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Font recognition was poor, due to forcing a 1st and 2nd choice at a character level, when the total score for the correct font is often correct at the word level, so allowed the propagation of a full set of fonts and scores to the word recognizer, which can now decide word level fonts using the scores instead of simple votes. Change precipitated a cleanup of output data structures for classifier results, eliminating ScoredClass and INT_RESULT_STRUCT, with a few extra elements going in UnicharRating, and using that wherever possible. That added the extra complexity of 1-rating due to a flip between 0 is good and 0 is bad for the internal classifier scores before they are converted to rating and certainty.
774 lines
31 KiB
C++
774 lines
31 KiB
C++
/**********************************************************************
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* File: pageres.h (Formerly page_res.h)
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* Description: Results classes used by control.c
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* Author: Phil Cheatle
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* Created: Tue Sep 22 08:42:49 BST 1992
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*
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* (C) Copyright 1992, Hewlett-Packard Ltd.
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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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#ifndef PAGERES_H
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#define PAGERES_H
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#include "blamer.h"
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#include "blobs.h"
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#include "boxword.h"
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#include "elst.h"
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#include "genericvector.h"
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#include "normalis.h"
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#include "ocrblock.h"
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#include "ocrrow.h"
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#include "params_training_featdef.h"
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#include "ratngs.h"
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#include "rejctmap.h"
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#include "seam.h"
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#include "werd.h"
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namespace tesseract {
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struct FontInfo;
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class Tesseract;
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}
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using tesseract::FontInfo;
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/* Forward declarations */
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class BLOCK_RES;
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ELISTIZEH (BLOCK_RES) CLISTIZEH (BLOCK_RES)
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class
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ROW_RES;
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ELISTIZEH (ROW_RES)
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class WERD_RES;
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ELISTIZEH (WERD_RES)
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/*************************************************************************
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* PAGE_RES - Page results
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*************************************************************************/
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class PAGE_RES { // page result
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public:
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inT32 char_count;
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inT32 rej_count;
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BLOCK_RES_LIST block_res_list;
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BOOL8 rejected;
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// Updated every time PAGE_RES_IT iterating on this PAGE_RES moves to
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// the next word. This pointer is not owned by PAGE_RES class.
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WERD_CHOICE **prev_word_best_choice;
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// Sums of blame reasons computed by the blamer.
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GenericVector<int> blame_reasons;
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// Debug information about all the misadaptions on this page.
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// Each BlamerBundle contains an index into this vector, so that words that
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// caused misadaption could be marked. However, since words could be
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// deleted/split/merged, the log is stored on the PAGE_RES level.
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GenericVector<STRING> misadaption_log;
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inline void Init() {
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char_count = 0;
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rej_count = 0;
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rejected = FALSE;
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prev_word_best_choice = NULL;
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blame_reasons.init_to_size(IRR_NUM_REASONS, 0);
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}
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PAGE_RES() { Init(); } // empty constructor
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PAGE_RES(bool merge_similar_words,
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BLOCK_LIST *block_list, // real blocks
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WERD_CHOICE **prev_word_best_choice_ptr);
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~PAGE_RES () { // destructor
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}
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};
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/*************************************************************************
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* BLOCK_RES - Block results
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*************************************************************************/
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class BLOCK_RES:public ELIST_LINK {
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public:
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BLOCK * block; // real block
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inT32 char_count; // chars in block
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inT32 rej_count; // rejected chars
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inT16 font_class; //
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inT16 row_count;
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float x_height;
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BOOL8 font_assigned; // block already
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// processed
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BOOL8 bold; // all bold
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BOOL8 italic; // all italic
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ROW_RES_LIST row_res_list;
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BLOCK_RES() {
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} // empty constructor
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BLOCK_RES(bool merge_similar_words, BLOCK *the_block); // real block
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~BLOCK_RES () { // destructor
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}
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};
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/*************************************************************************
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* ROW_RES - Row results
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*************************************************************************/
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class ROW_RES:public ELIST_LINK {
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public:
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ROW * row; // real row
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inT32 char_count; // chars in block
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inT32 rej_count; // rejected chars
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inT32 whole_word_rej_count; // rejs in total rej wds
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WERD_RES_LIST word_res_list;
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ROW_RES() {
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} // empty constructor
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ROW_RES(bool merge_similar_words, ROW *the_row); // real row
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~ROW_RES() { // destructor
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}
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};
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/*************************************************************************
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* WERD_RES - Word results
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*************************************************************************/
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enum CRUNCH_MODE
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{
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CR_NONE,
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CR_KEEP_SPACE,
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CR_LOOSE_SPACE,
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CR_DELETE
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};
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// WERD_RES is a collection of publicly accessible members that gathers
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// information about a word result.
