → (real / integer / string)HTuple (double / Hlong / HString)HTuple (double / int / long / string)MaybeSequence[Union[float, int, str]]Htuple (double / Hlong / char*)

Parameter values.

Default: [][]

DeepCountingHandledeepCountingHandledeep_counting_handle (output_control) deep_counting → (handle)HTuple (HHandle)HDlModelCounting, HTuple (IntPtr)HHandleHtuple (handle)

Deep Counting model for counting objects.

Result🔗

If the parameters are valid, the operator create_deep_counting_modelCreateDeepCountingModel returns the value 2 (H_MSG_TRUE). If necessary, an exception is raised.

Combinations with other operators🔗

Combinations

Possible successors

set_deep_counting_model_paramSetDeepCountingModelParam, get_deep_counting_model_paramGetDeepCountingModelParam, prepare_deep_counting_modelPrepareDeepCountingModel, apply_deep_counting_modelApplyDeepCountingModel

Alternatives

read_deep_counting_modelReadDeepCountingModel

Module🔗

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