/**********************************************************************

 * File:        devanagari_processing.cpp

 * Description: Methods to process images containing devanagari symbols,

 *              prior to classification.

 * Author:      Shobhit Saxena

 *

 * (C) Copyright 2008, Google Inc.

 ** Licensed under the Apache License, Version 2.0 (the "License");

 ** you may not use this file except in compliance with the License.

 ** You may obtain a copy of the License at

 ** http://www.apache.org/licenses/LICENSE-2.0

 ** Unless required by applicable law or agreed to in writing, software

 ** distributed under the License is distributed on an "AS IS" BASIS,

 ** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

 ** See the License for the specific language governing permissions and

 ** limitations under the License.

 *

 **********************************************************************/

#ifdef HAVE_CONFIG_H

#  include "config_auto.h"

#endif

#include "devanagari_processing.h"

#include "debugpixa.h"

#include "statistc.h"

#include "tordmain.h"

#include <allheaders.h>

namespace tesseract {

// Flags controlling the debugging information for shiro-rekha splitting

// strategies.

INT_VAR(devanagari_split_debuglevel, 0, "Debug level for split shiro-rekha process.");

BOOL_VAR(devanagari_split_debugimage, 0,

         "Whether to create a debug image for split shiro-rekha process.");

ShiroRekhaSplitter::ShiroRekhaSplitter() :

  orig_pix_(nullptr),

  splitted_image_(nullptr),

  pageseg_split_strategy_(NO_SPLIT),

  ocr_split_strategy_(NO_SPLIT),

  debug_image_(nullptr),

  segmentation_block_list_(nullptr),

  global_xheight_(kUnspecifiedXheight),

  perform_close_(false)

{

}

ShiroRekhaSplitter::~ShiroRekhaSplitter() {

  Clear();

}

void ShiroRekhaSplitter::Clear() {

  orig_pix_.destroy();

  splitted_image_.destroy();

  pageseg_split_strategy_ = NO_SPLIT;

  ocr_split_strategy_ = NO_SPLIT;

  debug_image_.destroy();

  segmentation_block_list_ = nullptr;

  global_xheight_ = kUnspecifiedXheight;

  perform_close_ = false;

}

// On setting the input image, a clone of it is owned by this class.

void ShiroRekhaSplitter::set_orig_pix(Image pix) {

  if (orig_pix_) {

    orig_pix_.destroy();

  }

  orig_pix_ = pix.clone();

}

// Top-level method to perform splitting based on current settings.

// Returns true if a split was actually performed.

// split_for_pageseg should be true if the splitting is being done prior to

// page segmentation. This mode uses the flag

// pageseg_devanagari_split_strategy to determine the splitting strategy.

bool ShiroRekhaSplitter::Split(bool split_for_pageseg, DebugPixa *pixa_debug) {

  SplitStrategy split_strategy = split_for_pageseg ? pageseg_split_strategy_ : ocr_split_strategy_;

  if (split_strategy == NO_SPLIT) {

    return false; // Nothing to do.

  }

  ASSERT_HOST(split_strategy == MINIMAL_SPLIT || split_strategy == MAXIMAL_SPLIT);

  ASSERT_HOST(orig_pix_);

  if (devanagari_split_debuglevel > 0) {

    tprintf("Splitting shiro-rekha ...\n");

    tprintf("Split strategy = %s\n", split_strategy == MINIMAL_SPLIT ? "Minimal" : "Maximal");

    tprintf("Initial pageseg available = %s\n", segmentation_block_list_ ? "yes" : "no");

  }

  // Create a copy of original image to store the splitting output.

  splitted_image_.destroy();

  splitted_image_ = orig_pix_.copy();

  // Initialize debug image if required.

  if (devanagari_split_debugimage) {

    debug_image_.destroy();

    debug_image_ = pixConvertTo32(orig_pix_);

  }

  // Determine all connected components in the input image. A close operation

  // may be required prior to this, depending on the current settings.

  Image pix_for_ccs = orig_pix_.clone();

  if (perform_close_ && global_xheight_ != kUnspecifiedXheight && !segmentation_block_list_) {

    if (devanagari_split_debuglevel > 0) {

      tprintf("Performing a global close operation..\n");

    }

    // A global measure is available for xheight, but no local information

    // exists.

    pix_for_ccs.destroy();

    pix_for_ccs = orig_pix_.copy();

    PerformClose(pix_for_ccs, global_xheight_);

  }

  Pixa *ccs;

  Boxa *tmp_boxa = pixConnComp(pix_for_ccs, &ccs, 8);

  boxaDestroy(&tmp_boxa);

  pix_for_ccs.destroy();

  // Iterate over all connected components. Get their bounding boxes and clip

  // out the image regions corresponding to these boxes from the original image.

  // Conditionally run splitting on each of them.

