/******************************************************************
 * File:        docqual.cpp  (Formerly docqual.c)
 * Description: Document Quality Metrics
 * Author:      Phil Cheatle
 *
 * (C) Copyright 1994, 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.
 *
 **********************************************************************/

#include "docqual.h"
#include <cctype>
#include "reject.h"
#include "tesseractclass.h"
#include "tessvars.h"

namespace tesseract {

static void countMatchingBlobs(int16_t &match_count, int /*index*/) {
  ++match_count;
}

static void countAcceptedBlobs(WERD_RES *word, int16_t &match_count, int16_t &accepted_match_count,
                               int index) {
  if (word->reject_map[index].accepted()) {
    ++accepted_match_count;
  }
  ++match_count;
}

static void acceptIfGoodQuality(WERD_RES *word, int index) {
  if (word->reject_map[index].accept_if_good_quality()) {
    word->reject_map[index].setrej_quality_accept();
  }
}

/*************************************************************************
 * word_blob_quality()
 * How many blobs in the box_word are identical to those of the inword?
 * ASSUME blobs in both initial word and box_word are in ascending order of
 * left hand blob edge.
 *************************************************************************/
int16_t Tesseract::word_blob_quality(WERD_RES *word) {
  int16_t match_count = 0;
  if (word->bln_boxes != nullptr && word->rebuild_word != nullptr &&
      !word->rebuild_word->blobs.empty()) {
    using namespace std::placeholders; // for _1
    word->bln_boxes->ProcessMatchedBlobs(*word->rebuild_word,
                                         std::bind(countMatchingBlobs, match_count, _1));
  }
  return match_count;
}

int16_t Tesseract::word_outline_errs(WERD_RES *word) {
  int16_t i = 0;
  int16_t err_count = 0;

  if (word->rebuild_word != nullptr) {
    for (int b = 0; b < word->rebuild_word->NumBlobs(); ++b) {
      TBLOB *blob = word->rebuild_word->blobs[b];
      err_count += count_outline_errs(word->best_choice->unichar_string()[i], blob->NumOutlines());
      i++;
    }
  }
  return err_count;
}

/*************************************************************************
 * word_char_quality()
 * Combination of blob quality and outline quality - how many good chars are
 * there? - I.e chars which pass the blob AND outline tests.
 *************************************************************************/
void Tesseract::word_char_quality(WERD_RES *word, int16_t *match_count,
                                  int16_t *accepted_match_count) {
  *match_count = 0;
  *accepted_match_count = 0;
  if (word->bln_boxes != nullptr && word->rebuild_word != nullptr &&
      !word->rebuild_word->blobs.empty()) {
    using namespace std::placeholders; // for _1
    word->bln_boxes->ProcessMatchedBlobs(
        *word->rebuild_word,
        std::bind(countAcceptedBlobs, word, *match_count, *accepted_match_count, _1));
  }
}

/*************************************************************************
 * unrej_good_chs()
 * Unreject POTENTIAL rejects if the blob passes the blob and outline checks
 *************************************************************************/
void Tesseract::unrej_good_chs(WERD_RES *word) {
  if (word->bln_boxes != nullptr && word->rebuild_word != nullptr &&
      word->rebuild_word->blobs.empty()) {
    using namespace std::placeholders; // for _1
    word->bln_boxes->ProcessMatchedBlobs(*word->rebuild_word,
                                         std::bind(acceptIfGoodQuality, word, _1));
  }
}

int16_t Tesseract::count_outline_errs(char c, int16_t outline_count) {
  int expected_outline_count;

  if (outlines_odd.contains(c))
    return 0; // Don't use this char
  else if (outlines_2.contains(c))
    expected_outline_count = 2;
  else
    expected_outline_count = 1;
  return abs(outline_count - expected_outline_count);
}

void Tesseract::quality_based_rejection(PAGE_RES_IT &page_res_it, bool good_quality_doc) {
  if ((tessedit_good_quality_unrej && good_quality_doc))
    unrej_good_quality_words(page_res_it);
  doc_and_block_rejection(page_res_it, good_quality_doc);
  if (unlv_tilde_crunching) {
    tilde_crunch(page_res_it);
    tilde_delete(page_res_it);
  }
}

