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tesseract/ccmain/tesseractclass.h
Ray Smith 0e868ef377 Major change to improve layout analysis for heavily diacritic languages: 
Tha, Vie, Kan, Tel etc.
There is a new overlap detector that detects when diacritics
cause a big increase in textline overlap. In such cases, diacritics from
overlap regions are kept separate from layout analysis completely, allowing
textline formation to happen without them. The diacritics are then assigned
to 0, 1 or 2 close words at the end of layout analysis, using and modifying
an old noise detection data path.
The stored diacritics are used or not during recognition according to the
character classifier's liking for them.
2015-05-12 16:47:02 -07:00

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///////////////////////////////////////////////////////////////////////
// File: tesseractclass.h
// Description: The Tesseract class. It holds/owns everything needed
// to run Tesseract on a single language, and also a set of
// sub-Tesseracts to run sub-languages. For thread safety, *every*
// global variable goes in here, directly, or indirectly.
// This makes it safe to run multiple Tesseracts in different
// threads in parallel, and keeps the different language
// instances separate.
// Author: Ray Smith
// Created: Fri Mar 07 08:17:01 PST 2008
//
// (C) Copyright 2008, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#ifndef TESSERACT_CCMAIN_TESSERACTCLASS_H__
#define TESSERACT_CCMAIN_TESSERACTCLASS_H__
#include "allheaders.h"
#include "control.h"
#include "docqual.h"
#include "devanagari_processing.h"
#include "genericvector.h"
#include "params.h"
#include "ocrclass.h"
#include "textord.h"
#include "wordrec.h"
class BLOB_CHOICE_LIST_CLIST;
class BLOCK_LIST;
class CharSamp;
struct OSResults;
class PAGE_RES;
class PAGE_RES_IT;
struct Pix;
class ROW;
class SVMenuNode;
class TBOX;
class TO_BLOCK_LIST;
class WERD;
class WERD_CHOICE;
class WERD_RES;
// Top-level class for all tesseract global instance data.
// This class either holds or points to all data used by an instance
// of Tesseract, including the memory allocator. When this is
// complete, Tesseract will be thread-safe. UNTIL THEN, IT IS NOT!
//
// NOTE to developers: Do not create cyclic dependencies through this class!
// The directory dependency tree must remain a tree! The keep this clean,
// lower-level code (eg in ccutil, the bottom level) must never need to
// know about the content of a higher-level directory.
// The following scheme will grant the easiest access to lower-level
// global members without creating a cyclic dependency:
//
// Class Hierarchy (^ = inheritance):
//
// CCUtil (ccutil/ccutil.h)
// ^ Members include: UNICHARSET
// CUtil (cutil/cutil_class.h)
// ^ Members include: TBLOB*, TEXTBLOCK*
// CCStruct (ccstruct/ccstruct.h)
// ^ Members include: Image
// Classify (classify/classify.h)
// ^ Members include: Dict
// WordRec (wordrec/wordrec.h)
// ^ Members include: WERD*, DENORM*
// Tesseract (ccmain/tesseractclass.h)
// Members include: Pix*, CubeRecoContext*,
// TesseractCubeCombiner*
//
// Other important classes:
//
// TessBaseAPI (api/baseapi.h)
// Members include: BLOCK_LIST*, PAGE_RES*,
// Tesseract*, ImageThresholder*
// Dict (dict/dict.h)
// Members include: Image* (private)
//
// NOTE: that each level contains members that correspond to global
// data that is defined (and used) at that level, not necessarily where
// the type is defined so for instance:
// BOOL_VAR_H(textord_show_blobs, false, "Display unsorted blobs");
// goes inside the Textord class, not the cc_util class.
namespace tesseract {
class ColumnFinder;
#ifndef ANDROID_BUILD
class CubeLineObject;
class CubeObject;
class CubeRecoContext;
#endif
class EquationDetect;
class Tesseract;
#ifndef ANDROID_BUILD
class TesseractCubeCombiner;
#endif
// A collection of various variables for statistics and debugging.
struct TesseractStats {
TesseractStats()
: adaption_word_number(0),
doc_blob_quality(0),
doc_outline_errs(0),
doc_char_quality(0),
good_char_count(0),
doc_good_char_quality(0),
word_count(0),
dict_words(0),
tilde_crunch_written(false),
last_char_was_newline(true),
last_char_was_tilde(false),
write_results_empty_block(true) {}
inT32 adaption_word_number;
inT16 doc_blob_quality;
inT16 doc_outline_errs;
inT16 doc_char_quality;
inT16 good_char_count;
inT16 doc_good_char_quality;
inT32 word_count; // count of word in the document
inT32 dict_words; // number of dicitionary words in the document
STRING dump_words_str; // accumulator used by dump_words()
// Flags used by write_results()
bool tilde_crunch_written;
bool last_char_was_newline;
bool last_char_was_tilde;
bool write_results_empty_block;
};
// Struct to hold all the pointers to relevant data for processing a word.
struct WordData {
WordData() : word(NULL), row(NULL), block(NULL), prev_word(NULL) {}
explicit WordData(const PAGE_RES_IT& page_res_it)
: word(page_res_it.word()), row(page_res_it.row()->row),
block(page_res_it.block()->block), prev_word(NULL) {}
WordData(BLOCK* block_in, ROW* row_in, WERD_RES* word_res)
: word(word_res), row(row_in), block(block_in), prev_word(NULL) {}
WERD_RES* word;
ROW* row;
BLOCK* block;
WordData* prev_word;
PointerVector<WERD_RES> lang_words;
};
// Definition of a Tesseract WordRecognizer. The WordData provides the context
// of row/block, in_word holds an initialized, possibly pre-classified word,
// that the recognizer may or may not consume (but if so it sets *in_word=NULL)
// and produces one or more output words in out_words, which may be the
// consumed in_word, or may be generated independently.
// This api allows both a conventional tesseract classifier to work, or a
// line-level classifier that generates multiple words from a merged input.
typedef void (Tesseract::*WordRecognizer)(const WordData& word_data,
WERD_RES** in_word,
PointerVector<WERD_RES>* out_words);
class Tesseract : public Wordrec {
public:
Tesseract();
~Tesseract();
// Clear as much used memory as possible without resetting the adaptive
// classifier or losing any other classifier data.
void Clear();
// Clear all memory of adaption for this and all subclassifiers.
void ResetAdaptiveClassifier();
// Clear the document dictionary for this and all subclassifiers.
void ResetDocumentDictionary();
// Set the equation detector.
void SetEquationDetect(EquationDetect* detector);
// Simple accessors.
const FCOORD& reskew() const {
return reskew_;
}
// Destroy any existing pix and return a pointer to the pointer.
Pix** mutable_pix_binary() {
Clear();
return &pix_binary_;
}
Pix* pix_binary() const {
return pix_binary_;
}
Pix* pix_grey() const {
return pix_grey_;
}
void set_pix_grey(Pix* grey_pix) {
pixDestroy(&pix_grey_);
pix_grey_ = grey_pix;
}
// Returns a pointer to a Pix representing the best available image of the
// page. The image will be 8-bit grey if the input was grey or color. Note
// that in grey 0 is black and 255 is white. If the input was binary, then
// the returned Pix will be binary. Note that here black is 1 and white is 0.
// To tell the difference pixGetDepth() will return 8 or 1.
// In either case, the return value is a borrowed Pix, and should not be
// deleted or pixDestroyed.
