get_generic_shape_model_paramT_get_generic_shape_model_paramGetGenericShapeModelParamGetGenericShapeModelParamget_generic_shape_model_param (算子)

名称

get_generic_shape_model_paramT_get_generic_shape_model_paramGetGenericShapeModelParamGetGenericShapeModelParamget_generic_shape_model_param — 返回形状模型的参数。

签名

get_generic_shape_model_param( : : ModelID, GenParamName : GenParamValue)

描述

算子 get_generic_shape_model_paramget_generic_shape_model_paramGetGenericShapeModelParamGetGenericShapeModelParamGetGenericShapeModelParamget_generic_shape_model_param returns the parameters values GenParamValueGenParamValueGenParamValueGenParamValuegenParamValuegen_param_value of GenParamNameGenParamNameGenParamNameGenParamNamegenParamNamegen_param_name for the shape model ModelIDModelIDModelIDModelIDmodelIDmodel_id。

For an explanation of the settable GenParamValueGenParamValueGenParamValueGenParamValuegenParamValuegen_param_value, see set_generic_shape_model_paramset_generic_shape_model_paramSetGenericShapeModelParamSetGenericShapeModelParamSetGenericShapeModelParamset_generic_shape_model_param。Additional parameters whose value can only be retrieved:

'needs_training'"needs_training""needs_training""needs_training""needs_training""needs_training"：

States, whether the model must be trained using train_generic_shape_modeltrain_generic_shape_modelTrainGenericShapeModelTrainGenericShapeModelTrainGenericShapeModeltrain_generic_shape_model before it can be used by find_generic_shape_modelfind_generic_shape_modelFindGenericShapeModelFindGenericShapeModelFindGenericShapeModelfind_generic_shape_model ('true'"true""true""true""true""true") or not ('false'"false""false""false""false""false").
'scale_type'"scale_type""scale_type""scale_type""scale_type""scale_type"：

A string which describes the type of scaling of the shape model.

算子 get_generic_shape_model_paramget_generic_shape_model_paramGetGenericShapeModelParamGetGenericShapeModelParamGetGenericShapeModelParamget_generic_shape_model_param returns the value as it is used by the shape model. As certain parameters may be modified after calling train_generic_shape_modeltrain_generic_shape_modelTrainGenericShapeModelTrainGenericShapeModelTrainGenericShapeModeltrain_generic_shape_model, their value can differ from the set value. This applies particularly to parameters whose value is to be determined automatically, e.g., with values set to 'auto'"auto""auto""auto""auto""auto". The (unmodified) set value of a GenParamNameGenParamNameGenParamNameGenParamNamegenParamNamegen_param_name can be retrieved by adding the suffix '_param' to its name.

Example: After calling train_generic_shape_modeltrain_generic_shape_modelTrainGenericShapeModelTrainGenericShapeModelTrainGenericShapeModeltrain_generic_shape_model, 'num_levels'"num_levels""num_levels""num_levels""num_levels""num_levels" returns the estimated value and 'num_levels_param'"num_levels_param""num_levels_param""num_levels_param""num_levels_param""num_levels_param" returns the set value, e.g., its value set by default or the one set by the user.

执行信息

多线程类型：可重入（与非独占算子并行运行）。
多线程作用域：全局（可从任何线程调用）。
未采用并行化处理。

此算子修改后续输入参数的状态：

ModelIDModelIDModelIDModelIDmodelIDmodel_id

在执行此算子时，若该参数值需在多个线程间使用，则必须对其访问进行同步。

参数

ModelIDModelIDModelIDModelIDmodelIDmodel_id (输入控制，状态被修改) shape_model → (handle)

形状模型的句柄。

GenParamNameGenParamNameGenParamNameGenParamNamegenParamNamegen_param_name (输入控制) attribute.name-array → (string)

Parameter name.

默认值： 'min_score' "min_score" "min_score" "min_score" "min_score" "min_score"