/*************************************************************************
 * unrej_good_quality_words()
 * Accept potential rejects in words which pass the following checks:
 *    - Contains a potential reject
 *    - Word looks like a sensible alpha word.
 *    - Word segmentation is the same as the original image
 *    - All characters have the expected number of outlines
 * NOTE - the rejection counts are recalculated after unrejection
 *      - CAN'T do it in a single pass without a bit of fiddling
 *    - keep it simple but inefficient
 *************************************************************************/
void Tesseract::unrej_good_quality_words( // unreject potential
    PAGE_RES_IT &page_res_it) {
  WERD_RES *word;
  ROW_RES *current_row;
  BLOCK_RES *current_block;
  int i;

  page_res_it.restart_page();
  while (page_res_it.word() != nullptr) {
    check_debug_pt(page_res_it.word(), 100);
    if (bland_unrej) {
      word = page_res_it.word();
      for (i = 0; i < word->reject_map.length(); i++) {
        if (word->reject_map[i].accept_if_good_quality())
          word->reject_map[i].setrej_quality_accept();
      }
      page_res_it.forward();
    } else if ((page_res_it.row()->char_count > 0) &&
               ((page_res_it.row()->rej_count /
                 static_cast<float>(page_res_it.row()->char_count)) <= quality_rowrej_pc)) {
      word = page_res_it.word();
      if (word->reject_map.quality_recoverable_rejects() &&
          (tessedit_unrej_any_wd ||
           acceptable_word_string(*word->uch_set, word->best_choice->unichar_string().c_str(),
                                  word->best_choice->unichar_lengths().c_str()) !=
               AC_UNACCEPTABLE)) {
        unrej_good_chs(word);
      }
      page_res_it.forward();
    } else {
      // Skip to end of dodgy row.
      current_row = page_res_it.row();
      while ((page_res_it.word() != nullptr) && (page_res_it.row() == current_row))
        page_res_it.forward();
    }
    check_debug_pt(page_res_it.word(), 110);
  }
  page_res_it.restart_page();
  page_res_it.page_res->char_count = 0;
  page_res_it.page_res->rej_count = 0;
  current_block = nullptr;
  current_row = nullptr;
  while (page_res_it.word() != nullptr) {
    if (current_block != page_res_it.block()) {
      current_block = page_res_it.block();
      current_block->char_count = 0;
      current_block->rej_count = 0;
    }
    if (current_row != page_res_it.row()) {
      current_row = page_res_it.row();
      current_row->char_count = 0;
      current_row->rej_count = 0;
      current_row->whole_word_rej_count = 0;
    }
    page_res_it.rej_stat_word();
    page_res_it.forward();
  }
}

/*************************************************************************
 * doc_and_block_rejection()
 *
 * If the page has too many rejects - reject all of it.
 * If any block has too many rejects - reject all words in the block
 *************************************************************************/

void Tesseract::doc_and_block_rejection( // reject big chunks
    PAGE_RES_IT &page_res_it, bool good_quality_doc) {
  int16_t block_no = 0;
  int16_t row_no = 0;
  BLOCK_RES *current_block;
  ROW_RES *current_row;

  bool rej_word;
  bool prev_word_rejected;
  int16_t char_quality = 0;
  int16_t accepted_char_quality;

  if (page_res_it.page_res->rej_count * 100.0 / page_res_it.page_res->char_count >
      tessedit_reject_doc_percent) {
    reject_whole_page(page_res_it);
    if (tessedit_debug_doc_rejection) {
      tprintf("REJECT ALL #chars: %d #Rejects: %d; \n", page_res_it.page_res->char_count,
              page_res_it.page_res->rej_count);
    }
  } else {
    if (tessedit_debug_doc_rejection) {
      tprintf("NO PAGE REJECTION #chars: %d  # Rejects: %d; \n", page_res_it.page_res->char_count,
              page_res_it.page_res->rej_count);
    }