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class WERD_RES : public ELIST_LINK {
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public:
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// Which word is which?
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// There are 3 coordinate spaces in use here: a possibly rotated pixel space,
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// the original image coordinate space, and the BLN space in which the
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// baseline of a word is at kBlnBaselineOffset, the xheight is kBlnXHeight,
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// and the x-middle of the word is at 0.
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// In the rotated pixel space, coordinates correspond to the input image,
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// but may be rotated about the origin by a multiple of 90 degrees,
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// and may therefore be negative.
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// In any case a rotation by denorm.block()->re_rotation() will take them
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// back to the original image.
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// The other differences between words all represent different stages of
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// processing during recognition.
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// ---------------------------INPUT-------------------------------------
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// The word is the input C_BLOBs in the rotated pixel space.
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// word is NOT owned by the WERD_RES unless combination is true.
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// All the other word pointers ARE owned by the WERD_RES.
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WERD* word; // Input C_BLOB word.
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// -------------SETUP BY SetupFor*Recognition---READONLY-INPUT------------
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// The bln_boxes contains the bounding boxes (only) of the input word, in the
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// BLN space. The lengths of word and bln_boxes
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// match as they are both before any chopping.
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// TODO(rays) determine if docqual does anything useful and delete bln_boxes
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// if it doesn't.
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tesseract::BoxWord* bln_boxes; // BLN input bounding boxes.
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// The ROW that this word sits in. NOT owned by the WERD_RES.
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ROW* blob_row;
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// The denorm provides the transformation to get back to the rotated image
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// coords from the chopped_word/rebuild_word BLN coords, but each blob also
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// has its own denorm.
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DENORM denorm; // For use on chopped_word.
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// Unicharset used by the classifier output in best_choice and raw_choice.
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const UNICHARSET* uch_set; // For converting back to utf8.
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// ----Initialized by SetupFor*Recognition---BUT OUTPUT FROM RECOGNITION----
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// ----Setup to a (different!) state expected by the various classifiers----
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// TODO(rays) Tidy and make more consistent.
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// The chopped_word is also in BLN space, and represents the fully chopped
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// character fragments that make up the word.
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// The length of chopped_word matches length of seam_array + 1 (if set).
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TWERD* chopped_word; // BLN chopped fragments output.
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// Vector of SEAM* holding chopping points matching chopped_word.
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GenericVector<SEAM*> seam_array;
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// Widths of blobs in chopped_word.
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GenericVector<int> blob_widths;
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// Gaps between blobs in chopped_word. blob_gaps[i] is the gap between
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// blob i and blob i+1.
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GenericVector<int> blob_gaps;
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// Ratings matrix contains classifier choices for each classified combination
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// of blobs. The dimension is the same as the number of blobs in chopped_word
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// and the leading diagonal corresponds to classifier results of the blobs
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// in chopped_word. The state_ members of best_choice, raw_choice and
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// best_choices all correspond to this ratings matrix and allow extraction
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// of the blob choices for any given WERD_CHOICE.
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MATRIX* ratings; // Owned pointer.
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// Pointer to the first WERD_CHOICE in best_choices. This is the result that
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// will be output from Tesseract. Note that this is now a borrowed pointer
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// and should NOT be deleted.
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WERD_CHOICE* best_choice; // Borrowed pointer.
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// The best raw_choice found during segmentation search. Differs from the
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// best_choice by being the best result according to just the character
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// classifier, not taking any language model information into account.
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// Unlike best_choice, the pointer IS owned by this WERD_RES.
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WERD_CHOICE* raw_choice; // Owned pointer.
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// Alternative results found during chopping/segmentation search stages.
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// Note that being an ELIST, best_choices owns the WERD_CHOICEs.
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WERD_CHOICE_LIST best_choices;
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// Truth bounding boxes, text and incorrect choice reason.