Pix* BestPix() const {
return pix_grey_ != NULL ? pix_grey_ : pix_binary_;
}
void set_pix_thresholds(Pix* thresholds) {
pixDestroy(&pix_thresholds_);
pix_thresholds_ = thresholds;
}
int source_resolution() const {
return source_resolution_;
}
void set_source_resolution(int ppi) {
source_resolution_ = ppi;
}
int ImageWidth() const {
return pixGetWidth(pix_binary_);
}
int ImageHeight() const {
return pixGetHeight(pix_binary_);
}
Pix* scaled_color() const {
return scaled_color_;
}
int scaled_factor() const {
return scaled_factor_;
}
void SetScaledColor(int factor, Pix* color) {
scaled_factor_ = factor;
scaled_color_ = color;
}
const Textord& textord() const {
return textord_;
}
Textord* mutable_textord() {
return &textord_;
}
bool right_to_left() const {
return right_to_left_;
}
int num_sub_langs() const {
return sub_langs_.size();
}
Tesseract* get_sub_lang(int index) const {
return sub_langs_[index];
}
// Returns true if any language uses Tesseract (as opposed to cube).
bool AnyTessLang() const {
if (tessedit_ocr_engine_mode != OEM_CUBE_ONLY) return true;
for (int i = 0; i < sub_langs_.size(); ++i) {
if (sub_langs_[i]->tessedit_ocr_engine_mode != OEM_CUBE_ONLY)
return true;
}
return false;
}
void SetBlackAndWhitelist();
// Perform steps to prepare underlying binary image/other data structures for
// page segmentation. Uses the strategy specified in the global variable
// pageseg_devanagari_split_strategy for perform splitting while preparing for
// page segmentation.
void PrepareForPageseg();
// Perform steps to prepare underlying binary image/other data structures for
// Tesseract OCR. The current segmentation is required by this method.
// Uses the strategy specified in the global variable
// ocr_devanagari_split_strategy for performing splitting while preparing for
// Tesseract ocr.
void PrepareForTessOCR(BLOCK_LIST* block_list,
Tesseract* osd_tess, OSResults* osr);
int SegmentPage(const STRING* input_file, BLOCK_LIST* blocks,
Tesseract* osd_tess, OSResults* osr);
void SetupWordScripts(BLOCK_LIST* blocks);
int AutoPageSeg(PageSegMode pageseg_mode, BLOCK_LIST* blocks,
TO_BLOCK_LIST* to_blocks, BLOBNBOX_LIST* diacritic_blobs,
Tesseract* osd_tess, OSResults* osr);
ColumnFinder* SetupPageSegAndDetectOrientation(
bool single_column, bool osd, bool only_osd,
BLOCK_LIST* blocks, Tesseract* osd_tess, OSResults* osr,
TO_BLOCK_LIST* to_blocks, Pix** photo_mask_pix, Pix** music_mask_pix);
// par_control.cpp
void PrerecAllWordsPar(const GenericVector<WordData>& words);
//// control.h /////////////////////////////////////////////////////////
bool ProcessTargetWord(const TBOX& word_box, const TBOX& target_word_box,
const char* word_config, int pass);
// Sets up the words ready for whichever engine is to be run
void SetupAllWordsPassN(int pass_n,
const TBOX* target_word_box,
const char* word_config,
PAGE_RES* page_res,
GenericVector<WordData>* words);
// Sets up the single word ready for whichever engine is to be run.
void SetupWordPassN(int pass_n, WordData* word);
// Runs word recognition on all the words.
bool RecogAllWordsPassN(int pass_n, ETEXT_DESC* monitor,
PAGE_RES_IT* pr_it,
GenericVector<WordData>* words);
bool recog_all_words(PAGE_RES* page_res,
ETEXT_DESC* monitor,
const TBOX* target_word_box,
const char* word_config,
int dopasses);
void rejection_passes(PAGE_RES* page_res,
ETEXT_DESC* monitor,
const TBOX* target_word_box,
const char* word_config);
void bigram_correction_pass(PAGE_RES *page_res);
void blamer_pass(PAGE_RES* page_res);
// Sets script positions and detects smallcaps on all output words.
void script_pos_pass(PAGE_RES* page_res);
// Helper to recognize the word using the given (language-specific) tesseract.
// Returns positive if this recognizer found more new best words than the
// number kept from best_words.
int RetryWithLanguage(const WordData& word_data,
WordRecognizer recognizer,
WERD_RES** in_word,
PointerVector<WERD_RES>* best_words);
// Moves good-looking "noise"/diacritics from the reject list to the main
// blob list on the current word. Returns true if anything was done, and
// sets make_next_word_fuzzy if blob(s) were added to the end of the word.
bool ReassignDiacritics(int pass, PAGE_RES_IT* pr_it,
bool* make_next_word_fuzzy);
// Attempts to put noise/diacritic outlines into the blobs that they overlap.
// Input: a set of noisy outlines that probably belong to the real_word.
// Output: outlines that overlapped blobs are set to NULL and put back into
// the word, either in the blobs or in the reject list.
void AssignDiacriticsToOverlappingBlobs(
const GenericVector<C_OUTLINE*>& outlines, int pass, WERD* real_word,
PAGE_RES_IT* pr_it, GenericVector<bool>* word_wanted,
GenericVector<bool>* overlapped_any_blob,
GenericVector<C_BLOB*>* target_blobs);
// Attempts to assign non-overlapping outlines to their nearest blobs or
// make new blobs out of them.
void AssignDiacriticsToNewBlobs(const GenericVector<C_OUTLINE*>& outlines,
int pass, WERD* real_word, PAGE_RES_IT* pr_it,
GenericVector<bool>* word_wanted,
GenericVector<C_BLOB*>* target_blobs);
// Starting with ok_outlines set to indicate which outlines overlap the blob,
// chooses the optimal set (approximately) and returns true if any outlines
// are desired, in which case ok_outlines indicates which ones.
bool SelectGoodDiacriticOutlines(int pass, float certainty_threshold,
PAGE_RES_IT* pr_it, C_BLOB* blob,
const GenericVector<C_OUTLINE*>& outlines,
int num_outlines,
GenericVector<bool>* ok_outlines);
// Classifies the given blob plus the outlines flagged by ok_outlines, undoes
// the inclusion of the outlines, and returns the certainty of the raw choice.
float ClassifyBlobPlusOutlines(const GenericVector<bool>& ok_outlines,
const GenericVector<C_OUTLINE*>& outlines,
int pass_n, PAGE_RES_IT* pr_it, C_BLOB* blob,
STRING* best_str);
// Classifies the given blob (part of word_data->word->word) as an individual
// word, using languages, chopper etc, returning only the certainty of the
// best raw choice, and undoing all the work done to fake out the word.
float ClassifyBlobAsWord(int pass_n, PAGE_RES_IT* pr_it, C_BLOB* blob,
STRING* best_str, float* c2);
void classify_word_and_language(int pass_n, PAGE_RES_IT* pr_it,
WordData* word_data);
void classify_word_pass1(const WordData& word_data,
WERD_RES** in_word,
PointerVector<WERD_RES>* out_words);
void recog_pseudo_word(PAGE_RES* page_res, // blocks to check
TBOX &selection_box);
void fix_rep_char(PAGE_RES_IT* page_res_it);
ACCEPTABLE_WERD_TYPE acceptable_word_string(const UNICHARSET& char_set,
const char *s,
const char *lengths);
void match_word_pass_n(int pass_n, WERD_RES *word, ROW *row, BLOCK* block);
void classify_word_pass2(const WordData& word_data,
WERD_RES** in_word,
PointerVector<WERD_RES>* out_words);
void ReportXhtFixResult(bool accept_new_word, float new_x_ht,
WERD_RES* word, WERD_RES* new_word);
bool RunOldFixXht(WERD_RES *word, BLOCK* block, ROW *row);
bool TrainedXheightFix(WERD_RES *word, BLOCK* block, ROW *row);
// Runs recognition with the test baseline shift and x-height and returns true
// if there was an improvement in recognition result.