    /* Walk blocks testing for block rejection */

    page_res_it.restart_page();
    WERD_RES *word;
    while ((word = page_res_it.word()) != nullptr) {
      current_block = page_res_it.block();
      block_no = current_block->block->pdblk.index();
      if (current_block->char_count > 0 &&
          (current_block->rej_count * 100.0 / current_block->char_count) >
              tessedit_reject_block_percent) {
        if (tessedit_debug_block_rejection) {
          tprintf("REJECTING BLOCK %d  #chars: %d;  #Rejects: %d\n", block_no,
                  current_block->char_count, current_block->rej_count);
        }
        prev_word_rejected = false;
        while ((word = page_res_it.word()) != nullptr && (page_res_it.block() == current_block)) {
          if (tessedit_preserve_blk_rej_perfect_wds) {
            rej_word = word->reject_map.reject_count() > 0 ||
                       word->reject_map.length() < tessedit_preserve_min_wd_len;
            if (rej_word && tessedit_dont_blkrej_good_wds &&
                word->reject_map.length() >= tessedit_preserve_min_wd_len &&
                acceptable_word_string(*word->uch_set, word->best_choice->unichar_string().c_str(),
                                       word->best_choice->unichar_lengths().c_str()) !=
                    AC_UNACCEPTABLE) {
              word_char_quality(word, &char_quality, &accepted_char_quality);
              rej_word = char_quality != word->reject_map.length();
            }
          } else {
            rej_word = true;
          }
          if (rej_word) {
            /*
  Reject spacing if both current and prev words are rejected.
  NOTE - this is NOT restricted to FUZZY spaces. - When tried this
  generated more space errors.
*/
            if (tessedit_use_reject_spaces && prev_word_rejected &&
                page_res_it.prev_row() == page_res_it.row() && word->word->space() == 1)
              word->reject_spaces = true;
            word->reject_map.rej_word_block_rej();
          }
          prev_word_rejected = rej_word;
          page_res_it.forward();
        }
      } else {
        if (tessedit_debug_block_rejection) {
          tprintf("NOT REJECTING BLOCK %d #chars: %d  # Rejects: %d; \n", block_no,
                  page_res_it.block()->char_count, page_res_it.block()->rej_count);
        }

        /* Walk rows in block testing for row rejection */
        row_no = 0;
        while (page_res_it.word() != nullptr && page_res_it.block() == current_block) {
          current_row = page_res_it.row();
          row_no++;
          /* Reject whole row if:
  fraction of chars on row which are rejected exceed a limit AND
  fraction rejects which occur in WHOLE WERD rejects is LESS THAN a
  limit
*/
          if (current_row->char_count > 0 &&
              (current_row->rej_count * 100.0 / current_row->char_count) >
                  tessedit_reject_row_percent &&
              (current_row->whole_word_rej_count * 100.0 / current_row->rej_count) <
                  tessedit_whole_wd_rej_row_percent) {
            if (tessedit_debug_block_rejection) {
              tprintf("REJECTING ROW %d  #chars: %d;  #Rejects: %d\n", row_no,
                      current_row->char_count, current_row->rej_count);
            }
            prev_word_rejected = false;
            while ((word = page_res_it.word()) != nullptr && page_res_it.row() == current_row) {
              /* Preserve words on good docs unless they are mostly rejected*/
              if (!tessedit_row_rej_good_docs && good_quality_doc) {
                rej_word = word->reject_map.reject_count() /
                               static_cast<float>(word->reject_map.length()) >
                           tessedit_good_doc_still_rowrej_wd;
              } else if (tessedit_preserve_row_rej_perfect_wds) {
                /* Preserve perfect words anyway */
                rej_word = word->reject_map.reject_count() > 0 ||
                           word->reject_map.length() < tessedit_preserve_min_wd_len;
                if (rej_word && tessedit_dont_rowrej_good_wds &&
                    word->reject_map.length() >= tessedit_preserve_min_wd_len &&
                    acceptable_word_string(
                        *word->uch_set, word->best_choice->unichar_string().c_str(),
                        word->best_choice->unichar_lengths().c_str()) != AC_UNACCEPTABLE) {
                  word_char_quality(word, &char_quality, &accepted_char_quality);
                  rej_word = char_quality != word->reject_map.length();
                }
              } else {
                rej_word = true;
              }
              if (rej_word) {
                /*
  Reject spacing if both current and prev words are rejected.
  NOTE - this is NOT restricted to FUZZY spaces. - When tried
  this generated more space errors.
*/
                if (tessedit_use_reject_spaces && prev_word_rejected &&
                    page_res_it.prev_row() == page_res_it.row() && word->word->space() == 1)
                  word->reject_spaces = true;
                word->reject_map.rej_word_row_rej();
              }
              prev_word_rejected = rej_word;
              page_res_it.forward();
            }
          } else {
            if (tessedit_debug_block_rejection) {
              tprintf("NOT REJECTING ROW %d #chars: %d  # Rejects: %d; \n", row_no,
                      current_row->char_count, current_row->rej_count);
            }
            while (page_res_it.word() != nullptr && page_res_it.row() == current_row)
              page_res_it.forward();
          }
        }
      }
    }
  }
}