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BlamerBundle *blamer_bundle;
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// --------------OUTPUT FROM RECOGNITION-------------------------------
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// --------------Not all fields are necessarily set.-------------------
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// ---best_choice, raw_choice *must* end up set, with a box_word-------
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// ---In complete output, the number of blobs in rebuild_word matches---
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// ---the number of boxes in box_word, the number of unichar_ids in---
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// ---best_choice, the number of ints in best_state, and the number---
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// ---of strings in correct_text--------------------------------------
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// ---SetupFake Sets everything to appropriate values if the word is---
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// ---known to be bad before recognition.------------------------------
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// The rebuild_word is also in BLN space, but represents the final best
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// segmentation of the word. Its length is therefore the same as box_word.
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TWERD* rebuild_word; // BLN best segmented word.
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// The box_word is in the original image coordinate space. It is the
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// bounding boxes of the rebuild_word, after denormalization.
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// The length of box_word matches rebuild_word, best_state (if set) and
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// correct_text (if set), as well as best_choice and represents the
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// number of classified units in the output.
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tesseract::BoxWord* box_word; // Denormalized output boxes.
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// The best_state stores the relationship between chopped_word and
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// rebuild_word. Each blob[i] in rebuild_word is composed of best_state[i]
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// adjacent blobs in chopped_word. The seams in seam_array are hidden
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// within a rebuild_word blob and revealed between them.
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GenericVector<int> best_state; // Number of blobs in each best blob.
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// The correct_text is used during training and adaption to carry the
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// text to the training system without the need for a unicharset. There
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// is one entry in the vector for each blob in rebuild_word and box_word.
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GenericVector<STRING> correct_text;
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// The Tesseract that was used to recognize this word. Just a borrowed
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// pointer. Note: Tesseract's class definition is in a higher-level library.
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// We avoid introducing a cyclic dependency by not using the Tesseract
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// within WERD_RES. We are just storing it to provide access to it
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// for the top-level multi-language controller, and maybe for output of
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// the recognized language.
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tesseract::Tesseract* tesseract;
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// Less-well documented members.
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// TODO(rays) Add more documentation here.
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WERD_CHOICE *ep_choice; // ep text TODO(rays) delete this.
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REJMAP reject_map; // best_choice rejects
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BOOL8 tess_failed;
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/*
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If tess_failed is TRUE, one of the following tests failed when Tess
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returned:
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- The outword blob list was not the same length as the best_choice string;
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- The best_choice string contained ALL blanks;
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- The best_choice string was zero length
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*/
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BOOL8 tess_accepted; // Tess thinks its ok?
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BOOL8 tess_would_adapt; // Tess would adapt?
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BOOL8 done; // ready for output?
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bool small_caps; // word appears to be small caps
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bool odd_size; // word is bigger than line or leader dots.
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inT8 italic;
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inT8 bold;
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// The fontinfos are pointers to data owned by the classifier.
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const FontInfo* fontinfo;
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const FontInfo* fontinfo2;
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inT8 fontinfo_id_count; // number of votes
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inT8 fontinfo_id2_count; // number of votes
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BOOL8 guessed_x_ht;
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BOOL8 guessed_caps_ht;
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CRUNCH_MODE unlv_crunch_mode;
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float x_height; // post match estimate
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float caps_height; // post match estimate
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float baseline_shift; // post match estimate.
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/*
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To deal with fuzzy spaces we need to be able to combine "words" to form
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combinations when we suspect that the gap is a non-space. The (new) text
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ord code generates separate words for EVERY fuzzy gap - flags in the word
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indicate whether the gap is below the threshold (fuzzy kern) and is thus
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NOT a real word break by default, or above the threshold (fuzzy space) and
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this is a real word break by default.
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The WERD_RES list contains all these words PLUS "combination" words built
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out of (copies of) the words split by fuzzy kerns. The separate parts have
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their "part_of_combo" flag set true and should be IGNORED on a default
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reading of the list.
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Combination words are FOLLOWED by the sequence of part_of_combo words
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which they combine.
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*/
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BOOL8 combination; //of two fuzzy gap wds
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BOOL8 part_of_combo; //part of a combo
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BOOL8 reject_spaces; //Reject spacing?
