/********************************************************************** * File: wordseg.cpp (Formerly wspace.c) * Description: Code to segment the blobs into words. * Author: Ray Smith * Created: Fri Oct 16 11:32:28 BST 1992 * * (C) Copyright 1992, Hewlett-Packard Ltd. ** 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. * **********************************************************************/ #ifdef __UNIX__ #include #endif #include "stderr.h" #include "blobbox.h" #include "statistc.h" #include "drawtord.h" #include "makerow.h" #include "pitsync1.h" #include "tovars.h" #include "topitch.h" #include "cjkpitch.h" #include "textord.h" #include "fpchop.h" #include "wordseg.h" // Include automatically generated configuration file if running autoconf. #ifdef HAVE_CONFIG_H #include "config_auto.h" #endif #define EXTERN EXTERN BOOL_VAR(textord_fp_chopping, TRUE, "Do fixed pitch chopping"); EXTERN BOOL_VAR(textord_force_make_prop_words, FALSE, "Force proportional word segmentation on all rows"); EXTERN BOOL_VAR(textord_chopper_test, FALSE, "Chopper is being tested."); #define FIXED_WIDTH_MULTIPLE 5 #define BLOCK_STATS_CLUSTERS 10 /** * @name make_single_word * * For each row, arrange the blobs into one word. There is no fixed * pitch detection. */ void make_single_word(bool one_blob, TO_ROW_LIST *rows, ROW_LIST* real_rows) { TO_ROW_IT to_row_it(rows); ROW_IT row_it(real_rows); for (to_row_it.mark_cycle_pt(); !to_row_it.cycled_list(); to_row_it.forward()) { TO_ROW* row = to_row_it.data(); // The blobs have to come out of the BLOBNBOX into the C_BLOB_LIST ready // to create the word. C_BLOB_LIST cblobs; C_BLOB_IT cblob_it(&cblobs); BLOBNBOX_IT box_it(row->blob_list()); for (;!box_it.empty(); box_it.forward()) { BLOBNBOX* bblob= box_it.extract(); if (bblob->joined_to_prev() || (one_blob && !cblob_it.empty())) { if (bblob->cblob() != NULL) { C_OUTLINE_IT cout_it(cblob_it.data()->out_list()); cout_it.move_to_last(); cout_it.add_list_after(bblob->cblob()->out_list()); delete bblob->cblob(); } } else { if (bblob->cblob() != NULL) cblob_it.add_after_then_move(bblob->cblob()); } delete bblob; } // Convert the TO_ROW to a ROW. ROW* real_row = new ROW(row, static_cast(row->kern_size), static_cast(row->space_size)); WERD_IT word_it(real_row->word_list()); WERD* word = new WERD(&cblobs, 0, NULL); word->set_flag(W_BOL, TRUE); word->set_flag(W_EOL, TRUE); word->set_flag(W_DONT_CHOP, one_blob); word_it.add_after_then_move(word); row_it.add_after_then_move(real_row); } } /** * make_words * * Arrange the blobs into words. */ void make_words(tesseract::Textord *textord, ICOORD page_tr, // top right float gradient, // page skew BLOCK_LIST *blocks, // block list TO_BLOCK_LIST *port_blocks) { // output list TO_BLOCK_IT block_it; // iterator TO_BLOCK *block; // current block if (textord->use_cjk_fp_model()) { compute_fixed_pitch_cjk(page_tr, port_blocks); } else { compute_fixed_pitch(page_tr, port_blocks, gradient, FCOORD(0.0f, -1.0f), !