/*************************************************************************
 * reject_whole_page()
 * Don't believe any of it - set the reject map to 00..00 in all words
 *
 *************************************************************************/

void reject_whole_page(PAGE_RES_IT &page_res_it) {
  page_res_it.restart_page();
  while (page_res_it.word() != nullptr) {
    page_res_it.word()->reject_map.rej_word_doc_rej();
    page_res_it.forward();
  }
  // whole page is rejected
  page_res_it.page_res->rejected = true;
}

void Tesseract::tilde_crunch(PAGE_RES_IT &page_res_it) {
  WERD_RES *word;
  GARBAGE_LEVEL garbage_level;
  PAGE_RES_IT copy_it;
  bool prev_potential_marked = false;
  bool found_terrible_word = false;
  bool ok_dict_word;

  page_res_it.restart_page();
  while (page_res_it.word() != nullptr) {
    POLY_BLOCK *pb = page_res_it.block()->block->pdblk.poly_block();
    if (pb != nullptr && !pb->IsText()) {
      page_res_it.forward();
      continue;
    }
    word = page_res_it.word();

    if (crunch_early_convert_bad_unlv_chs)
      convert_bad_unlv_chs(word);

    if (crunch_early_merge_tess_fails)
      word->merge_tess_fails();

    if (word->reject_map.accept_count() != 0) {
      found_terrible_word = false;
      // Forget earlier potential crunches
      prev_potential_marked = false;
    } else {
      ok_dict_word = safe_dict_word(word);
      garbage_level = garbage_word(word, ok_dict_word);

      if ((garbage_level != G_NEVER_CRUNCH) && (terrible_word_crunch(word, garbage_level))) {
        if (crunch_debug > 0) {
          tprintf("T CRUNCHING: \"%s\"\n", word->best_choice->unichar_string().c_str());
        }
        word->unlv_crunch_mode = CR_KEEP_SPACE;
        if (prev_potential_marked) {
          while (copy_it.word() != word) {
            if (crunch_debug > 0) {
              tprintf("P1 CRUNCHING: \"%s\"\n",
                      copy_it.word()->best_choice->unichar_string().c_str());
            }
            copy_it.word()->unlv_crunch_mode = CR_KEEP_SPACE;
            copy_it.forward();
          }
          prev_potential_marked = false;
        }
        found_terrible_word = true;
      } else if ((garbage_level != G_NEVER_CRUNCH) &&
                 (potential_word_crunch(word, garbage_level, ok_dict_word))) {
        if (found_terrible_word) {
          if (crunch_debug > 0) {
            tprintf("P2 CRUNCHING: \"%s\"\n", word->best_choice->unichar_string().c_str());
          }
          word->unlv_crunch_mode = CR_KEEP_SPACE;
        } else if (!prev_potential_marked) {
          copy_it = page_res_it;
          prev_potential_marked = true;
          if (crunch_debug > 1) {
            tprintf("P3 CRUNCHING: \"%s\"\n", word->best_choice->unichar_string().c_str());
          }
        }
      } else {
        found_terrible_word = false;
        // Forget earlier potential crunches
        prev_potential_marked = false;
        if (crunch_debug > 2) {
          tprintf("NO CRUNCH: \"%s\"\n", word->best_choice->unichar_string().c_str());
        }
      }
    }
    page_res_it.forward();
  }
}

bool Tesseract::terrible_word_crunch(WERD_RES *word, GARBAGE_LEVEL garbage_level) {
  float rating_per_ch;
  int adjusted_len;
  int crunch_mode = 0;