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WERD_RES() {
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InitNonPointers();
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InitPointers();
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}
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WERD_RES(WERD *the_word) {
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InitNonPointers();
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InitPointers();
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word = the_word;
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}
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// Deep copies everything except the ratings MATRIX.
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// To get that use deep_copy below.
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WERD_RES(const WERD_RES &source) {
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InitPointers();
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*this = source; // see operator=
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}
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~WERD_RES();
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// Returns the UTF-8 string for the given blob index in the best_choice word,
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// given that we know whether we are in a right-to-left reading context.
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// This matters for mirrorable characters such as parentheses. We recognize
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// characters purely based on their shape on the page, and by default produce
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// the corresponding unicode for a left-to-right context.
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const char* const BestUTF8(int blob_index, bool in_rtl_context) const {
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if (blob_index < 0 || best_choice == NULL ||
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blob_index >= best_choice->length())
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return NULL;
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UNICHAR_ID id = best_choice->unichar_id(blob_index);
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if (id < 0 || id >= uch_set->size() || id == INVALID_UNICHAR_ID)
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return NULL;
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UNICHAR_ID mirrored = uch_set->get_mirror(id);
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if (in_rtl_context && mirrored > 0 && mirrored != INVALID_UNICHAR_ID)
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id = mirrored;
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return uch_set->id_to_unichar_ext(id);
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}
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// Returns the UTF-8 string for the given blob index in the raw_choice word.
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const char* const RawUTF8(int blob_index) const {
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if (blob_index < 0 || blob_index >= raw_choice->length())
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return NULL;
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UNICHAR_ID id = raw_choice->unichar_id(blob_index);
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if (id < 0 || id >= uch_set->size() || id == INVALID_UNICHAR_ID)
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return NULL;
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return uch_set->id_to_unichar(id);
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}
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UNICHARSET::Direction SymbolDirection(int blob_index) const {
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if (best_choice == NULL ||
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blob_index >= best_choice->length() ||
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blob_index < 0)
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return UNICHARSET::U_OTHER_NEUTRAL;
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return uch_set->get_direction(best_choice->unichar_id(blob_index));
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}
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bool AnyRtlCharsInWord() const {
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if (uch_set == NULL || best_choice == NULL || best_choice->length() < 1)
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return false;
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for (int id = 0; id < best_choice->length(); id++) {
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int unichar_id = best_choice->unichar_id(id);
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if (unichar_id < 0 || unichar_id >= uch_set->size())
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continue; // Ignore illegal chars.
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UNICHARSET::Direction dir =
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uch_set->get_direction(unichar_id);
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if (dir == UNICHARSET::U_RIGHT_TO_LEFT ||
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dir == UNICHARSET::U_RIGHT_TO_LEFT_ARABIC ||
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dir == UNICHARSET::U_ARABIC_NUMBER)
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return true;
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}
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return false;
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}
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bool AnyLtrCharsInWord() const {
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if (uch_set == NULL || best_choice == NULL || best_choice->length() < 1)
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return false;
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for (int id = 0; id < best_choice->length(); id++) {
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int unichar_id = best_choice->unichar_id(id);
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if (unichar_id < 0 || unichar_id >= uch_set->size())
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continue; // Ignore illegal chars.
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UNICHARSET::Direction dir = uch_set->get_direction(unichar_id);
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if (dir == UNICHARSET::U_LEFT_TO_RIGHT)
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return true;
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}
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return false;
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}
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// Return whether the blobs in this WERD_RES 0, 1,... come from an engine
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// that gave us the unichars in reading order (as opposed to strict left
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// to right).
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bool UnicharsInReadingOrder() const {
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return best_choice->unichars_in_script_order();
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}
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void InitNonPointers();
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void InitPointers();
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void Clear();
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void ClearResults();
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void ClearWordChoices();
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void ClearRatings();
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// Deep copies everything except the ratings MATRIX.
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// To get that use deep_copy below.
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WERD_RES& operator=(const WERD_RES& source); //from this
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void CopySimpleFields(const WERD_RES& source);
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// Initializes a blank (default constructed) WERD_RES from one that has
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// already been recognized.
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// Use SetupFor*Recognition afterwards to complete the setup and make
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// it ready for a retry recognition.