bool TestNewNormalization(int original_misfits, float baseline_shift,
float new_x_ht, WERD_RES *word, BLOCK* block,
ROW *row);
BOOL8 recog_interactive(PAGE_RES_IT* pr_it);
// Set fonts of this word.
void set_word_fonts(WERD_RES *word);
void font_recognition_pass(PAGE_RES* page_res);
void dictionary_correction_pass(PAGE_RES* page_res);
BOOL8 check_debug_pt(WERD_RES *word, int location);
//// superscript.cpp ////////////////////////////////////////////////////
bool SubAndSuperscriptFix(WERD_RES *word_res);
void GetSubAndSuperscriptCandidates(const WERD_RES *word,
int *num_rebuilt_leading,
ScriptPos *leading_pos,
float *leading_certainty,
int *num_rebuilt_trailing,
ScriptPos *trailing_pos,
float *trailing_certainty,
float *avg_certainty,
float *unlikely_threshold);
WERD_RES *TrySuperscriptSplits(int num_chopped_leading,
float leading_certainty,
ScriptPos leading_pos,
int num_chopped_trailing,
float trailing_certainty,
ScriptPos trailing_pos,
WERD_RES *word,
bool *is_good,
int *retry_leading,
int *retry_trailing);
bool BelievableSuperscript(bool debug,
const WERD_RES &word,
float certainty_threshold,
int *left_ok,
int *right_ok) const;
//// cube_control.cpp ///////////////////////////////////////////////////
#ifndef ANDROID_BUILD
bool init_cube_objects(bool load_combiner,
TessdataManager *tessdata_manager);
// Iterates through tesseract's results and calls cube on each word,
// combining the results with the existing tesseract result.
void run_cube_combiner(PAGE_RES *page_res);
// Recognizes a single word using (only) cube. Compatible with
// Tesseract's classify_word_pass1/classify_word_pass2.
void cube_word_pass1(BLOCK* block, ROW *row, WERD_RES *word);
// Cube recognizer to recognize a single word as with classify_word_pass1
// but also returns the cube object in case the combiner is needed.
CubeObject* cube_recognize_word(BLOCK* block, WERD_RES* word);
// Combines the cube and tesseract results for a single word, leaving the
// result in tess_word.
void cube_combine_word(CubeObject* cube_obj, WERD_RES* cube_word,
WERD_RES* tess_word);
// Call cube on the current word, and write the result to word.
// Sets up a fake result and returns false if something goes wrong.
bool cube_recognize(CubeObject *cube_obj, BLOCK* block, WERD_RES *word);
void fill_werd_res(const BoxWord& cube_box_word,
const char* cube_best_str,
WERD_RES* tess_werd_res);
bool extract_cube_state(CubeObject* cube_obj, int* num_chars,
Boxa** char_boxes, CharSamp*** char_samples);
bool create_cube_box_word(Boxa *char_boxes, int num_chars,
TBOX word_box, BoxWord* box_word);
#endif
//// output.h //////////////////////////////////////////////////////////
void output_pass(PAGE_RES_IT &page_res_it, const TBOX *target_word_box);
void write_results(PAGE_RES_IT &page_res_it, // full info
char newline_type, // type of newline
BOOL8 force_eol // override tilde crunch?
);
void set_unlv_suspects(WERD_RES *word);
UNICHAR_ID get_rep_char(WERD_RES *word); // what char is repeated?
BOOL8 acceptable_number_string(const char *s,
const char *lengths);
inT16 count_alphanums(const WERD_CHOICE &word);
inT16 count_alphas(const WERD_CHOICE &word);
//// tessedit.h ////////////////////////////////////////////////////////
void read_config_file(const char *filename, SetParamConstraint constraint);
// Initialize for potentially a set of languages defined by the language
// string and recursively any additional languages required by any language
// traineddata file (via tessedit_load_sublangs in its config) that is loaded.
// See init_tesseract_internal for args.
int init_tesseract(const char *arg0,
const char *textbase,
const char *language,
OcrEngineMode oem,
char **configs,
int configs_size,
const GenericVector<STRING> *vars_vec,
const GenericVector<STRING> *vars_values,
bool set_only_init_params);
int init_tesseract(const char *datapath,
const char *language,
OcrEngineMode oem) {
return init_tesseract(datapath, NULL, language, oem,
NULL, 0, NULL, NULL, false);
}
// Common initialization for a single language.
// arg0 is the datapath for the tessdata directory, which could be the
// path of the tessdata directory with no trailing /, or (if tessdata
// lives in the same directory as the executable, the path of the executable,
// hence the name arg0.
// textbase is an optional output file basename (used only for training)
// language is the language code to load.
// oem controls which engine(s) will operate on the image
// configs (argv) is an array of config filenames to load variables from.
// May be NULL.
// configs_size (argc) is the number of elements in configs.
// vars_vec is an optional vector of variables to set.
// vars_values is an optional corresponding vector of values for the variables
// in vars_vec.
// If set_only_init_params is true, then only the initialization variables
// will be set.
int init_tesseract_internal(const char *arg0,
const char *textbase,
const char *language,
OcrEngineMode oem,
char **configs,
int configs_size,
const GenericVector<STRING> *vars_vec,
const GenericVector<STRING> *vars_values,
bool set_only_init_params);
// Set the universal_id member of each font to be unique among all
// instances of the same font loaded.
void SetupUniversalFontIds();
int init_tesseract_lm(const char *arg0,
const char *textbase,
const char *language);
void recognize_page(STRING& image_name);
void end_tesseract();
bool init_tesseract_lang_data(const char *arg0,
const char *textbase,
const char *language,
OcrEngineMode oem,
char **configs,
int configs_size,
const GenericVector<STRING> *vars_vec,
const GenericVector<STRING> *vars_values,
bool set_only_init_params);
void ParseLanguageString(const char* lang_str,
GenericVector<STRING>* to_load,
GenericVector<STRING>* not_to_load);
//// pgedit.h //////////////////////////////////////////////////////////
SVMenuNode *build_menu_new();
#ifndef GRAPHICS_DISABLED
void pgeditor_main(int width, int height, PAGE_RES* page_res);
#endif // GRAPHICS_DISABLED
void process_image_event( // action in image win
const SVEvent &event);
BOOL8 process_cmd_win_event( // UI command semantics
inT32 cmd_event, // which menu item?