  if ((word->best_choice->unichar_string().length() == 0) ||
      (strspn(word->best_choice->unichar_string().c_str(), " ") ==
       word->best_choice->unichar_string().size()))
    crunch_mode = 1;
  else {
    adjusted_len = word->reject_map.length();
    if (adjusted_len > crunch_rating_max)
      adjusted_len = crunch_rating_max;
    rating_per_ch = word->best_choice->rating() / adjusted_len;

    if (rating_per_ch > crunch_terrible_rating)
      crunch_mode = 2;
    else if (crunch_terrible_garbage && (garbage_level == G_TERRIBLE))
      crunch_mode = 3;
    else if ((word->best_choice->certainty() < crunch_poor_garbage_cert) && (garbage_level != G_OK))
      crunch_mode = 4;
    else if ((rating_per_ch > crunch_poor_garbage_rate) && (garbage_level != G_OK))
      crunch_mode = 5;
  }
  if (crunch_mode > 0) {
    if (crunch_debug > 2) {
      tprintf("Terrible_word_crunch (%d) on \"%s\"\n", crunch_mode,
              word->best_choice->unichar_string().c_str());
    }
    return true;
  } else
    return false;
}

bool Tesseract::potential_word_crunch(WERD_RES *word, GARBAGE_LEVEL garbage_level,
                                      bool ok_dict_word) {
  float rating_per_ch;
  int adjusted_len;
  const char *str = word->best_choice->unichar_string().c_str();
  const char *lengths = word->best_choice->unichar_lengths().c_str();
  bool word_crunchable;
  int poor_indicator_count = 0;

  word_crunchable =
      !crunch_leave_accept_strings || word->reject_map.length() < 3 ||
      (acceptable_word_string(*word->uch_set, str, lengths) == AC_UNACCEPTABLE && !ok_dict_word);

  adjusted_len = word->reject_map.length();
  if (adjusted_len > 10)
    adjusted_len = 10;
  rating_per_ch = word->best_choice->rating() / adjusted_len;

  if (rating_per_ch > crunch_pot_poor_rate) {
    if (crunch_debug > 2) {
      tprintf("Potential poor rating on \"%s\"\n", word->best_choice->unichar_string().c_str());
    }
    poor_indicator_count++;
  }

  if (word_crunchable && word->best_choice->certainty() < crunch_pot_poor_cert) {
    if (crunch_debug > 2) {
      tprintf("Potential poor cert on \"%s\"\n", word->best_choice->unichar_string().c_str());
    }
    poor_indicator_count++;
  }

  if (garbage_level != G_OK) {
    if (crunch_debug > 2) {
      tprintf("Potential garbage on \"%s\"\n", word->best_choice->unichar_string().c_str());
    }
    poor_indicator_count++;
  }
  return poor_indicator_count >= crunch_pot_indicators;
}

void Tesseract::tilde_delete(PAGE_RES_IT &page_res_it) {
  WERD_RES *word;
  PAGE_RES_IT copy_it;
  bool deleting_from_bol = false;
  bool marked_delete_point = false;
  int16_t debug_delete_mode;
  CRUNCH_MODE delete_mode;
  int16_t x_debug_delete_mode;
  CRUNCH_MODE x_delete_mode;

  page_res_it.restart_page();
  while (page_res_it.word() != nullptr) {
    word = page_res_it.word();

