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tuning_params.h
Go to the documentation of this file.
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/**********************************************************************
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* File: tuning_params.h
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* Description: Declaration of the Tuning Parameters Base Class
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* Author: Ahmad Abdulkader
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* Created: 2008
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*
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* (C) Copyright 2008, Google Inc.
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** Licensed under the Apache License, Version 2.0 (the "License");
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** you may not use this file except in compliance with the License.
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** You may obtain a copy of the License at
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** http://www.apache.org/licenses/LICENSE-2.0
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** Unless required by applicable law or agreed to in writing, software
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** distributed under the License is distributed on an "AS IS" BASIS,
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** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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** See the License for the specific language governing permissions and
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** limitations under the License.
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*
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**********************************************************************/
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// The TuningParams class abstracts all the parameters that can be learned or
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// tuned during the training process. It is a base class that all TuningParams
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// classes should inherit from.
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#ifndef TUNING_PARAMS_H
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#define TUNING_PARAMS_H
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#include <string>
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#ifdef USE_STD_NAMESPACE
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using
std::string;
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#endif
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namespace
tesseract
{
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class
TuningParams
{
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public
:
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enum
type_classifer
{
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NN
,
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HYBRID_NN
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};
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enum
type_feature
{
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BMP
,
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CHEBYSHEV
,
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HYBRID
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};
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TuningParams
() {}
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virtual
~TuningParams
() {}
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// Accessor functions
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inline
double
RecoWgt
()
const
{
return
reco_wgt_
; }
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inline
double
SizeWgt
()
const
{
return
size_wgt_
; }
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inline
double
CharBigramWgt
()
const
{
return
char_bigrams_wgt_
; }
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inline
double
WordUnigramWgt
()
const
{
return
word_unigrams_wgt_
; }
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inline
int
MaxSegPerChar
()
const
{
return
max_seg_per_char_
; }
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inline
int
BeamWidth
()
const
{
return
beam_width_
; }
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inline
int
TypeClassifier
()
const
{
return
tp_classifier_
; }
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inline
int
TypeFeature
()
const
{
return
tp_feat_
; }
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inline
int
ConvGridSize
()
const
{
return
conv_grid_size_
; }
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inline
int
HistWindWid
()
const
{
return
hist_wind_wid_
; }
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inline
int
MinConCompSize
()
const
{
return
min_con_comp_size_
; }
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inline
double
MaxWordAspectRatio
()
const
{
return
max_word_aspect_ratio_
; }
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inline
double
MinSpaceHeightRatio
()
const
{
return
min_space_height_ratio_
; }
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inline
double
MaxSpaceHeightRatio
()
const
{
return
max_space_height_ratio_
; }
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inline
double
CombinerRunThresh
()
const
{
return
combiner_run_thresh_
; }
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inline
double
CombinerClassifierThresh
()
const
{
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return
combiner_classifier_thresh_
; }
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inline
void
SetRecoWgt
(
double
wgt) {
reco_wgt_
= wgt; }
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inline
void
SetSizeWgt
(
double
wgt) {
size_wgt_
= wgt; }
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inline
void
SetCharBigramWgt
(
double
wgt) {
char_bigrams_wgt_
= wgt; }
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inline
void
SetWordUnigramWgt
(
double
wgt) {
word_unigrams_wgt_
= wgt; }
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inline
void
SetMaxSegPerChar
(
int
max_seg_per_char) {
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max_seg_per_char_
= max_seg_per_char;
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}
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inline
void
SetBeamWidth
(
int
beam_width) {
beam_width_
= beam_width; }
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inline
void
SetTypeClassifier
(
type_classifer
tp_classifier) {
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tp_classifier_
= tp_classifier;
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}
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inline
void
SetTypeFeature
(
type_feature
tp_feat) {
tp_feat_
= tp_feat;}
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inline
void
SetHistWindWid
(
int
hist_wind_wid) {
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hist_wind_wid_
= hist_wind_wid;
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}
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virtual
bool
Save
(
string
file_name) = 0;
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virtual
bool
Load
(
string
file_name) = 0;
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protected
:
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// weight of recognition cost. This includes the language model cost
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double
reco_wgt_
;
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// weight of size cost
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double
size_wgt_
;
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// weight of character bigrams cost
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double
char_bigrams_wgt_
;
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// weight of word unigrams cost
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double
word_unigrams_wgt_
;
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// Maximum number of segments per character
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int
max_seg_per_char_
;
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// Beam width equal to the maximum number of nodes kept in the beam search
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// trellis column after pruning
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int
beam_width_
;
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// Classifier type: See enum type_classifer for classifier types
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type_classifer
tp_classifier_
;
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// Feature types: See enum type_feature for feature types
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type_feature
tp_feat_
;
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// Grid size to scale a grapheme bitmap used by the BMP feature type
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int
conv_grid_size_
;
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// Histogram window size as a ratio of the word height used in computing
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// the vertical pixel density histogram in the segmentation algorithm
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int
hist_wind_wid_
;
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// Minimum possible size of a connected component
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int
min_con_comp_size_
;
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// Maximum aspect ratio of a word (width / height)
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double
max_word_aspect_ratio_
;
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// Minimum ratio relative to the line height of a gap to be considered as
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// a word break
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double
min_space_height_ratio_
;
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// Maximum ratio relative to the line height of a gap to be considered as
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// a definite word break
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double
max_space_height_ratio_
;
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// When Cube and Tesseract are run in combined mode, only run
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// combiner classifier when tesseract confidence is below this
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// threshold. When Cube is run without Tesseract, this is ignored.
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double
combiner_run_thresh_
;
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// When Cube and tesseract are run in combined mode, threshold on
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// output of combiner binary classifier (chosen from ROC during
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// combiner training). When Cube is run without Tesseract, this is ignored.
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double
combiner_classifier_thresh_
;
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};
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}
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#endif // TUNING_PARAMS_H
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data
src
tesseract-ocr
cube
tuning_params.h
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