char *new_value // any prompt data
);
void debug_word(PAGE_RES* page_res, const TBOX &selection_box);
void do_re_display(
BOOL8 (tesseract::Tesseract::*word_painter)(PAGE_RES_IT* pr_it));
BOOL8 word_display(PAGE_RES_IT* pr_it);
BOOL8 word_bln_display(PAGE_RES_IT* pr_it);
BOOL8 word_blank_and_set_display(PAGE_RES_IT* pr_its);
BOOL8 word_set_display(PAGE_RES_IT* pr_it);
// #ifndef GRAPHICS_DISABLED
BOOL8 word_dumper(PAGE_RES_IT* pr_it);
// #endif // GRAPHICS_DISABLED
void blob_feature_display(PAGE_RES* page_res, const TBOX& selection_box);
//// reject.h //////////////////////////////////////////////////////////
// make rej map for word
void make_reject_map(WERD_RES *word, ROW *row, inT16 pass);
BOOL8 one_ell_conflict(WERD_RES *word_res, BOOL8 update_map);
inT16 first_alphanum_index(const char *word,
const char *word_lengths);
inT16 first_alphanum_offset(const char *word,
const char *word_lengths);
inT16 alpha_count(const char *word,
const char *word_lengths);
BOOL8 word_contains_non_1_digit(const char *word,
const char *word_lengths);
void dont_allow_1Il(WERD_RES *word);
inT16 count_alphanums( //how many alphanums
WERD_RES *word);
void flip_0O(WERD_RES *word);
BOOL8 non_0_digit(const UNICHARSET& ch_set, UNICHAR_ID unichar_id);
BOOL8 non_O_upper(const UNICHARSET& ch_set, UNICHAR_ID unichar_id);
BOOL8 repeated_nonalphanum_wd(WERD_RES *word, ROW *row);
void nn_match_word( //Match a word
WERD_RES *word,
ROW *row);
void nn_recover_rejects(WERD_RES *word, ROW *row);
void set_done( //set done flag
WERD_RES *word,
inT16 pass);
inT16 safe_dict_word(const WERD_RES *werd_res); // is best_choice in dict?
void flip_hyphens(WERD_RES *word);
void reject_I_1_L(WERD_RES *word);
void reject_edge_blobs(WERD_RES *word);
void reject_mostly_rejects(WERD_RES *word);
//// adaptions.h ///////////////////////////////////////////////////////
BOOL8 word_adaptable( //should we adapt?
WERD_RES *word,
uinT16 mode);
//// tfacepp.cpp ///////////////////////////////////////////////////////
void recog_word_recursive(WERD_RES* word);
void recog_word(WERD_RES *word);
void split_and_recog_word(WERD_RES* word);
void split_word(WERD_RES *word,
int split_pt,
WERD_RES **right_piece,
BlamerBundle **orig_blamer_bundle) const;
void join_words(WERD_RES *word,
WERD_RES *word2,
BlamerBundle *orig_bb) const;
//// fixspace.cpp ///////////////////////////////////////////////////////
BOOL8 digit_or_numeric_punct(WERD_RES *word, int char_position);
inT16 eval_word_spacing(WERD_RES_LIST &word_res_list);
void match_current_words(WERD_RES_LIST &words, ROW *row, BLOCK* block);
inT16 fp_eval_word_spacing(WERD_RES_LIST &word_res_list);
void fix_noisy_space_list(WERD_RES_LIST &best_perm, ROW *row, BLOCK* block);
void fix_fuzzy_space_list(WERD_RES_LIST &best_perm, ROW *row, BLOCK* block);
void fix_sp_fp_word(WERD_RES_IT &word_res_it, ROW *row, BLOCK* block);
void fix_fuzzy_spaces( //find fuzzy words
ETEXT_DESC *monitor, //progress monitor
inT32 word_count, //count of words in doc
PAGE_RES *page_res);
void dump_words(WERD_RES_LIST &perm, inT16 score,
inT16 mode, BOOL8 improved);
BOOL8 fixspace_thinks_word_done(WERD_RES *word);
inT16 worst_noise_blob(WERD_RES *word_res, float *worst_noise_score);
float blob_noise_score(TBLOB *blob);
void break_noisiest_blob_word(WERD_RES_LIST &words);
//// docqual.cpp ////////////////////////////////////////////////////////
GARBAGE_LEVEL garbage_word(WERD_RES *word, BOOL8 ok_dict_word);
BOOL8 potential_word_crunch(WERD_RES *word,
GARBAGE_LEVEL garbage_level,
BOOL8 ok_dict_word);
void tilde_crunch(PAGE_RES_IT &page_res_it);
void unrej_good_quality_words( //unreject potential
PAGE_RES_IT &page_res_it);
void doc_and_block_rejection( //reject big chunks
PAGE_RES_IT &page_res_it,
BOOL8 good_quality_doc);
void quality_based_rejection(PAGE_RES_IT &page_res_it,
BOOL8 good_quality_doc);
void convert_bad_unlv_chs(WERD_RES *word_res);
void tilde_delete(PAGE_RES_IT &page_res_it);
inT16 word_blob_quality(WERD_RES *word, ROW *row);
void word_char_quality(WERD_RES *word, ROW *row, inT16 *match_count,
inT16 *accepted_match_count);
void unrej_good_chs(WERD_RES *word, ROW *row);
inT16 count_outline_errs(char c, inT16 outline_count);
inT16 word_outline_errs(WERD_RES *word);
BOOL8 terrible_word_crunch(WERD_RES *word, GARBAGE_LEVEL garbage_level);
CRUNCH_MODE word_deletable(WERD_RES *word, inT16 &delete_mode);
inT16 failure_count(WERD_RES *word);
BOOL8 noise_outlines(TWERD *word);
//// pagewalk.cpp ///////////////////////////////////////////////////////
void
process_selected_words (
PAGE_RES* page_res, // blocks to check
//function to call
TBOX & selection_box,
BOOL8 (tesseract::Tesseract::*word_processor)(PAGE_RES_IT* pr_it));
//// tessbox.cpp ///////////////////////////////////////////////////////
void tess_add_doc_word( //test acceptability
WERD_CHOICE *word_choice //after context
);
void tess_segment_pass_n(int pass_n, WERD_RES *word);
bool tess_acceptable_word(WERD_RES *word);
//// applybox.cpp //////////////////////////////////////////////////////
// Applies the box file based on the image name fname, and resegments
// the words in the block_list (page), with:
// blob-mode: one blob per line in the box file, words as input.
// word/line-mode: one blob per space-delimited unit after the #, and one word
// per line in the box file. (See comment above for box file format.)
// If find_segmentation is true, (word/line mode) then the classifier is used
// to re-segment words/lines to match the space-delimited truth string for
// each box. In this case, the input box may be for a word or even a whole
// text line, and the output words will contain multiple blobs corresponding
// to the space-delimited input string.
// With find_segmentation false, no classifier is needed, but the chopper
// can still be used to correctly segment touching characters with the help
// of the input boxes.
// In the returned PAGE_RES, the WERD_RES are setup as they would be returned
// from normal classification, ie. with a word, chopped_word, rebuild_word,
// seam_array, denorm, box_word, and best_state, but NO best_choice or
// raw_choice, as they would require a UNICHARSET, which we aim to avoid.
// Instead, the correct_text member of WERD_RES is set, and this may be later
// converted to a best_choice using CorrectClassifyWords. CorrectClassifyWords
// is not required before calling ApplyBoxTraining.
PAGE_RES* ApplyBoxes(const STRING& fname, bool find_segmentation,
BLOCK_LIST *block_list);
// Any row xheight that is significantly different from the median is set
// to the median.
void PreenXHeights(BLOCK_LIST *block_list);
// Builds a PAGE_RES from the block_list in the way required for ApplyBoxes:
// All fuzzy spaces are removed, and all the words are maximally chopped.
PAGE_RES* SetupApplyBoxes(const GenericVector<TBOX>& boxes,
BLOCK_LIST *block_list);
// Tests the chopper by exhaustively running chop_one_blob.