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void InitForRetryRecognition(const WERD_RES& source);
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// Sets up the members used in recognition: bln_boxes, chopped_word,
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// seam_array, denorm. Returns false if
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// the word is empty and sets up fake results. If use_body_size is
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// true and row->body_size is set, then body_size will be used for
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// blob normalization instead of xheight + ascrise. This flag is for
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// those languages that are using CJK pitch model and thus it has to
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// be true if and only if tesseract->textord_use_cjk_fp_model is
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// true.
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// If allow_detailed_fx is true, the feature extractor will receive fine
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// precision outline information, allowing smoother features and better
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// features on low resolution images.
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// The norm_mode sets the default mode for normalization in absence
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// of any of the above flags. It should really be a tesseract::OcrEngineMode
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// but is declared as int for ease of use with tessedit_ocr_engine_mode.
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// Returns false if the word is empty and sets up fake results.
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bool SetupForRecognition(const UNICHARSET& unicharset_in,
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tesseract::Tesseract* tesseract, Pix* pix,
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int norm_mode,
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const TBOX* norm_box, bool numeric_mode,
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bool use_body_size, bool allow_detailed_fx,
|
|
ROW *row, const BLOCK* block);
|
|
|
|
// Set up the seam array, bln_boxes, best_choice, and raw_choice to empty
|
|
// accumulators from a made chopped word. We presume the fields are already
|
|
// empty.
|
|
void SetupBasicsFromChoppedWord(const UNICHARSET &unicharset_in);
|
|
|
|
// Sets up the members used in recognition for an empty recognition result:
|
|
// bln_boxes, chopped_word, seam_array, denorm, best_choice, raw_choice.
|
|
void SetupFake(const UNICHARSET& uch);
|
|
|
|
// Set the word as having the script of the input unicharset.
|
|
void SetupWordScript(const UNICHARSET& unicharset_in);
|
|
|
|
// Sets up the blamer_bundle if it is not null, using the initialized denorm.
|
|
void SetupBlamerBundle();
|
|
|
|
// Computes the blob_widths and blob_gaps from the chopped_word.
|
|
void SetupBlobWidthsAndGaps();
|
|
|
|
// Updates internal data to account for a new SEAM (chop) at the given
|
|
// blob_number. Fixes the ratings matrix and states in the choices, as well
|
|
// as the blob widths and gaps.
|
|
void InsertSeam(int blob_number, SEAM* seam);
|
|
|
|
// Returns true if all the word choices except the first have adjust_factors
|
|
// worse than the given threshold.
|
|
bool AlternativeChoiceAdjustmentsWorseThan(float threshold) const;
|
|
|
|
// Returns true if the current word is ambiguous (by number of answers or
|
|
// by dangerous ambigs.)
|
|
bool IsAmbiguous();
|
|
|
|
// Returns true if the ratings matrix size matches the sum of each of the
|
|
// segmentation states.
|
|
bool StatesAllValid();
|
|
|
|
// Prints a list of words found if debug is true or the word result matches
|
|
// the word_to_debug.
|
|
void DebugWordChoices(bool debug, const char* word_to_debug);
|
|
|
|
// Prints the top choice along with the accepted/done flags.
|
|
void DebugTopChoice(const char* msg) const;
|
|
|
|
// Removes from best_choices all choices which are not within a reasonable
|
|
// range of the best choice.
|
|
void FilterWordChoices(int debug_level);
|
|
|
|
// Computes a set of distance thresholds used to control adaption.
|
|
// Compares the best choice for the current word to the best raw choice
|
|
// to determine which characters were classified incorrectly by the
|
|
// classifier. Then places a separate threshold into thresholds for each
|
|
// character in the word. If the classifier was correct, max_rating is placed
|
|
// into thresholds. If the classifier was incorrect, the mean match rating
|
|
// (error percentage) of the classifier's incorrect choice minus some margin
|
|
// is placed into thresholds. This can then be used by the caller to try to
|
|
// create a new template for the desired class that will classify the
|
|
// character with a rating better than the threshold value. The match rating
|
|
// placed into thresholds is never allowed to be below min_rating in order to
|
|
// prevent trying to make overly tight templates.
|
|
// min_rating limits how tight to make a template.
|
|
// max_rating limits how loose to make a template.