(BOOL8) textord_test_landscape); } textord->to_spacing(page_tr, port_blocks); block_it.set_to_list(port_blocks); for (block_it.mark_cycle_pt(); !block_it.cycled_list(); block_it.forward()) { block = block_it.data(); make_real_words(textord, block, FCOORD(1.0f, 0.0f)); } } /** * @name set_row_spaces * * Set the min_space and max_nonspace members of the row so that * the blobs can be arranged into words. */ void set_row_spaces( //find space sizes TO_BLOCK *block, //block to do FCOORD rotation, //for drawing BOOL8 testing_on //correct orientation ) { TO_ROW *row; //current row TO_ROW_IT row_it = block->get_rows (); if (row_it.empty ()) return; //empty block for (row_it.mark_cycle_pt (); !row_it.cycled_list (); row_it.forward ()) { row = row_it.data (); if (row->fixed_pitch == 0) { row->min_space = (inT32) ceil (row->pr_space - (row->pr_space - row->pr_nonsp) * textord_words_definite_spread); row->max_nonspace = (inT32) floor (row->pr_nonsp + (row->pr_space - row->pr_nonsp) * textord_words_definite_spread); if (testing_on && textord_show_initial_words) { tprintf ("Assigning defaults %d non, %d space to row at %g\n", row->max_nonspace, row->min_space, row->intercept ()); } row->space_threshold = (row->max_nonspace + row->min_space) / 2; row->space_size = row->pr_space; row->kern_size = row->pr_nonsp; } #ifndef GRAPHICS_DISABLED if (textord_show_initial_words && testing_on) { plot_word_decisions (to_win, (inT16) row->fixed_pitch, row); } #endif } } /** * @name row_words * * Compute the max nonspace and min space for the row. */ inT32 row_words( //compute space size TO_BLOCK *block, //block it came from TO_ROW *row, //row to operate on inT32 maxwidth, //max expected space size FCOORD rotation, //for drawing BOOL8 testing_on //for debug ) { BOOL8 testing_row; //contains testpt BOOL8 prev_valid; //if decent size BOOL8 this_valid; //current blob big enough inT32 prev_x; //end of prev blob inT32 min_gap; //min interesting gap inT32 cluster_count; //no of clusters inT32 gap_index; //which cluster inT32 smooth_factor; //for smoothing stats BLOBNBOX *blob; //current blob float lower, upper; //clustering parameters float gaps[3]; //gap clusers ICOORD testpt; TBOX blob_box; //bounding box //iterator BLOBNBOX_IT blob_it = row->blob_list (); STATS gap_stats (0, maxwidth); STATS cluster_stats[4]; //clusters testpt = ICOORD (textord_test_x, textord_test_y); smooth_factor = (inT32) (block->xheight * textord_wordstats_smooth_factor + 1.5); // if (testing_on) // tprintf("Row smooth factor=%d\n",smooth_factor); prev_valid = FALSE; prev_x = -MAX_INT32; testing_row = FALSE; for (blob_it.mark_cycle_pt (); !blob_it.cycled_list (); blob_it.forward ()) { blob = blob_it.data (); blob_box = blob->bounding_box (); if (blob_box.contains (testpt)) testing_row = TRUE; gap_stats.add (blob_box.width (), 1); } min_gap = (inT32) floor (gap_stats.ile (textord_words_width_ile)); gap_stats.clear (); for (blob_it.mark_cycle_pt (); !blob_it.cycled_list (); blob_it.forward ()) { blob = blob_it.data (); if (!blob->joined_to_prev ()) { blob_box = blob->bounding_box (); // this_valid=blob_box.width()>=min_gap; this_valid = TRUE; if (this_valid && prev_valid && blob_box.left () - prev_x < maxwidth) { gap_stats.add (blob_box.left () - prev_x, 1); } prev_x = blob_box.right (); prev_valid = this_valid; } } if (gap_stats.get_total () == 0) { row->min_space = 0; //no evidence row->max_nonspace = 0; return 0; } gap_stats.smooth (smooth_factor); lower = row->xheight * textord_words_initial_lower; upper = row->xheight * textord_words_initial_upper; cluster_count = gap_stats.cluster (lower, upper, textord_spacesize_ratioprop, 3, cluster_stats); while (cluster_count < 2 && ceil (lower) < floor (upper)) { //shrink gap upper = (upper * 3 + lower) / 4; lower = (lower * 3 + upper) / 4; cluster_count = gap_stats.cluster (lower, upper, textord_spacesize_ratioprop, 3, cluster_stats); } if (cluster_count < 2) { row->min_space = 0; //no evidence row->max_nonspace = 