    delete_mode = word_deletable(word, debug_delete_mode);
    if (delete_mode != CR_NONE) {
      if (word->word->flag(W_BOL) || deleting_from_bol) {
        if (crunch_debug > 0) {
          tprintf("BOL CRUNCH DELETING(%d): \"%s\"\n", debug_delete_mode,
                  word->best_choice->unichar_string().c_str());
        }
        word->unlv_crunch_mode = delete_mode;
        deleting_from_bol = true;
      } else if (word->word->flag(W_EOL)) {
        if (marked_delete_point) {
          while (copy_it.word() != word) {
            x_delete_mode = word_deletable(copy_it.word(), x_debug_delete_mode);
            if (crunch_debug > 0) {
              tprintf("EOL CRUNCH DELETING(%d): \"%s\"\n", x_debug_delete_mode,
                      copy_it.word()->best_choice->unichar_string().c_str());
            }
            copy_it.word()->unlv_crunch_mode = x_delete_mode;
            copy_it.forward();
          }
        }
        if (crunch_debug > 0) {
          tprintf("EOL CRUNCH DELETING(%d): \"%s\"\n", debug_delete_mode,
                  word->best_choice->unichar_string().c_str());
        }
        word->unlv_crunch_mode = delete_mode;
        deleting_from_bol = false;
        marked_delete_point = false;
      } else {
        if (!marked_delete_point) {
          copy_it = page_res_it;
          marked_delete_point = true;
        }
      }
    } else {
      deleting_from_bol = false;
      // Forget earlier potential crunches
      marked_delete_point = false;
    }
    /*
  The following step has been left till now as the tess fails are used to
  determine if the word is deletable.
*/
    if (!crunch_early_merge_tess_fails)
      word->merge_tess_fails();
    page_res_it.forward();
  }
}

void Tesseract::convert_bad_unlv_chs(WERD_RES *word_res) {
  int i;
  UNICHAR_ID unichar_dash = word_res->uch_set->unichar_to_id("-");
  UNICHAR_ID unichar_space = word_res->uch_set->unichar_to_id(" ");
  UNICHAR_ID unichar_tilde = word_res->uch_set->unichar_to_id("~");
  UNICHAR_ID unichar_pow = word_res->uch_set->unichar_to_id("^");
  for (i = 0; i < word_res->reject_map.length(); ++i) {
    if (word_res->best_choice->unichar_id(i) == unichar_tilde) {
      word_res->best_choice->set_unichar_id(unichar_dash, i);
      if (word_res->reject_map[i].accepted())
        word_res->reject_map[i].setrej_unlv_rej();
    }
    if (word_res->best_choice->unichar_id(i) == unichar_pow) {
      word_res->best_choice->set_unichar_id(unichar_space, i);
      if (word_res->reject_map[i].accepted())
        word_res->reject_map[i].setrej_unlv_rej();
    }
  }
}

GARBAGE_LEVEL Tesseract::garbage_word(WERD_RES *word, bool ok_dict_word) {
  enum STATES {
    JUNK,
    FIRST_UPPER,
    FIRST_LOWER,
    FIRST_NUM,
    SUBSEQUENT_UPPER,
    SUBSEQUENT_LOWER,
    SUBSEQUENT_NUM
  };
  const char *str = word->best_choice->unichar_string().c_str();
  const char *lengths = word->best_choice->unichar_lengths().c_str();
  STATES state = JUNK;
  int len = 0;
  int isolated_digits = 0;
  int isolated_alphas = 0;
  int bad_char_count = 0;
  int tess_rejs = 0;
  int dodgy_chars = 0;
  int ok_chars;
  UNICHAR_ID last_char = -1;
  int alpha_repetition_count = 0;
  int longest_alpha_repetition_count = 0;
  int longest_lower_run_len = 0;
  int lower_string_count = 0;
  int longest_upper_run_len = 0;
  int upper_string_count = 0;
  int total_alpha_count = 0;
  int total_digit_count = 0;

