select_feature_set_trainf_mlp_protectedSelectFeatureSetTrainfMlpProtectedSelectFeatureSetTrainfMlpProtectedselect_feature_set_trainf_mlp_protected🔗

Short description🔗

select_feature_set_trainf_mlp_protectedSelectFeatureSetTrainfMlpProtectedSelectFeatureSetTrainfMlpProtectedselect_feature_set_trainf_mlp_protectedT_select_feature_set_trainf_mlp_protected — Select an optimal combination of features to classify OCR data from a (protected) training file.

Signature🔗

select_feature_set_trainf_mlp_protected( filename.read TrainingFile, string Password, string FeatureList, string SelectionMethod, integer Width, integer Height, string GenParamName, number GenParamValue, out ocr_mlp OCRHandle, out string FeatureSet, out real Score )

Description🔗

select_feature_set_trainf_mlp_protectedSelectFeatureSetTrainfMlpProtected selects an optimal combination of features to classify the data given in the training files TrainingFiletrainingFiletraining_file with a multilayer perceptron (MLP). Its functionality corresponds to the functionality of select_feature_set_trainf_mlpSelectFeatureSetTrainfMlp, with the addition that select_feature_set_trainf_mlp_protectedSelectFeatureSetTrainfMlpProtected can process unprotected and protected training files. Protected training files can be used only with the correct user password Passwordpasswordpassword. If the number of passwords Passwordpasswordpassword equals 1, then every input file TrainingFiletrainingFiletraining_file is checked with that password, otherwise the number of passwords has to be equal to the number of input files and the input file at position n is checked with the password at position n. For unprotected training files the passwords are ignored.

For a more detailed description of the operator’s functionality see select_feature_set_trainf_mlpSelectFeatureSetTrainfMlp. The concept of protecting OCR training data in HALCON is described in protect_ocr_trainfProtectOcrTrainf.

Attention🔗

This operator may take considerable time, depending on the size of the data set in the training file, and the number of features.

Please note, that this operator should not be called, if only a small set of training data is available. Due to the risk of overfitting the operator select_feature_set_trainf_mlp_protectedSelectFeatureSetTrainfMlpProtected may deliver a classifier with a very high score. However, the classifier may perform poorly when tested.

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🔗

TrainingFiletrainingFiletraining_file (input_control) filename.read(-array) → (string)HTuple (HString)HTuple (string)MaybeSequence[str]Htuple (char*)

Names of the training files.

Default: ''""
File extension: .trf, .otr

Passwordpasswordpassword (input_control) string(-array) → (string)HTuple (HString)HTuple (string)MaybeSequence[str]Htuple (char*)

Passwords for protected training files.

FeatureListfeatureListfeature_list (input_control) string(-array) → (string)HTuple (HString)HTuple (string)MaybeSequence[str]Htuple (char*)

List of features that should be considered for selection.

Default: ['zoom_factor', 'ratio', 'width', 'height', 'foreground', 'foreground_grid_9', 'foreground_grid_16', 'anisometry', 'compactness', 'convexity', 'moments_region_2nd_invar', 'moments_region_2nd_rel_invar', 'moments_region_3rd_invar', 'moments_central', 'phi', 'num_connect', 'num_holes', 'projection_horizontal', 'projection_vertical', 'projection_horizontal_invar', 'projection_vertical_invar', 'chord_histo', 'num_runs', 'pixel', 'pixel_invar', 'pixel_binary', 'gradient_8dir', 'cooc', 'moments_gray_plane']
List of values: 'anisometry', 'chord_histo', 'compactness', 'convexity', 'cooc', 'default', 'foreground', 'foreground_grid_16', 'foreground_grid_9', 'gradient_8dir', 'height', 'moments_central', 'moments_gray_plane', 'moments_region_2nd_invar', 'moments_region_2nd_rel_invar', 'moments_region_3rd_invar', 'num_connect', 'num_holes', 'num_runs', 'phi', 'pixel', 'pixel_binary', 'pixel_invar', 'projection_horizontal', 'projection_horizontal_invar', 'projection_vertical', 'projection_vertical_invar', 'ratio', 'width', 'zoom_factor'

SelectionMethodselectionMethodselection_method (input_control) string → (string)HTuple (HString)HTuple (string)strHtuple (char*)

Method to perform the selection.

Default: 'greedy'"greedy"
List of values: 'greedy', 'greedy_oscillating'"greedy", "greedy_oscillating"

Widthwidthwidth (input_control) integer → (integer)HTuple (Hlong)HTuple (int / long)intHtuple (Hlong)

Width of the rectangle to which the gray values of the segmented character are zoomed.

Default: 1515

Heightheightheight (input_control) integer → (integer)HTuple (Hlong)HTuple (int / long)intHtuple (Hlong)

Height of the rectangle to which the gray values of the segmented character are zoomed.

Default: 1616

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

Names of generic parameters to configure the selection process and the classifier.

Default: [][]
List of values: 'nu'"nu"

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

Values of generic parameters to configure the selection process and the classifier.

Default: [][]
Suggested values: '0.1'"0.1"

OCRHandleOCRHandleocrhandle (output_control) ocr_mlp → (handle)HTuple (HHandle)HOCRMlp, HTuple (IntPtr)HHandleHtuple (handle)

Trained OCR-MLP classifier.

FeatureSetfeatureSetfeature_set (output_control) string-array → (string)HTuple (HString)HTuple (string)Sequence[str]Htuple (char*)

Selected feature set, contains only entries from FeatureListfeatureListfeature_list.

Scorescorescore (output_control) real-array → (real)HTuple (double)HTuple (double)Sequence[float]Htuple (double)

Achieved score using tow-fold cross-validation.

Result🔗

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

Combinations with other operators🔗

Combinations

Possible predecessors

protect_ocr_trainfProtectOcrTrainf

Alternatives

select_feature_set_trainf_svm_protectedSelectFeatureSetTrainfSvmProtected

Module🔗

OCR/OCV

select_feature_set_trainf_mlp_protectedSelectFeatureSetTrainfMlpProtectedSelectFeatureSetTrainfMlpProtectedselect_feature_set_trainf_mlp_protectedT_select_feature_set_trainf_mlp_protected🔗