0; return 0; } for (gap_index = 0; gap_index < cluster_count; gap_index++) gaps[gap_index] = cluster_stats[gap_index + 1].ile (0.5); //get medians if (cluster_count > 2) { if (testing_on && textord_show_initial_words) { tprintf ("Row at %g has 3 sizes of gap:%g,%g,%g\n", row->intercept (), cluster_stats[1].ile (0.5), cluster_stats[2].ile (0.5), cluster_stats[3].ile (0.5)); } lower = gaps[0]; if (gaps[1] > lower) { upper = gaps[1]; //prefer most frequent if (upper < block->xheight * textord_words_min_minspace && gaps[2] > gaps[1]) { upper = gaps[2]; } } else if (gaps[2] > lower && gaps[2] >= block->xheight * textord_words_min_minspace) upper = gaps[2]; else if (lower >= block->xheight * textord_words_min_minspace) { upper = lower; //not nice lower = gaps[1]; if (testing_on && textord_show_initial_words) { tprintf ("Had to switch most common from lower to upper!!\n"); gap_stats.print(); } } else { row->min_space = 0; //no evidence row->max_nonspace = 0; return 0; } } else { if (gaps[1] < gaps[0]) { if (testing_on && textord_show_initial_words) { tprintf ("Had to switch most common from lower to upper!!\n"); gap_stats.print(); } lower = gaps[1]; upper = gaps[0]; } else { upper = gaps[1]; lower = gaps[0]; } } if (upper < block->xheight * textord_words_min_minspace) { row->min_space = 0; //no evidence row->max_nonspace = 0; return 0; } if (upper * 3 < block->min_space * 2 + block->max_nonspace || lower * 3 > block->min_space * 2 + block->max_nonspace) { if (testing_on && textord_show_initial_words) { tprintf ("Disagreement between block and row at %g!!\n", row->intercept ()); tprintf ("Lower=%g, upper=%g, Stats:\n", lower, upper); gap_stats.print(); } } row->min_space = (inT32) ceil (upper - (upper - lower) * textord_words_definite_spread); row->max_nonspace = (inT32) floor (lower + (upper - lower) * textord_words_definite_spread); row->space_threshold = (row->max_nonspace + row->min_space) / 2; row->space_size = upper; row->kern_size = lower; if (testing_on && textord_show_initial_words) { if (testing_row) { tprintf ("GAP STATS\n"); gap_stats.print(); tprintf ("SPACE stats\n"); cluster_stats[2].print_summary(); tprintf ("NONSPACE stats\n"); cluster_stats[1].print_summary(); } tprintf ("Row at %g has minspace=%d(%g), max_non=%d(%g)\n", row->intercept (), row->min_space, upper, row->max_nonspace, lower); } return cluster_stats[2].get_total (); } /** * @name row_words2 * * Compute the max nonspace and min space for the row. */ inT32 row_words2( //compute space size TO_BLOCK *block, //block it came from TO_ROW *row, //row to operate on inT32 maxwidth, //max expected space size FCOORD rotation, //for drawing BOOL8 testing_on //for debug ) { BOOL8 testing_row; //contains testpt BOOL8 prev_valid; //if decent size BOOL8 this_valid; //current blob big enough inT32 prev_x; //end of prev blob inT32 min_width; //min interesting width inT32 valid_count; //good gaps inT32 total_count; //total gaps inT32 cluster_count; //no of clusters inT32 prev_count; //previous cluster_count inT32 gap_index; //which cluster inT32 smooth_factor; //for smoothing stats BLOBNBOX *blob; //current blob float lower, upper; //clustering parameters ICOORD testpt; TBOX blob_box; //bounding box //iterator BLOBNBOX_IT blob_it = row->blob_list (); STATS gap_stats (0, maxwidth); //gap sizes float gaps[BLOCK_STATS_CLUSTERS]; STATS cluster_stats[BLOCK_STATS_CLUSTERS + 1]; //clusters testpt = ICOORD (textord_test_x, textord_test_y); smooth_factor = (inT32) (block->xheight * textord_wordstats_smooth_factor + 1.5); // if (testing_on) // tprintf("Row smooth factor=%d\n",smooth_factor); prev_valid = FALSE; prev_x = -MAX_INT16; testing_row = FALSE; //min blob size min_width = (inT32) block->pr_space; total_count = 0; for (blob_it.mark_cycle_pt (); !blob_it.cycled_list (); blob_it.forward ()) { blob = blob_it.data (); if (!blob->joined_to_prev ()) { blob_box = blob->bounding_box (); this_valid = blob_box.width () >= min_width; this_valid = TRUE; if (this_valid && prev_valid && blob_box.left () - prev_x < maxwidth) { gap_stats.add (blob_box.left () - prev_x, 1); } total_count++; //count possibles prev_x = blob_box.right (); prev_valid = this_valid; } } valid_count = gap_stats.get_total (); if (valid_count < total_count * textord_words_minlarge) { gap_stats.clear (); prev_x = -MAX_INT16; for (blob_it.mark_cycle_pt (); !blob_it.cycled_list (); blob_it.forward ()) { blob = blob_it.data (); if (!blob->joined_to_prev ()) { blob_box = blob->bounding_box (); if (blob_box.left () - prev_x < maxwidth) { gap_stats.add (blob_box.left () - prev_x, 1); } prev_x = blob_box.right (); } } } if (gap_stats.get_total () == 0) { row->min_space = 0; //no evidence row->max_nonspace = 0; return 0; } cluster_count = 0; lower = block->xheight * words_initial_lower; upper = block->xheight * words_initial_upper; gap_stats.smooth (smooth_factor); do { prev_count = cluster_count; cluster_count = gap_stats.cluster (lower, upper, textord_spacesize_ratioprop, BLOCK_STATS_CLUSTERS, cluster_stats); } while (cluster_count > prev_count && cluster_count < BLOCK_STATS_CLUSTERS); if (cluster_count < 1) { row->min_space = 0; row->max_nonspace = 0; return 0; } for (gap_index = 0; gap_index < cluster_count; gap_index++) gaps[gap_index] = cluster_stats[gap_index + 1].ile (0.5); //get medians if (testing_on) { tprintf ("cluster_count=%d:", cluster_count); for (gap_index = 0; gap_index < cluster_count; gap_index++) tprintf (" %g(%d)", gaps[gap_index], cluster_stats[gap_index + 1].get_total ()); tprintf ("\n"); } //Try to find proportional non-space and space for row. for (gap_index = 0; gap_index < cluster_count && gaps[gap_index] > block->max_nonspace; gap_index++); if (gap_index < cluster_count) lower = gaps[gap_index]; //most frequent below else { if (testing_on) tprintf ("No cluster below block threshold!, using default=%g\n", block->pr_nonsp); lower = block->pr_nonsp; } for (gap_index = 0; gap_index < cluster_count && gaps[gap_index] <= block->max_nonspace; gap_index++); if (gap_index < cluster_count) upper = gaps[gap_index]; //most frequent above else { if (testing_on) tprintf ("No cluster above block threshold!, using default=%g\n", block->pr_space); upper = block->pr_space; } row->min_space = (inT32) ceil (upper - (upper - lower) * textord_words_definite_spread); row->max_nonspace = (inT32) floor (lower + (upper - lower) * textord_words_definite_spread); row->space_threshold = (row->max_nonspace + row->min_space) / 2; row->space_size = upper; row->kern_size = lower; if (testing_on) { if (testing_row) { tprintf ("GAP STATS\n"); gap_stats.print(); tprintf ("SPACE stats\n"); cluster_stats[2].print_summary(); tprintf ("NONSPACE stats\n"); cluster_stats[1].print_summary(); } tprintf ("Row at %g has minspace=%d(%g), max_non=%d(%g)\n", row->intercept (), row->min_space, upper, row->max_nonspace, lower); } return 1; } /** * @name make_real_words * * Convert a TO_BLOCK to a BLOCK. */ void make_real_words( tesseract::Textord *textord, TO_BLOCK *block, //block to do FCOORD rotation //for drawing ) { TO_ROW *row; //current row TO_ROW_IT row_it = block->get_rows (); ROW *real_row = NULL; //output row ROW_IT real_row_it = block->block->row_list (); if (row_it.empty ()) return; //empty block for (row_it.mark_cycle_pt (); !row_it.cycled_list (); row_it.forward ()) { row = row_it.data (); if (row->blob_list ()->empty () && !row->rep_words.empty ()) { real_row = make_rep_words (row, block); } else if (!row->blob_list()->empty()) { // In a fixed pitch document, some lines may be detected as fixed pitch // while others don't, and will go through different path. // For non-space delimited language like CJK, fixed pitch chop always // leave the entire line as one word. We can force consistent chopping // with force_make_prop_words flag. POLY_BLOCK* pb = block->block->poly_block(); if (textord_chopper_test) { real_row = textord->make_blob_words (row, rotation); } else if (textord_force_make_prop_words || (pb != NULL && !pb->IsText()) || row->pitch_decision == PITCH_DEF_PROP || row->pitch_decision == PITCH_CORR_PROP) { real_row = textord->make_prop_words (row, rotation); } else if (row->pitch_decision == PITCH_DEF_FIXED || row->pitch_decision == PITCH_CORR_FIXED) { real_row = fixed_pitch_words (row, rotation); } else { ASSERT_HOST(FALSE); } } if (real_row != NULL) { //put row in block real_row_it.add_after_then_move (real_row); } } block->block->set_stats (block->fixed_pitch == 0, (inT16) block->kern_size, (inT16) block->space_size, (inT16) block->fixed_pitch); block->block->check_pitch (); } /** * @name make_rep_words * * Fabricate a real row from only the repeated blob words. * Get the xheight from the block as it may be more meaningful. */ ROW *make_rep_words( //make a row TO_ROW *row, //row to convert TO_BLOCK *block //block it lives in ) { ROW *real_row; //output row TBOX word_box; //bounding box //iterator WERD_IT word_it = &row->rep_words; if (word_it.empty ()) return NULL; word_box = word_it.data ()->bounding_box (); for (word_it.mark_cycle_pt (); !word_it.cycled_list (); word_it.forward ()) word_box += word_it.data ()->bounding_box (); row->xheight = block->xheight; real_row = new ROW(row, (inT16) block->kern_size, (inT16) block->space_size); word_it.set_to_list (real_row->word_list ()); //put words in row word_it.add_list_after (&row->rep_words); real_row->recalc_bounding_box (); return real_row; } /** * @name make_real_word * * Construct a WERD from a given number of adjacent entries in a * list of BLOBNBOXs. */ WERD *make_real_word(BLOBNBOX_IT *box_it, //iterator inT32 blobcount, //no of blobs to use BOOL8 bol, //start of line uinT8 blanks //no of blanks ) { C_OUTLINE_IT cout_it; C_BLOB_LIST cblobs; C_BLOB_IT cblob_it = &cblobs; WERD *word; // new word BLOBNBOX *bblob; // current blob inT32 blobindex; // in row for (blobindex = 0; blobindex < blobcount; blobindex++) { bblob = box_it->extract(); if (bblob->joined_to_prev()) { if (bblob->cblob() != NULL) { cout_it.set_to_list(cblob_it.data()->out_list()); cout_it.move_to_last(); cout_it.add_list_after(bblob->cblob()->out_list()); delete bblob->cblob(); } } else { if (bblob->cblob() != NULL) cblob_it.add_after_then_move(bblob->cblob()); } delete bblob; box_it->forward(); // next one } if (blanks < 1) blanks = 1; word = new WERD(&cblobs, blanks, NULL); if (bol) word->set_flag(W_BOL, TRUE); if (box_it->at_first()) word->set_flag(W_EOL, TRUE); // at end of line return word; }