  for (; *str != '\0'; str += *(lengths++)) {
    len++;
    if (word->uch_set->get_isupper(str, *lengths)) {
      total_alpha_count++;
      switch (state) {
        case SUBSEQUENT_UPPER:
        case FIRST_UPPER:
          state = SUBSEQUENT_UPPER;
          upper_string_count++;
          if (longest_upper_run_len < upper_string_count)
            longest_upper_run_len = upper_string_count;
          if (last_char == word->uch_set->unichar_to_id(str, *lengths)) {
            alpha_repetition_count++;
            if (longest_alpha_repetition_count < alpha_repetition_count) {
              longest_alpha_repetition_count = alpha_repetition_count;
            }
          } else {
            last_char = word->uch_set->unichar_to_id(str, *lengths);
            alpha_repetition_count = 1;
          }
          break;
        case FIRST_NUM:
          isolated_digits++;
          // Fall through.
        default:
          state = FIRST_UPPER;
          last_char = word->uch_set->unichar_to_id(str, *lengths);
          alpha_repetition_count = 1;
          upper_string_count = 1;
          break;
      }
    } else if (word->uch_set->get_islower(str, *lengths)) {
      total_alpha_count++;
      switch (state) {
        case SUBSEQUENT_LOWER:
        case FIRST_LOWER:
          state = SUBSEQUENT_LOWER;
          lower_string_count++;
          if (longest_lower_run_len < lower_string_count)
            longest_lower_run_len = lower_string_count;
          if (last_char == word->uch_set->unichar_to_id(str, *lengths)) {
            alpha_repetition_count++;
            if (longest_alpha_repetition_count < alpha_repetition_count) {
              longest_alpha_repetition_count = alpha_repetition_count;
            }
          } else {
            last_char = word->uch_set->unichar_to_id(str, *lengths);
            alpha_repetition_count = 1;
          }
          break;
        case FIRST_NUM:
          isolated_digits++;
          // Fall through.
        default:
          state = FIRST_LOWER;
          last_char = word->uch_set->unichar_to_id(str, *lengths);
          alpha_repetition_count = 1;
          lower_string_count = 1;
          break;
      }
    } else if (word->uch_set->get_isdigit(str, *lengths)) {
      total_digit_count++;
      switch (state) {
        case FIRST_NUM:
          state = SUBSEQUENT_NUM;
        case SUBSEQUENT_NUM:
          break;
        case FIRST_UPPER:
        case FIRST_LOWER:
          isolated_alphas++;
          // Fall through.
        default:
          state = FIRST_NUM;
          break;
      }
    } else {
      if (*lengths == 1 && *str == ' ')
        tess_rejs++;
      else
        bad_char_count++;
      switch (state) {
        case FIRST_NUM:
          isolated_digits++;
          break;
        case FIRST_UPPER:
        case FIRST_LOWER:
          isolated_alphas++;
        default:
          break;
      }
      state = JUNK;
    }
  }

  switch (state) {
    case FIRST_NUM:
      isolated_digits++;
      break;
    case FIRST_UPPER:
    case FIRST_LOWER:
      isolated_alphas++;
    default:
      break;
  }

  if (crunch_include_numerals) {
    total_alpha_count += total_digit_count - isolated_digits;
  }

  if (crunch_leave_ok_strings && len >= 4 && 2 * (total_alpha_count - isolated_alphas) > len &&
      longest_alpha_repetition_count < crunch_long_repetitions) {
    if ((crunch_accept_ok &&
         acceptable_word_string(*word->uch_set, str, lengths) != AC_UNACCEPTABLE) ||
        longest_lower_run_len > crunch_leave_lc_strings ||
        longest_upper_run_len > crunch_leave_uc_strings)
      return G_NEVER_CRUNCH;
  }
  if (word->reject_map.length() > 1 && strpbrk(str, " ") == nullptr &&
      (word->best_choice->permuter() == SYSTEM_DAWG_PERM ||
       word->best_choice->permuter() == FREQ_DAWG_PERM ||
       word->best_choice->permuter() == USER_DAWG_PERM ||
       word->best_choice->permuter() == NUMBER_PERM ||
       acceptable_word_string(*word->uch_set, str, lengths) != AC_UNACCEPTABLE || ok_dict_word))
    return G_OK;

  ok_chars = len - bad_char_count - isolated_digits - isolated_alphas - tess_rejs;

  if (crunch_debug > 3) {
    tprintf("garbage_word: \"%s\"\n", word->best_choice->unichar_string().c_str());
    tprintf("LEN: %d  bad: %d  iso_N: %d  iso_A: %d  rej: %d\n", len, bad_char_count,
            isolated_digits, isolated_alphas, tess_rejs);
  }
  if (bad_char_count == 0 && tess_rejs == 0 &&
      (len > isolated_digits + isolated_alphas || len <= 2))
    return G_OK;

  if (tess_rejs > ok_chars || (tess_rejs > 0 && (bad_char_count + tess_rejs) * 2 > len))
    return G_TERRIBLE;

  if (len > 4) {
    dodgy_chars = 2 * tess_rejs + bad_char_count + isolated_digits + isolated_alphas;
    if (dodgy_chars > 5 || (dodgy_chars / static_cast<float>(len)) > 0.5)
      return G_DODGY;
    else
      return G_OK;
  } else {
    dodgy_chars = 2 * tess_rejs + bad_char_count;
    if ((len == 4 && dodgy_chars > 2) || (len == 3 && dodgy_chars > 2) || dodgy_chars >= len)
      return G_DODGY;
    else
      return G_OK;
  }
}