|
|
// rating_margin denotes the amount of margin to put in template.
|
|
void ComputeAdaptionThresholds(float certainty_scale,
|
|
float min_rating,
|
|
float max_rating,
|
|
float rating_margin,
|
|
float* thresholds);
|
|
|
|
// Saves a copy of the word_choice if it has the best unadjusted rating.
|
|
// Returns true if the word_choice was the new best.
|
|
bool LogNewRawChoice(WERD_CHOICE* word_choice);
|
|
// Consumes word_choice by adding it to best_choices, (taking ownership) if
|
|
// the certainty for word_choice is some distance of the best choice in
|
|
// best_choices, or by deleting the word_choice and returning false.
|
|
// The best_choices list is kept in sorted order by rating. Duplicates are
|
|
// removed, and the list is kept no longer than max_num_choices in length.
|
|
// Returns true if the word_choice is still a valid pointer.
|
|
bool LogNewCookedChoice(int max_num_choices, bool debug,
|
|
WERD_CHOICE* word_choice);
|
|
|
|
// Prints a brief list of all the best choices.
|
|
void PrintBestChoices() const;
|
|
|
|
// Returns the sum of the widths of the blob between start_blob and last_blob
|
|
// inclusive.
|
|
int GetBlobsWidth(int start_blob, int last_blob);
|
|
// Returns the width of a gap between the specified blob and the next one.
|
|
int GetBlobsGap(int blob_index);
|
|
|
|
// Returns the BLOB_CHOICE corresponding to the given index in the
|
|
// best choice word taken from the appropriate cell in the ratings MATRIX.
|
|
// Borrowed pointer, so do not delete. May return NULL if there is no
|
|
// BLOB_CHOICE matching the unichar_id at the given index.
|
|
BLOB_CHOICE* GetBlobChoice(int index) const;
|
|
|
|
// Returns the BLOB_CHOICE_LIST corresponding to the given index in the
|
|
// best choice word taken from the appropriate cell in the ratings MATRIX.
|
|
// Borrowed pointer, so do not delete.
|
|
BLOB_CHOICE_LIST* GetBlobChoices(int index) const;
|
|
|
|
// Moves the results fields from word to this. This takes ownership of all
|
|
// the data, so src can be destructed.
|
|
// word1.ConsumeWordResult(word);
|
|
// delete word;
|
|
// is simpler and faster than:
|
|
// word1 = *word;
|
|
// delete word;
|
|
// as it doesn't need to copy and reallocate anything.
|
|
void ConsumeWordResults(WERD_RES* word);
|
|
|
|
// Replace the best choice and rebuild box word.
|
|
// choice must be from the current best_choices list.
|
|
void ReplaceBestChoice(WERD_CHOICE* choice);
|
|
|
|
// Builds the rebuild_word and sets the best_state from the chopped_word and
|
|
// the best_choice->state.
|
|
void RebuildBestState();
|
|
|
|
// Copies the chopped_word to the rebuild_word, faking a best_state as well.
|
|
// Also sets up the output box_word.
|
|
void CloneChoppedToRebuild();
|
|
|
|
// Sets/replaces the box_word with one made from the rebuild_word.
|
|
void SetupBoxWord();
|
|
|
|
// Sets up the script positions in the best_choice using the best_choice
|
|
// to get the unichars, and the unicharset to get the target positions.
|
|
void SetScriptPositions();
|
|
// Sets all the blobs in all the words (best choice and alternates) to be
|
|
// the given position. (When a sub/superscript is recognized as a separate
|
|
// word, it falls victim to the rule that a whole word cannot be sub or
|
|
// superscript, so this function overrides that problem.)
|
|
void SetAllScriptPositions(tesseract::ScriptPos position);
|
|
|
|
// Classifies the word with some already-calculated BLOB_CHOICEs.
|
|
// The choices are an array of blob_count pointers to BLOB_CHOICE,
|
|
// providing a single classifier result for each blob.
|
|
// The BLOB_CHOICEs are consumed and the word takes ownership.
|
|
// The number of blobs in the box_word must match blob_count.
|
|
void FakeClassifyWord(int blob_count, BLOB_CHOICE** choices);
|
|
|
|
// Creates a WERD_CHOICE for the word using the top choices from the leading
|
|
// diagonal of the ratings matrix.