// The word_res will contain filled chopped_word, seam_array, denorm,
// box_word and best_state for the maximally chopped word.
void MaximallyChopWord(const GenericVector<TBOX>& boxes,
BLOCK* block, ROW* row, WERD_RES* word_res);
// Gather consecutive blobs that match the given box into the best_state
// and corresponding correct_text.
// Fights over which box owns which blobs are settled by pre-chopping and
// applying the blobs to box or next_box with the least non-overlap.
// Returns false if the box was in error, which can only be caused by
// failing to find an appropriate blob for a box.
// This means that occasionally, blobs may be incorrectly segmented if the
// chopper fails to find a suitable chop point.
bool ResegmentCharBox(PAGE_RES* page_res, const TBOX *prev_box,
const TBOX& box, const TBOX& next_box,
const char* correct_text);
// Consume all source blobs that strongly overlap the given box,
// putting them into a new word, with the correct_text label.
// Fights over which box owns which blobs are settled by
// applying the blobs to box or next_box with the least non-overlap.
// Returns false if the box was in error, which can only be caused by
// failing to find an overlapping blob for a box.
bool ResegmentWordBox(BLOCK_LIST *block_list,
const TBOX& box, const TBOX& next_box,
const char* correct_text);
// Resegments the words by running the classifier in an attempt to find the
// correct segmentation that produces the required string.
void ReSegmentByClassification(PAGE_RES* page_res);
// Converts the space-delimited string of utf8 text to a vector of UNICHAR_ID.
// Returns false if an invalid UNICHAR_ID is encountered.
bool ConvertStringToUnichars(const char* utf8,
GenericVector<UNICHAR_ID>* class_ids);
// Resegments the word to achieve the target_text from the classifier.
// Returns false if the re-segmentation fails.
// Uses brute-force combination of upto kMaxGroupSize adjacent blobs, and
// applies a full search on the classifier results to find the best classified
// segmentation. As a compromise to obtain better recall, 1-1 ambigiguity
// substitutions ARE used.
bool FindSegmentation(const GenericVector<UNICHAR_ID>& target_text,
WERD_RES* word_res);
// Recursive helper to find a match to the target_text (from text_index
// position) in the choices (from choices_pos position).
// Choices is an array of GenericVectors, of length choices_length, with each
// element representing a starting position in the word, and the
// GenericVector holding classification results for a sequence of consecutive
// blobs, with index 0 being a single blob, index 1 being 2 blobs etc.
void SearchForText(const GenericVector<BLOB_CHOICE_LIST*>* choices,
int choices_pos, int choices_length,
const GenericVector<UNICHAR_ID>& target_text,
int text_index,
float rating, GenericVector<int>* segmentation,
float* best_rating, GenericVector<int>* best_segmentation);
// Counts up the labelled words and the blobs within.
// Deletes all unused or emptied words, counting the unused ones.
// Resets W_BOL and W_EOL flags correctly.
// Builds the rebuild_word and rebuilds the box_word.
void TidyUp(PAGE_RES* page_res);
// Logs a bad box by line in the box file and box coords.
void ReportFailedBox(int boxfile_lineno, TBOX box, const char *box_ch,
const char *err_msg);
// Creates a fake best_choice entry in each WERD_RES with the correct text.
void CorrectClassifyWords(PAGE_RES* page_res);
// Call LearnWord to extract features for labelled blobs within each word.
// Features are stored in an internal buffer.
void ApplyBoxTraining(const STRING& fontname, PAGE_RES* page_res);
//// fixxht.cpp ///////////////////////////////////////////////////////
// Returns the number of misfit blob tops in this word.
int CountMisfitTops(WERD_RES *word_res);
// Returns a new x-height in pixels (original image coords) that is
// maximally compatible with the result in word_res.
// Returns 0.0f if no x-height is found that is better than the current
// estimate.
float ComputeCompatibleXheight(WERD_RES *word_res, float* baseline_shift);
//// Data members ///////////////////////////////////////////////////////
// TODO(ocr-team): Find and remove obsolete parameters.
BOOL_VAR_H(tessedit_resegment_from_boxes, false,
"Take segmentation and labeling from box file");
BOOL_VAR_H(tessedit_resegment_from_line_boxes, false,
"Conversion of word/line box file to char box file");
BOOL_VAR_H(tessedit_train_from_boxes, false,
"Generate training data from boxed chars");
BOOL_VAR_H(tessedit_make_boxes_from_boxes, false,
"Generate more boxes from boxed chars");
BOOL_VAR_H(tessedit_dump_pageseg_images, false,
"Dump intermediate images made during page segmentation");
INT_VAR_H(tessedit_pageseg_mode, PSM_SINGLE_BLOCK,
"Page seg mode: 0=osd only, 1=auto+osd, 2=auto, 3=col, 4=block,"
" 5=line, 6=word, 7=char"
" (Values from PageSegMode enum in publictypes.h)");
INT_VAR_H(tessedit_ocr_engine_mode, tesseract::OEM_TESSERACT_ONLY,
"Which OCR engine(s) to run (Tesseract, Cube, both). Defaults"
" to loading and running only Tesseract (no Cube, no combiner)."
" (Values from OcrEngineMode enum in tesseractclass.h)");
STRING_VAR_H(tessedit_char_blacklist, "",
"Blacklist of chars not to recognize");
STRING_VAR_H(tessedit_char_whitelist, "",
"Whitelist of chars to recognize");
STRING_VAR_H(tessedit_char_unblacklist, "",
"List of chars to override tessedit_char_blacklist");
BOOL_VAR_H(tessedit_ambigs_training, false,
"Perform training for ambiguities");
INT_VAR_H(pageseg_devanagari_split_strategy,
tesseract::ShiroRekhaSplitter::NO_SPLIT,
"Whether to use the top-line splitting process for Devanagari "
"documents while performing page-segmentation.");
INT_VAR_H(ocr_devanagari_split_strategy,
tesseract::ShiroRekhaSplitter::NO_SPLIT,
"Whether to use the top-line splitting process for Devanagari "
"documents while performing ocr.");
STRING_VAR_H(tessedit_write_params_to_file, "",
"Write all parameters to the given file.");
BOOL_VAR_H(tessedit_adaption_debug, false,
"Generate and print debug information for adaption");
INT_VAR_H(bidi_debug, 0, "Debug level for BiDi");
INT_VAR_H(applybox_debug, 1, "Debug level");
INT_VAR_H(applybox_page, 0, "Page number to apply boxes from");
STRING_VAR_H(applybox_exposure_pattern, ".exp",
"Exposure value follows this pattern in the image"
" filename. The name of the image files are expected"
" to be in the form [lang].[fontname].exp[num].tif");
BOOL_VAR_H(applybox_learn_chars_and_char_frags_mode, false,
"Learn both character fragments (as is done in the"
" special low exposure mode) as well as unfragmented"
" characters.");
BOOL_VAR_H(applybox_learn_ngrams_mode, false,
"Each bounding box is assumed to contain ngrams. Only"
" learn the ngrams whose outlines overlap horizontally.");
BOOL_VAR_H(tessedit_display_outwords, false, "Draw output words");
BOOL_VAR_H(tessedit_dump_choices, false, "Dump char choices");
BOOL_VAR_H(tessedit_timing_debug, false, "Print timing stats");
BOOL_VAR_H(tessedit_fix_fuzzy_spaces, true,
"Try to improve fuzzy spaces");
BOOL_VAR_H(tessedit_unrej_any_wd, false,
"Dont bother with word plausibility");
BOOL_VAR_H(tessedit_fix_hyphens, true, "Crunch double hyphens?");
BOOL_VAR_H(tessedit_redo_xheight, true, "Check/Correct x-height");
BOOL_VAR_H(tessedit_enable_doc_dict, true,
"Add words to the document dictionary");
BOOL_VAR_H(tessedit_debug_fonts, false, "Output font info per char");
BOOL_VAR_H(tessedit_debug_block_rejection, false, "Block and Row stats");
BOOL_VAR_H(tessedit_enable_bigram_correction, true,
"Enable correction based on the word bigram dictionary.");
BOOL_VAR_H(tessedit_enable_dict_correction, false,
"Enable single word correction based on the dictionary.");
INT_VAR_H(tessedit_bigram_debug, 0, "Amount of debug output for bigram "
"correction.");
BOOL_VAR_H(enable_noise_removal, true,
"Remove and conditionally reassign small outlines when they"
" confuse layout analysis, determining diacritics vs noise");
INT_VAR_H(debug_noise_removal, 0, "Debug reassignment of small outlines");
// Worst (min) certainty, for which a diacritic is allowed to make the base
// character worse and still be included.
