get_generic_shape_model_param🔗
Short description🔗
get_generic_shape_model_param — Return the parameters of a shape model.
Signature🔗
get_generic_shape_model_param( shape_model ModelID, attribute.name GenParamName, out attribute.value GenParamValue )
Description🔗
The operator get_generic_shape_model_param returns the parameters
values GenParamValue of GenParamName for the shape model
ModelID.
For an explanation of the settable GenParamValue, see
set_generic_shape_model_param.
Additional parameters whose value can only be retrieved:
-
'has_samples':
States, whether the model contains training samples for sample-based training ('true') or not ('false').
-
'needs_training':
States, whether the model must be trained using
train_generic_shape_modelbefore it can be used byfind_generic_shape_model('true') or not ('false'). -
'sample_based_training_compatible':
States, whether the model is compatible with the selected sample-based training methods ('true') or not ('false'). Selected methods for the sample-based training are set using 'sample_based_training' and retrievable using 'sample_based_training_param'.
In order to accomplish a successful sample-based training, the model needs to be compatible and contain training samples.
-
'scale_type':
A string which describes the type of scaling of the shape model.
-
'score_visualization_enabled':
States, whether the set parameters are compatible for 'score_visualization' and therewith the calculation of the score contribution of each model point is possible ('true') or not ('false').
The operator get_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_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'.
The (unmodified) set value of a GenParamName can be retrieved by
adding the suffix ’_param’ to its name.
Example: After calling train_generic_shape_model,
'num_levels' returns the estimated value
and 'num_levels_param' returns the set value, e.g., its value
set by default or the one set by the user.
Exceptions to this rule are:
-
'greediness' when 'sample_based_training' is set to 'per_level'.
-
'min_score' when 'sample_based_training' is set to 'per_level'.
A parameter GenParamName for which the resulting
GenParamValue can consist of more than a single value,
for example a transformation matrix, cannot be queried together with other
parameters. Instead, it requires a separate call to
get_generic_shape_model_param.
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 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🔗
ModelID (input_control, state is modified) shape_model → (handle)
Handle of the shape model.
GenParamName (input_control) attribute.name-array → (string)
Parameter name.
Default: 'min_score'
List of values: 'angle_end', 'angle_start', 'angle_step', 'border_shape_models', 'clutter_border_mode', 'clutter_contrast', 'clutter_hom_mat_2d', 'contour_pruning_threshold', 'contrast_high', 'contrast_low', 'greediness', 'has_samples', 'iso_scale_max', 'iso_scale_min', 'iso_scale_step', 'max_clutter', 'max_deformation', 'max_overlap', 'max_overlap_global_enable', 'metric', 'min_contrast', 'min_score', 'min_size', 'model_cache', 'model_identifier', 'needs_training', 'num_levels', 'num_matches', 'num_matches_global_enable', 'optimization', 'origin_column', 'origin_row', 'prepare_clutter_region_for_visualization', 'prepare_contours_for_visualization', 'pyramid_level_highest', 'pyramid_level_lowest', 'pyramid_level_robust_tracking', 'restrict_iso_scale_max', 'restrict_iso_scale_min', 'restrict_scale_column_max', 'restrict_scale_column_min', 'restrict_scale_row_max', 'restrict_scale_row_min', 'sample_based_training', 'sample_based_training_compatible', 'scale_column_max', 'scale_column_min', 'scale_column_step', 'scale_row_max', 'scale_row_min', 'scale_row_step', 'scale_type', 'score_visualization', 'score_visualization_enabled', 'strict_boundaries', 'subpixel', 'time_measurement', 'timeout', 'use_clutter'
GenParamValue (output_control) attribute.value-array → (real / integer / string)
Parameter value.
Result🔗
If the parameters are valid, the operator
get_generic_shape_model_param returns the value 2 (H_MSG_TRUE).
If necessary an exception is raised.
Combinations with other operators🔗
Combinations
Possible predecessors
create_generic_shape_model, set_generic_shape_model_param, train_generic_shape_model
Module🔗
Matching