|
|
void FakeWordFromRatings();
|
|
|
|
// Copies the best_choice strings to the correct_text for adaption/training.
|
|
void BestChoiceToCorrectText();
|
|
|
|
// Merges 2 adjacent blobs in the result if the permanent callback
|
|
// class_cb returns other than INVALID_UNICHAR_ID, AND the permanent
|
|
// callback box_cb is NULL or returns true, setting the merged blob
|
|
// result to the class returned from class_cb.
|
|
// Returns true if anything was merged.
|
|
bool ConditionalBlobMerge(
|
|
TessResultCallback2<UNICHAR_ID, UNICHAR_ID, UNICHAR_ID>* class_cb,
|
|
TessResultCallback2<bool, const TBOX&, const TBOX&>* box_cb);
|
|
|
|
// Merges 2 adjacent blobs in the result (index and index+1) and corrects
|
|
// all the data to account for the change.
|
|
void MergeAdjacentBlobs(int index);
|
|
|
|
// Callback helper for fix_quotes returns a double quote if both
|
|
// arguments are quote, otherwise INVALID_UNICHAR_ID.
|
|
UNICHAR_ID BothQuotes(UNICHAR_ID id1, UNICHAR_ID id2);
|
|
void fix_quotes();
|
|
|
|
// Callback helper for fix_hyphens returns UNICHAR_ID of - if both
|
|
// arguments are hyphen, otherwise INVALID_UNICHAR_ID.
|
|
UNICHAR_ID BothHyphens(UNICHAR_ID id1, UNICHAR_ID id2);
|
|
// Callback helper for fix_hyphens returns true if box1 and box2 overlap
|
|
// (assuming both on the same textline, are in order and a chopped em dash.)
|
|
bool HyphenBoxesOverlap(const TBOX& box1, const TBOX& box2);
|
|
void fix_hyphens();
|
|
|
|
// Callback helper for merge_tess_fails returns a space if both
|
|
// arguments are space, otherwise INVALID_UNICHAR_ID.
|
|
UNICHAR_ID BothSpaces(UNICHAR_ID id1, UNICHAR_ID id2);
|
|
void merge_tess_fails();
|
|
|
|
// Returns a really deep copy of *src, including the ratings MATRIX.
|
|
static WERD_RES* deep_copy(const WERD_RES* src) {
|
|
WERD_RES* result = new WERD_RES(*src);
|
|
// That didn't copy the ratings, but we want a copy if there is one to
|
|
// begin width.
|
|
if (src->ratings != NULL)
|
|
result->ratings = src->ratings->DeepCopy();
|
|
return result;
|
|
}
|
|
|
|
// Copy blobs from word_res onto this word (eliminating spaces between).
|
|
// Since this may be called bidirectionally OR both the BOL and EOL flags.
|
|
void copy_on(WERD_RES *word_res) { //from this word
|
|
word->set_flag(W_BOL, word->flag(W_BOL) || word_res->word->flag(W_BOL));
|
|
word->set_flag(W_EOL, word->flag(W_EOL) || word_res->word->flag(W_EOL));
|
|
word->copy_on(word_res->word);
|
|
}
|
|
|
|
// Returns true if the collection of count pieces, starting at start, are all
|
|
// natural connected components, ie there are no real chops involved.
|
|
bool PiecesAllNatural(int start, int count) const;
|
|
};
|
|
|
|
/*************************************************************************
|
|
* PAGE_RES_IT - Page results iterator
|
|
*************************************************************************/
|
|
|
|
class PAGE_RES_IT {
|
|
public:
|
|
PAGE_RES * page_res; // page being iterated
|
|
|
|
PAGE_RES_IT() {
|
|
} // empty contructor
|
|
|
|
PAGE_RES_IT(PAGE_RES *the_page_res) { // page result
|
|
page_res = the_page_res;
|
|
restart_page(); // ready to scan
|
|
}
|
|
|
|
// Do two PAGE_RES_ITs point at the same word?
|
|
// This is much cheaper than cmp().