double_VAR_H(noise_cert_basechar, -8.0, "Hingepoint for base char certainty");
// Worst (min) certainty, for which a non-overlapping diacritic is allowed to
// make the base character worse and still be included.
double_VAR_H(noise_cert_disjoint, -2.5, "Hingepoint for disjoint certainty");
// Worst (min) certainty, for which a diacritic is allowed to make a new
// stand-alone blob.
double_VAR_H(noise_cert_punc, -2.5, "Threshold for new punc char certainty");
// Factor of certainty margin for adding diacritics to not count as worse.
double_VAR_H(noise_cert_factor, 0.375,
"Scaling on certainty diff from Hingepoint");
INT_VAR_H(noise_maxperblob, 8, "Max diacritics to apply to a blob");
INT_VAR_H(noise_maxperword, 16, "Max diacritics to apply to a word");
INT_VAR_H(debug_x_ht_level, 0, "Reestimate debug");
BOOL_VAR_H(debug_acceptable_wds, false, "Dump word pass/fail chk");
STRING_VAR_H(chs_leading_punct, "('`\"", "Leading punctuation");
STRING_VAR_H(chs_trailing_punct1, ").,;:?!", "1st Trailing punctuation");
STRING_VAR_H(chs_trailing_punct2, ")'`\"", "2nd Trailing punctuation");
double_VAR_H(quality_rej_pc, 0.08, "good_quality_doc lte rejection limit");
double_VAR_H(quality_blob_pc, 0.0, "good_quality_doc gte good blobs limit");
double_VAR_H(quality_outline_pc, 1.0,
"good_quality_doc lte outline error limit");
double_VAR_H(quality_char_pc, 0.95, "good_quality_doc gte good char limit");
INT_VAR_H(quality_min_initial_alphas_reqd, 2, "alphas in a good word");
INT_VAR_H(tessedit_tess_adaption_mode, 0x27,
"Adaptation decision algorithm for tess");
BOOL_VAR_H(tessedit_minimal_rej_pass1, false,
"Do minimal rejection on pass 1 output");
BOOL_VAR_H(tessedit_test_adaption, false, "Test adaption criteria");
BOOL_VAR_H(tessedit_matcher_log, false, "Log matcher activity");
INT_VAR_H(tessedit_test_adaption_mode, 3,
"Adaptation decision algorithm for tess");
BOOL_VAR_H(test_pt, false, "Test for point");
double_VAR_H(test_pt_x, 99999.99, "xcoord");
double_VAR_H(test_pt_y, 99999.99, "ycoord");
INT_VAR_H(paragraph_debug_level, 0, "Print paragraph debug info.");
BOOL_VAR_H(paragraph_text_based, true,
"Run paragraph detection on the post-text-recognition "
"(more accurate)");
INT_VAR_H(cube_debug_level, 1, "Print cube debug info.");
STRING_VAR_H(outlines_odd, "%| ", "Non standard number of outlines");
STRING_VAR_H(outlines_2, "ij!?%\":;", "Non standard number of outlines");
BOOL_VAR_H(docqual_excuse_outline_errs, false,
"Allow outline errs in unrejection?");
BOOL_VAR_H(tessedit_good_quality_unrej, true,
"Reduce rejection on good docs");
BOOL_VAR_H(tessedit_use_reject_spaces, true, "Reject spaces?");
double_VAR_H(tessedit_reject_doc_percent, 65.00,
"%rej allowed before rej whole doc");
double_VAR_H(tessedit_reject_block_percent, 45.00,
"%rej allowed before rej whole block");
double_VAR_H(tessedit_reject_row_percent, 40.00,
"%rej allowed before rej whole row");
double_VAR_H(tessedit_whole_wd_rej_row_percent, 70.00,
"Number of row rejects in whole word rejects"
"which prevents whole row rejection");
BOOL_VAR_H(tessedit_preserve_blk_rej_perfect_wds, true,
"Only rej partially rejected words in block rejection");
BOOL_VAR_H(tessedit_preserve_row_rej_perfect_wds, true,
"Only rej partially rejected words in row rejection");
BOOL_VAR_H(tessedit_dont_blkrej_good_wds, false,
"Use word segmentation quality metric");
BOOL_VAR_H(tessedit_dont_rowrej_good_wds, false,
"Use word segmentation quality metric");
INT_VAR_H(tessedit_preserve_min_wd_len, 2,
"Only preserve wds longer than this");
BOOL_VAR_H(tessedit_row_rej_good_docs, true,
"Apply row rejection to good docs");
double_VAR_H(tessedit_good_doc_still_rowrej_wd, 1.1,
"rej good doc wd if more than this fraction rejected");
BOOL_VAR_H(tessedit_reject_bad_qual_wds, true,
"Reject all bad quality wds");
BOOL_VAR_H(tessedit_debug_doc_rejection, false, "Page stats");
BOOL_VAR_H(tessedit_debug_quality_metrics, false,
"Output data to debug file");
BOOL_VAR_H(bland_unrej, false, "unrej potential with no chekcs");
double_VAR_H(quality_rowrej_pc, 1.1,
"good_quality_doc gte good char limit");
BOOL_VAR_H(unlv_tilde_crunching, true,
"Mark v.bad words for tilde crunch");
BOOL_VAR_H(hocr_font_info, false,
"Add font info to hocr output");
BOOL_VAR_H(crunch_early_merge_tess_fails, true, "Before word crunch?");
BOOL_VAR_H(crunch_early_convert_bad_unlv_chs, false, "Take out ~^ early?");
double_VAR_H(crunch_terrible_rating, 80.0, "crunch rating lt this");
BOOL_VAR_H(crunch_terrible_garbage, true, "As it says");
double_VAR_H(crunch_poor_garbage_cert, -9.0,
"crunch garbage cert lt this");
double_VAR_H(crunch_poor_garbage_rate, 60, "crunch garbage rating lt this");
double_VAR_H(crunch_pot_poor_rate, 40, "POTENTIAL crunch rating lt this");
double_VAR_H(crunch_pot_poor_cert, -8.0, "POTENTIAL crunch cert lt this");
BOOL_VAR_H(crunch_pot_garbage, true, "POTENTIAL crunch garbage");
double_VAR_H(crunch_del_rating, 60, "POTENTIAL crunch rating lt this");
double_VAR_H(crunch_del_cert, -10.0, "POTENTIAL crunch cert lt this");
double_VAR_H(crunch_del_min_ht, 0.7, "Del if word ht lt xht x this");
double_VAR_H(crunch_del_max_ht, 3.0, "Del if word ht gt xht x this");
double_VAR_H(crunch_del_min_width, 3.0, "Del if word width lt xht x this");
double_VAR_H(crunch_del_high_word, 1.5,
"Del if word gt xht x this above bl");
double_VAR_H(crunch_del_low_word, 0.5, "Del if word gt xht x this below bl");
double_VAR_H(crunch_small_outlines_size, 0.6, "Small if lt xht x this");
INT_VAR_H(crunch_rating_max, 10, "For adj length in rating per ch");
INT_VAR_H(crunch_pot_indicators, 1, "How many potential indicators needed");
BOOL_VAR_H(crunch_leave_ok_strings, true, "Dont touch sensible strings");