值列表： 'angle_end'"angle_end""angle_end""angle_end""angle_end""angle_end", 'angle_start'"angle_start""angle_start""angle_start""angle_start""angle_start", 'angle_step'"angle_step""angle_step""angle_step""angle_step""angle_step", 'border_shape_models'"border_shape_models""border_shape_models""border_shape_models""border_shape_models""border_shape_models", 'clutter_border_mode'"clutter_border_mode""clutter_border_mode""clutter_border_mode""clutter_border_mode""clutter_border_mode", 'clutter_contrast'"clutter_contrast""clutter_contrast""clutter_contrast""clutter_contrast""clutter_contrast", 'clutter_hom_mat_2d'"clutter_hom_mat_2d""clutter_hom_mat_2d""clutter_hom_mat_2d""clutter_hom_mat_2d""clutter_hom_mat_2d", 'contrast_high'"contrast_high""contrast_high""contrast_high""contrast_high""contrast_high", 'contrast_low'"contrast_low""contrast_low""contrast_low""contrast_low""contrast_low", 'greediness'"greediness""greediness""greediness""greediness""greediness", 'iso_scale_max'"iso_scale_max""iso_scale_max""iso_scale_max""iso_scale_max""iso_scale_max", 'iso_scale_min'"iso_scale_min""iso_scale_min""iso_scale_min""iso_scale_min""iso_scale_min", 'iso_scale_step'"iso_scale_step""iso_scale_step""iso_scale_step""iso_scale_step""iso_scale_step", 'max_clutter'"max_clutter""max_clutter""max_clutter""max_clutter""max_clutter", 'max_deformation'"max_deformation""max_deformation""max_deformation""max_deformation""max_deformation", 'max_overlap'"max_overlap""max_overlap""max_overlap""max_overlap""max_overlap", 'max_overlap_global_enable'"max_overlap_global_enable""max_overlap_global_enable""max_overlap_global_enable""max_overlap_global_enable""max_overlap_global_enable", 'metric'"metric""metric""metric""metric""metric", 'min_contrast'"min_contrast""min_contrast""min_contrast""min_contrast""min_contrast", 'min_score'"min_score""min_score""min_score""min_score""min_score", 'min_size'"min_size""min_size""min_size""min_size""min_size", 'model_cache'"model_cache""model_cache""model_cache""model_cache""model_cache", 'model_identifier'"model_identifier""model_identifier""model_identifier""model_identifier""model_identifier", 'needs_training'"needs_training""needs_training""needs_training""needs_training""needs_training", 'num_levels'"num_levels""num_levels""num_levels""num_levels""num_levels", 'num_matches'"num_matches""num_matches""num_matches""num_matches""num_matches", 'optimization'"optimization""optimization""optimization""optimization""optimization", 'origin_column'"origin_column""origin_column""origin_column""origin_column""origin_column", 'origin_row'"origin_row""origin_row""origin_row""origin_row""origin_row", 'prepare_clutter_region_for_visualization', 'prepare_contours_for_visualization'"prepare_contours_for_visualization""prepare_contours_for_visualization""prepare_contours_for_visualization""prepare_contours_for_visualization""prepare_contours_for_visualization", 'pyramid_level_highest'"pyramid_level_highest""pyramid_level_highest""pyramid_level_highest""pyramid_level_highest""pyramid_level_highest", 'pyramid_level_lowest'"pyramid_level_lowest""pyramid_level_lowest""pyramid_level_lowest""pyramid_level_lowest""pyramid_level_lowest", 'pyramid_level_robust_tracking'"pyramid_level_robust_tracking""pyramid_level_robust_tracking""pyramid_level_robust_tracking""pyramid_level_robust_tracking""pyramid_level_robust_tracking", 'restrict_iso_scale_max'"restrict_iso_scale_max""restrict_iso_scale_max""restrict_iso_scale_max""restrict_iso_scale_max""restrict_iso_scale_max", 'restrict_iso_scale_min'"restrict_iso_scale_min""restrict_iso_scale_min""restrict_iso_scale_min""restrict_iso_scale_min""restrict_iso_scale_min", 'restrict_scale_column_max'"restrict_scale_column_max""restrict_scale_column_max""restrict_scale_column_max""restrict_scale_column_max""restrict_scale_column_max", 'restrict_scale_column_min'"restrict_scale_column_min""restrict_scale_column_min""restrict_scale_column_min""restrict_scale_column_min""restrict_scale_column_min", 'restrict_scale_row_max'"restrict_scale_row_max""restrict_scale_row_max""restrict_scale_row_max""restrict_scale_row_max""restrict_scale_row_max", 'restrict_scale_row_min'"restrict_scale_row_min""restrict_scale_row_min""restrict_scale_row_min""restrict_scale_row_min""restrict_scale_row_min", 'scale_column_max'"scale_column_max""scale_column_max""scale_column_max""scale_column_max""scale_column_max", 'scale_column_min'"scale_column_min""scale_column_min""scale_column_min""scale_column_min""scale_column_min", 'scale_column_step'"scale_column_step""scale_column_step""scale_column_step""scale_column_step""scale_column_step", 'scale_row_max'"scale_row_max""scale_row_max""scale_row_max""scale_row_max""scale_row_max", 'scale_row_min'"scale_row_min""scale_row_min""scale_row_min""scale_row_min""scale_row_min", 'scale_row_step'"scale_row_step""scale_row_step""scale_row_step""scale_row_step""scale_row_step", 'scale_type'"scale_type""scale_type""scale_type""scale_type""scale_type", 'strict_boundaries'"strict_boundaries""strict_boundaries""strict_boundaries""strict_boundaries""strict_boundaries", 'subpixel'"subpixel""subpixel""subpixel""subpixel""subpixel", 'time_measurement'"time_measurement""time_measurement""time_measurement""time_measurement""time_measurement", 'timeout'"timeout""timeout""timeout""timeout""timeout", 'use_clutter'"use_clutter""use_clutter""use_clutter""use_clutter""use_clutter"

GenParamValueGenParamValueGenParamValueGenParamValuegenParamValuegen_param_value (输出控制) attribute.value-array → (real / integer / string)

Parameter value.

结果

如果参数有效，算子 get_generic_shape_model_paramget_generic_shape_model_paramGetGenericShapeModelParamGetGenericShapeModelParamGetGenericShapeModelParamget_generic_shape_model_param 返回值 2 ( H_MSG_TRUE )。如有必要，则抛出异常。

可能的前趋

create_generic_shape_modelcreate_generic_shape_modelCreateGenericShapeModelCreateGenericShapeModelCreateGenericShapeModelcreate_generic_shape_model, set_generic_shape_model_paramset_generic_shape_model_paramSetGenericShapeModelParamSetGenericShapeModelParamSetGenericShapeModelParamset_generic_shape_model_param, train_generic_shape_modeltrain_generic_shape_modelTrainGenericShapeModelTrainGenericShapeModelTrainGenericShapeModeltrain_generic_shape_model

模块

匹配

算子