|
|
bool operator ==(const PAGE_RES_IT &other) const;
|
|
|
|
bool operator !=(const PAGE_RES_IT &other) const {return !(*this == other); }
|
|
|
|
// Given another PAGE_RES_IT to the same page,
|
|
// this before other: -1
|
|
// this equal to other: 0
|
|
// this later than other: 1
|
|
int cmp(const PAGE_RES_IT &other) const;
|
|
|
|
WERD_RES *restart_page() {
|
|
return start_page(false); // Skip empty blocks.
|
|
}
|
|
WERD_RES *restart_page_with_empties() {
|
|
return start_page(true); // Allow empty blocks.
|
|
}
|
|
WERD_RES *start_page(bool empty_ok);
|
|
|
|
WERD_RES *restart_row();
|
|
|
|
// ============ Methods that mutate the underling structures ===========
|
|
// Note that these methods will potentially invalidate other PAGE_RES_ITs
|
|
// and are intended to be used only while a single PAGE_RES_IT is active.
|
|
// This problem needs to be taken into account if these mutation operators
|
|
// are ever provided to PageIterator or its subclasses.
|
|
|
|
// Inserts the new_word and a corresponding WERD_RES before the current
|
|
// position. The simple fields of the WERD_RES are copied from clone_res and
|
|
// the resulting WERD_RES is returned for further setup with best_choice etc.
|
|
WERD_RES* InsertSimpleCloneWord(const WERD_RES& clone_res, WERD* new_word);
|
|
|
|
// Replaces the current WERD/WERD_RES with the given words. The given words
|
|
// contain fake blobs that indicate the position of the characters. These are
|
|
// replaced with real blobs from the current word as much as possible.
|
|
void ReplaceCurrentWord(tesseract::PointerVector<WERD_RES>* words);
|
|
|
|
// Deletes the current WERD_RES and its underlying WERD.
|
|
void DeleteCurrentWord();
|
|
|
|
// Makes the current word a fuzzy space if not already fuzzy. Updates
|
|
// corresponding part of combo if required.
|
|
void MakeCurrentWordFuzzy();
|
|
|
|
WERD_RES *forward() { // Get next word.
|
|
return internal_forward(false, false);
|
|
}
|
|
// Move forward, but allow empty blocks to show as single NULL words.
|
|
WERD_RES *forward_with_empties() {
|
|
return internal_forward(false, true);
|
|
}
|
|
|
|
WERD_RES *forward_paragraph(); // get first word in next non-empty paragraph
|
|
WERD_RES *forward_block(); // get first word in next non-empty block
|
|
|
|
WERD_RES *prev_word() const { // previous word
|
|
return prev_word_res;
|
|
}
|
|
ROW_RES *prev_row() const { // row of prev word
|
|
return prev_row_res;
|
|
}
|
|
BLOCK_RES *prev_block() const { // block of prev word
|
|
return prev_block_res;
|
|
}
|
|
WERD_RES *word() const { // current word
|
|
return word_res;
|
|
}
|
|
ROW_RES *row() const { // row of current word
|
|
return row_res;
|
|
}
|
|
BLOCK_RES *block() const { // block of cur. word
|
|
return block_res;
|
|
}
|
|
WERD_RES *next_word() const { // next word
|
|
return next_word_res;
|
|
}
|
|
ROW_RES *next_row() const { // row of next word
|
|
return next_row_res;
|
|
}
|
|
BLOCK_RES *next_block() const { // block of next word
|
|
return next_block_res;
|
|
}
|
|
void rej_stat_word(); // for page/block/row
|
|
void ResetWordIterator();
|
|
|
|
private:
|
|
WERD_RES *internal_forward(bool new_block, bool empty_ok);
|
|
|
|
WERD_RES * prev_word_res; // previous word
|
|
ROW_RES *prev_row_res; // row of prev word
|
|
BLOCK_RES *prev_block_res; // block of prev word
|
|
|
|
WERD_RES *word_res; // current word
|
|
ROW_RES *row_res; // row of current word
|
|
BLOCK_RES *block_res; // block of cur. word
|
|
|
|
WERD_RES *next_word_res; // next word
|
|
ROW_RES *next_row_res; // row of next word
|
|
BLOCK_RES *next_block_res; // block of next word
|
|
|
|
BLOCK_RES_IT block_res_it; // iterators
|
|
ROW_RES_IT row_res_it;
|
|
WERD_RES_IT word_res_it;
|
|
};
|
|
#endif
|