BOOL_VAR_H(crunch_accept_ok, true, "Use acceptability in okstring");
BOOL_VAR_H(crunch_leave_accept_strings, false,
"Dont pot crunch sensible strings");
BOOL_VAR_H(crunch_include_numerals, false, "Fiddle alpha figures");
INT_VAR_H(crunch_leave_lc_strings, 4,
"Dont crunch words with long lower case strings");
INT_VAR_H(crunch_leave_uc_strings, 4,
"Dont crunch words with long lower case strings");
INT_VAR_H(crunch_long_repetitions, 3, "Crunch words with long repetitions");
INT_VAR_H(crunch_debug, 0, "As it says");
INT_VAR_H(fixsp_non_noise_limit, 1,
"How many non-noise blbs either side?");
double_VAR_H(fixsp_small_outlines_size, 0.28, "Small if lt xht x this");
BOOL_VAR_H(tessedit_prefer_joined_punct, false, "Reward punctation joins");
INT_VAR_H(fixsp_done_mode, 1, "What constitues done for spacing");
INT_VAR_H(debug_fix_space_level, 0, "Contextual fixspace debug");
STRING_VAR_H(numeric_punctuation, ".,",
"Punct. chs expected WITHIN numbers");
INT_VAR_H(x_ht_acceptance_tolerance, 8,
"Max allowed deviation of blob top outside of font data");
INT_VAR_H(x_ht_min_change, 8, "Min change in xht before actually trying it");
INT_VAR_H(superscript_debug, 0, "Debug level for sub & superscript fixer");
double_VAR_H(superscript_worse_certainty, 2.0, "How many times worse "
"certainty does a superscript position glyph need to be for us "
"to try classifying it as a char with a different baseline?");
double_VAR_H(superscript_bettered_certainty, 0.97, "What reduction in "
"badness do we think sufficient to choose a superscript over "
"what we'd thought. For example, a value of 0.6 means we want "
"to reduce badness of certainty by 40%");
double_VAR_H(superscript_scaledown_ratio, 0.4,
"A superscript scaled down more than this is unbelievably "
"small. For example, 0.3 means we expect the font size to "
"be no smaller than 30% of the text line font size.");
double_VAR_H(subscript_max_y_top, 0.5,
"Maximum top of a character measured as a multiple of x-height "
"above the baseline for us to reconsider whether it's a "
"subscript.");
double_VAR_H(superscript_min_y_bottom, 0.3,
"Minimum bottom of a character measured as a multiple of "
"x-height above the baseline for us to reconsider whether it's "
"a superscript.");
BOOL_VAR_H(tessedit_write_block_separators, false,
"Write block separators in output");
BOOL_VAR_H(tessedit_write_rep_codes, false,
"Write repetition char code");
BOOL_VAR_H(tessedit_write_unlv, false, "Write .unlv output file");
BOOL_VAR_H(tessedit_create_txt, true, "Write .txt output file");
BOOL_VAR_H(tessedit_create_hocr, false, "Write .html hOCR output file");
BOOL_VAR_H(tessedit_create_pdf, false, "Write .pdf output file");
STRING_VAR_H(unrecognised_char, "|",
"Output char for unidentified blobs");
INT_VAR_H(suspect_level, 99, "Suspect marker level");
INT_VAR_H(suspect_space_level, 100,
"Min suspect level for rejecting spaces");
INT_VAR_H(suspect_short_words, 2,
"Dont Suspect dict wds longer than this");
BOOL_VAR_H(suspect_constrain_1Il, false, "UNLV keep 1Il chars rejected");
double_VAR_H(suspect_rating_per_ch, 999.9, "Dont touch bad rating limit");
double_VAR_H(suspect_accept_rating, -999.9, "Accept good rating limit");
BOOL_VAR_H(tessedit_minimal_rejection, false, "Only reject tess failures");
BOOL_VAR_H(tessedit_zero_rejection, false, "Dont reject ANYTHING");
BOOL_VAR_H(tessedit_word_for_word, false,
"Make output have exactly one word per WERD");
BOOL_VAR_H(tessedit_zero_kelvin_rejection, false,
"Dont reject ANYTHING AT ALL");
BOOL_VAR_H(tessedit_consistent_reps, true, "Force all rep chars the same");
INT_VAR_H(tessedit_reject_mode, 0, "Rejection algorithm");
BOOL_VAR_H(tessedit_rejection_debug, false, "Adaption debug");
BOOL_VAR_H(tessedit_flip_0O, true, "Contextual 0O O0 flips");
double_VAR_H(tessedit_lower_flip_hyphen, 1.5,
"Aspect ratio dot/hyphen test");
double_VAR_H(tessedit_upper_flip_hyphen, 1.8,
"Aspect ratio dot/hyphen test");
BOOL_VAR_H(rej_trust_doc_dawg, false, "Use DOC dawg in 11l conf. detector");
BOOL_VAR_H(rej_1Il_use_dict_word, false, "Use dictword test");
BOOL_VAR_H(rej_1Il_trust_permuter_type, true, "Dont double check");
BOOL_VAR_H(rej_use_tess_accepted, true, "Individual rejection control");
BOOL_VAR_H(rej_use_tess_blanks, true, "Individual rejection control");
BOOL_VAR_H(rej_use_good_perm, true, "Individual rejection control");
BOOL_VAR_H(rej_use_sensible_wd, false, "Extend permuter check");
BOOL_VAR_H(rej_alphas_in_number_perm, false, "Extend permuter check");
double_VAR_H(rej_whole_of_mostly_reject_word_fract, 0.85, "if >this fract");
INT_VAR_H(tessedit_image_border, 2, "Rej blbs near image edge limit");
STRING_VAR_H(ok_repeated_ch_non_alphanum_wds, "-?*\075",
"Allow NN to unrej");
STRING_VAR_H(conflict_set_I_l_1, "Il1[]", "Il1 conflict set");
INT_VAR_H(min_sane_x_ht_pixels, 8, "Reject any x-ht lt or eq than this");
BOOL_VAR_H(tessedit_create_boxfile, false, "Output text with boxes");
INT_VAR_H(tessedit_page_number, -1,
"-1 -> All pages, else specifc page to process");
BOOL_VAR_H(tessedit_write_images, false, "Capture the image from the IPE");
BOOL_VAR_H(interactive_display_mode, false, "Run interactively?");
STRING_VAR_H(file_type, ".tif", "Filename extension");
BOOL_VAR_H(tessedit_override_permuter, true, "According to dict_word");
INT_VAR_H(tessdata_manager_debug_level, 0,
"Debug level for TessdataManager functions.");
STRING_VAR_H(tessedit_load_sublangs, "",
"List of languages to load with this one");
BOOL_VAR_H(tessedit_use_primary_params_model, false,
"In multilingual mode use params model of the primary language");
// Min acceptable orientation margin (difference in scores between top and 2nd
// choice in OSResults::orientations) to believe the page orientation.
