/**********************************************************************
 * File:        wordseg.cpp  (Formerly wspace.c)
 * Description: Code to segment the blobs into words.
 * Author:      Ray Smith
 *
 * (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.
 *
 **********************************************************************/

#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 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() != nullptr) {
          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() != nullptr)
          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<int16_t>(row->kern_size),
                            static_cast<int16_t>(row->space_size));
    WERD_IT word_it(real_row->word_list());
    WERD* word = new WERD(&cblobs, 0, nullptr);
    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),
                        !bool(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
        bool 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 =
        static_cast<int32_t>(ceil (row->pr_space -
        (row->pr_space -
        row->pr_nonsp) * textord_words_definite_spread));
      row->max_nonspace =
        static_cast<int32_t>(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, static_cast<int16_t>(row->fixed_pitch), row);
    }
#endif
  }
}


/**
 * @name row_words
 *
 * Compute the max nonspace and min space for the row.
 */

int32_t row_words(                  //compute space size
        TO_BLOCK* block,  //block it came from
        TO_ROW* row,      //row to operate on
        int32_t maxwidth,   //max expected space size
        FCOORD rotation,  //for drawing
        bool testing_on  //for debug
) {
  bool testing_row;             //contains testpt
  bool prev_valid;              //if decent size
  int32_t prev_x;                //end of prev blob
  int32_t cluster_count;         //no of clusters
  int32_t gap_index;             //which cluster
  int32_t 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 =
    static_cast<int32_t>(block->xheight * textord_wordstats_smooth_factor + 1.5);
  //      if (testing_on)
  //              tprintf("Row smooth factor=%d\n",smooth_factor);
  prev_valid = false;
  prev_x = -INT32_MAX;
  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);
  }
  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 ();
      if (prev_valid && blob_box.left () - prev_x < maxwidth) {
        gap_stats.add (blob_box.left () - prev_x, 1);
      }
      prev_valid = true;
      prev_x = blob_box.right ();
    }
  }
  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 =
    static_cast<int32_t>(ceil (upper - (upper - lower) * textord_words_definite_spread));
  row->max_nonspace =
    static_cast<int32_t>(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_t row_words2(                  //compute space size
        TO_BLOCK* block,  //block it came from
        TO_ROW* row,      //row to operate on
        int32_t maxwidth,   //max expected space size
        FCOORD rotation,  //for drawing
        bool testing_on  //for debug
) {
  bool prev_valid;              //if decent size
  bool this_valid;              //current blob big enough
  int32_t prev_x;                  //end of prev blob
  int32_t min_width;               //min interesting width
  int32_t valid_count;             //good gaps
  int32_t total_count;             //total gaps
  int32_t cluster_count;           //no of clusters
  int32_t prev_count;              //previous cluster_count
  int32_t gap_index;               //which cluster
  int32_t 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 =
    static_cast<int32_t>(block->xheight * textord_wordstats_smooth_factor + 1.5);
  //      if (testing_on)
  //              tprintf("Row smooth factor=%d\n",smooth_factor);
  prev_valid = false;
  prev_x = -INT16_MAX;
  const bool testing_row = false;
                                 //min blob size
  min_width = static_cast<int32_t>(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;
      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 = -INT16_MAX;
    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 =
    static_cast<int32_t>(ceil (upper - (upper - lower) * textord_words_definite_spread));
  row->max_nonspace =
    static_cast<int32_t>(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 = nullptr;          //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->pdblk.poly_block();
      if (textord_chopper_test) {
        real_row = textord->make_blob_words (row, rotation);
      } else if (textord_force_make_prop_words ||
                 (pb != nullptr && !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 != nullptr) {
                                 //put row in block
      real_row_it.add_after_then_move (real_row);
    }
  }
  block->block->set_stats (block->fixed_pitch == 0, static_cast<int16_t>(block->kern_size),
    static_cast<int16_t>(block->space_size),
    static_cast<int16_t>(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 nullptr;
  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,
    static_cast<int16_t>(block->kern_size), static_cast<int16_t>(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_t blobcount,      //no of blobs to use
                     bool bol,            //start of line
                     uint8_t 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_t blobindex;               // in row

  for (blobindex = 0; blobindex < blobcount; blobindex++) {
    bblob = box_it->extract();
    if (bblob->joined_to_prev()) {
      if (bblob->cblob() != nullptr) {
        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() != nullptr)
        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, nullptr);

  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;
}