/*************************************************************************
 * word_deletable()
 *     DELETE WERDS AT ENDS OF ROWS IF
 *        Word is crunched &&
 *        ( string length = 0                                          OR
 *          > 50% of chars are "|" (before merging)                    OR
 *          certainty < -10                                            OR
 *          rating /char > 60                                          OR
 *          TOP of word is more than 0.5 xht BELOW baseline            OR
 *          BOTTOM of word is more than 0.5 xht ABOVE xht              OR
 *          length of word < 3xht                                      OR
 *          height of word < 0.7 xht                                   OR
 *          height of word > 3.0 xht                                   OR
 *          >75% of the outline BBs have longest dimension < 0.5xht
 *************************************************************************/

CRUNCH_MODE Tesseract::word_deletable(WERD_RES *word, int16_t &delete_mode) {
  int word_len = word->reject_map.length();
  float rating_per_ch;
  TBOX box; // BB of word

  if (word->unlv_crunch_mode == CR_NONE) {
    delete_mode = 0;
    return CR_NONE;
  }

  if (word_len == 0) {
    delete_mode = 1;
    return CR_DELETE;
  }

  if (word->rebuild_word != nullptr) {
    // Cube leaves rebuild_word nullptr.
    box = word->rebuild_word->bounding_box();
    if (box.height() < crunch_del_min_ht * kBlnXHeight) {
      delete_mode = 4;
      return CR_DELETE;
    }

    if (noise_outlines(word->rebuild_word)) {
      delete_mode = 5;
      return CR_DELETE;
    }
  }

  if ((failure_count(word) * 1.5) > word_len) {
    delete_mode = 2;
    return CR_LOOSE_SPACE;
  }

  if (word->best_choice->certainty() < crunch_del_cert) {
    delete_mode = 7;
    return CR_LOOSE_SPACE;
  }

  rating_per_ch = word->best_choice->rating() / word_len;

  if (rating_per_ch > crunch_del_rating) {
    delete_mode = 8;
    return CR_LOOSE_SPACE;
  }

  if (box.top() < kBlnBaselineOffset - crunch_del_low_word * kBlnXHeight) {
    delete_mode = 9;
    return CR_LOOSE_SPACE;
  }

  if (box.bottom() > kBlnBaselineOffset + crunch_del_high_word * kBlnXHeight) {
    delete_mode = 10;
    return CR_LOOSE_SPACE;
  }

  if (box.height() > crunch_del_max_ht * kBlnXHeight) {
    delete_mode = 11;
    return CR_LOOSE_SPACE;
  }

  if (box.width() < crunch_del_min_width * kBlnXHeight) {
    delete_mode = 3;
    return CR_LOOSE_SPACE;
  }

  delete_mode = 0;
  return CR_NONE;
}

int16_t Tesseract::failure_count(WERD_RES *word) {
  const char *str = word->best_choice->unichar_string().c_str();
  int tess_rejs = 0;

  for (; *str != '\0'; str++) {
    if (*str == ' ')
      tess_rejs++;
  }
  return tess_rejs;
}

bool Tesseract::noise_outlines(TWERD *word) {
  TBOX box; // BB of outline
  int16_t outline_count = 0;
  int16_t small_outline_count = 0;
  int16_t max_dimension;
  float small_limit = kBlnXHeight * crunch_small_outlines_size;

  for (int b = 0; b < word->NumBlobs(); ++b) {
    TBLOB *blob = word->blobs[b];
    for (TESSLINE *ol = blob->outlines; ol != nullptr; ol = ol->next) {
      outline_count++;
      box = ol->bounding_box();
      if (box.height() > box.width())
        max_dimension = box.height();
      else
        max_dimension = box.width();
      if (max_dimension < small_limit)
        small_outline_count++;
    }
  }
  return small_outline_count >= outline_count;
}

} // namespace tesseract