double_VAR_H(min_orientation_margin, 7.0,
"Min acceptable orientation margin");
BOOL_VAR_H(textord_tabfind_show_vlines, false, "Debug line finding");
BOOL_VAR_H(textord_use_cjk_fp_model, FALSE, "Use CJK fixed pitch model");
BOOL_VAR_H(poly_allow_detailed_fx, false,
"Allow feature extractors to see the original outline");
BOOL_VAR_H(tessedit_init_config_only, false,
"Only initialize with the config file. Useful if the instance is "
"not going to be used for OCR but say only for layout analysis.");
BOOL_VAR_H(textord_equation_detect, false, "Turn on equation detector");
BOOL_VAR_H(textord_tabfind_vertical_text, true, "Enable vertical detection");
BOOL_VAR_H(textord_tabfind_force_vertical_text, false,
"Force using vertical text page mode");
double_VAR_H(textord_tabfind_vertical_text_ratio, 0.5,
"Fraction of textlines deemed vertical to use vertical page "
"mode");
double_VAR_H(textord_tabfind_aligned_gap_fraction, 0.75,
"Fraction of height used as a minimum gap for aligned blobs.");
INT_VAR_H(tessedit_parallelize, 0, "Run in parallel where possible");
BOOL_VAR_H(preserve_interword_spaces, false,
"Preserve multiple interword spaces");
BOOL_VAR_H(include_page_breaks, false,
"Include page separator string in output text after each "
"image/page.");
STRING_VAR_H(page_separator, "\f",
"Page separator (default is form feed control character)");
// The following parameters were deprecated and removed from their original
// locations. The parameters are temporarily kept here to give Tesseract
// users a chance to updated their [lang].traineddata and config files
// without introducing failures during Tesseract initialization.
// TODO(ocr-team): remove these parameters from the code once we are
// reasonably sure that Tesseract users have updated their data files.
//
// BEGIN DEPRECATED PARAMETERS
BOOL_VAR_H(textord_tabfind_vertical_horizontal_mix, true,
"find horizontal lines such as headers in vertical page mode");
INT_VAR_H(tessedit_ok_mode, 5, "Acceptance decision algorithm");
BOOL_VAR_H(load_fixed_length_dawgs, true, "Load fixed length"
" dawgs (e.g. for non-space delimited languages)");
INT_VAR_H(segment_debug, 0, "Debug the whole segmentation process");
BOOL_VAR_H(permute_debug, 0, "char permutation debug");
double_VAR_H(bestrate_pruning_factor, 2.0, "Multiplying factor of"
" current best rate to prune other hypotheses");
BOOL_VAR_H(permute_script_word, 0,
"Turn on word script consistency permuter");
BOOL_VAR_H(segment_segcost_rating, 0,
"incorporate segmentation cost in word rating?");
double_VAR_H(segment_reward_script, 0.95,
"Score multipler for script consistency within a word. "
"Being a 'reward' factor, it should be <= 1. "
"Smaller value implies bigger reward.");
BOOL_VAR_H(permute_fixed_length_dawg, 0,
"Turn on fixed-length phrasebook search permuter");
BOOL_VAR_H(permute_chartype_word, 0,
"Turn on character type (property) consistency permuter");
double_VAR_H(segment_reward_chartype, 0.97,
"Score multipler for char type consistency within a word. ");
double_VAR_H(segment_reward_ngram_best_choice, 0.99,
"Score multipler for ngram permuter's best choice"
" (only used in the Han script path).");
BOOL_VAR_H(ngram_permuter_activated, false,
"Activate character-level n-gram-based permuter");
BOOL_VAR_H(permute_only_top, false, "Run only the top choice permuter");
INT_VAR_H(language_model_fixed_length_choices_depth, 3,
"Depth of blob choice lists to explore"
" when fixed length dawgs are on");
BOOL_VAR_H(use_new_state_cost, FALSE,
"use new state cost heuristics for segmentation state evaluation");
double_VAR_H(heuristic_segcost_rating_base, 1.25,
"base factor for adding segmentation cost into word rating."
"It's a multiplying factor, the larger the value above 1, "
"the bigger the effect of segmentation cost.");
double_VAR_H(heuristic_weight_rating, 1,
"weight associated with char rating in combined cost of state");
double_VAR_H(heuristic_weight_width, 1000.0,
"weight associated with width evidence in combined cost of"
" state");
double_VAR_H(heuristic_weight_seamcut, 0,
"weight associated with seam cut in combined cost of state");
double_VAR_H(heuristic_max_char_wh_ratio, 2.0,
"max char width-to-height ratio allowed in segmentation");
BOOL_VAR_H(enable_new_segsearch, false,
"Enable new segmentation search path.");
double_VAR_H(segsearch_max_fixed_pitch_char_wh_ratio, 2.0,
"Maximum character width-to-height ratio for"
"fixed pitch fonts");
// END DEPRECATED PARAMETERS
//// ambigsrecog.cpp /////////////////////////////////////////////////////////
FILE *init_recog_training(const STRING &fname);
void recog_training_segmented(const STRING &fname,
PAGE_RES *page_res,
volatile ETEXT_DESC *monitor,
FILE *output_file);
void ambigs_classify_and_output(const char *label,
PAGE_RES_IT* pr_it,
FILE *output_file);
#ifndef ANDROID_BUILD
inline CubeRecoContext *GetCubeRecoContext() { return cube_cntxt_; }
#endif
private:
// The filename of a backup config file. If not null, then we currently
// have a temporary debug config file loaded, and backup_config_file_
// will be loaded, and set to null when debug is complete.
const char* backup_config_file_;
// The filename of a config file to read when processing a debug word.
STRING word_config_;
// Image used for input to layout analysis and tesseract recognition.
// May be modified by the ShiroRekhaSplitter to eliminate the top-line.
Pix* pix_binary_;
// Unmodified image used for input to cube. Always valid.
Pix* cube_binary_;
// Grey-level input image if the input was not binary, otherwise NULL.
Pix* pix_grey_;
// Thresholds that were used to generate the thresholded image from grey.
Pix* pix_thresholds_;
// Input image resolution after any scaling. The resolution is not well
// transmitted by operations on Pix, so we keep an independent record here.
int source_resolution_;
// The shiro-rekha splitter object which is used to split top-lines in
// Devanagari words to provide a better word and grapheme segmentation.
ShiroRekhaSplitter splitter_;
// Page segmentation/layout
Textord textord_;
// True if the primary language uses right_to_left reading order.
bool right_to_left_;
Pix* scaled_color_;
int scaled_factor_;
FCOORD deskew_;
FCOORD reskew_;
TesseractStats stats_;
// Sub-languages to be tried in addition to this.
GenericVector<Tesseract*> sub_langs_;
// Most recently used Tesseract out of this and sub_langs_. The default
// language for the next word.
Tesseract* most_recently_used_;
// The size of the font table, ie max possible font id + 1.
int font_table_size_;
#ifndef ANDROID_BUILD
// Cube objects.
CubeRecoContext* cube_cntxt_;
TesseractCubeCombiner *tess_cube_combiner_;
#endif
// Equation detector. Note: this pointer is NOT owned by the class.
EquationDetect* equ_detect_;
};
} // namespace tesseract
#endif // TESSERACT_CCMAIN_TESSERACTCLASS_H__
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