  Boxa *regions_to_clear = boxaCreate(0);

  int num_ccs = 0;

  if (ccs != nullptr) {

    num_ccs = pixaGetCount(ccs);

  }

  for (int i = 0; i < num_ccs; ++i) {

    Box *box = pixaGetBox(ccs, i, L_CLONE);

    Image word_pix = pixClipRectangle(orig_pix_, box, nullptr);

    ASSERT_HOST(word_pix);

    int xheight = GetXheightForCC(box);

    if (xheight == kUnspecifiedXheight && segmentation_block_list_ && devanagari_split_debugimage) {

      pixRenderBoxArb(debug_image_, box, 1, 255, 0, 0);

    }

    // If some xheight measure is available, attempt to pre-eliminate small

    // blobs from the shiro-rekha process. This is primarily to save the CCs

    // corresponding to punctuation marks/small dots etc which are part of

    // larger graphemes.

    l_int32 x, y, w, h;

    boxGetGeometry(box, &x, &y, &w, &h);

    if (xheight == kUnspecifiedXheight || (w > xheight / 3 && h > xheight / 2)) {

      SplitWordShiroRekha(split_strategy, word_pix, xheight, x, y, regions_to_clear);

    } else if (devanagari_split_debuglevel > 0) {

      tprintf("CC dropped from splitting: %d,%d (%d, %d)\n", x, y, w, h);

    }

    word_pix.destroy();

    boxDestroy(&box);

  }

  // Actually clear the boxes now.

  for (int i = 0; i < boxaGetCount(regions_to_clear); ++i) {

    Box *box = boxaGetBox(regions_to_clear, i, L_CLONE);

    pixClearInRect(splitted_image_, box);

    boxDestroy(&box);

  }

  boxaDestroy(&regions_to_clear);

  pixaDestroy(&ccs);

  if (devanagari_split_debugimage && pixa_debug != nullptr) {

    pixa_debug->AddPix(debug_image_, split_for_pageseg ? "pageseg_split" : "ocr_split");

  }

  return true;

}

// Method to perform a close operation on the input image. The xheight

// estimate decides the size of sel used.

void ShiroRekhaSplitter::PerformClose(Image pix, int xheight_estimate) {

  pixCloseBrick(pix, pix, xheight_estimate / 8, xheight_estimate / 3);

}

// This method resolves the cc bbox to a particular row and returns the row's

// xheight.

int ShiroRekhaSplitter::GetXheightForCC(Box *cc_bbox) {

  if (!segmentation_block_list_) {

    return global_xheight_;

  }

  // Compute the box coordinates in Tesseract's coordinate system.

  l_int32 x, y, w, h;

  boxGetGeometry(cc_bbox, &x, &y, &w, &h);

  TBOX bbox(x, pixGetHeight(orig_pix_) - y - h - 1,

            x + w, pixGetHeight(orig_pix_) - y - 1);

  // Iterate over all blocks.

  BLOCK_IT block_it(segmentation_block_list_);

  for (block_it.mark_cycle_pt(); !block_it.cycled_list(); block_it.forward()) {

    BLOCK *block = block_it.data();

    // Iterate over all rows in the block.

    ROW_IT row_it(block->row_list());

    for (row_it.mark_cycle_pt(); !row_it.cycled_list(); row_it.forward()) {

      ROW *row = row_it.data();

      if (!row->bounding_box().major_overlap(bbox)) {

        continue;

      }

      // Row could be skewed, warped, etc. Use the position of the box to

      // determine the baseline position of the row for that x-coordinate.

      // Create a square TBOX whose baseline's mid-point lies at this point

      // and side is row's xheight. Take the overlap of this box with the input

      // box and check if it is a 'major overlap'. If so, this box lies in this

      // row. In that case, return the xheight for this row.

      float box_middle = 0.5 * (bbox.left() + bbox.right());

      int baseline = static_cast<int>(row->base_line(box_middle) + 0.5);

      TBOX test_box(box_middle - row->x_height() / 2, baseline, box_middle + row->x_height() / 2,

                    static_cast<int>(baseline + row->x_height()));

      // Compute overlap. If it is a major overlap, this is the right row.

      if (bbox.major_overlap(test_box)) {

        return row->x_height();

      }

    }

  }

  // No row found for this bbox.

  return kUnspecifiedXheight;

}

// Returns a list of regions (boxes) which should be cleared in the original

// image so as to perform shiro-rekha splitting. Pix is assumed to carry one

// (or less) word only. Xheight measure could be the global estimate, the row

// estimate, or unspecified. If unspecified, over splitting may occur, since a

// conservative estimate of stroke width along with an associated multiplier

// is used in its place. It is advisable to have a specified xheight when

// splitting for classification/training.

// A vertical projection histogram of all the on-pixels in the input pix is

// computed. The maxima of this histogram is regarded as an approximate location

// of the shiro-rekha. By descending on the maxima's peak on both sides,

// stroke width of shiro-rekha is estimated.

// A horizontal projection histogram is computed for a sub-image of the input

// image, which extends from just below the shiro-rekha down to a certain

// leeway. The leeway depends on the input xheight, if provided, else a

// conservative multiplier on approximate stroke width is used (which may lead

// to over-splitting).

void ShiroRekhaSplitter::SplitWordShiroRekha(SplitStrategy split_strategy, Image pix, int xheight,

                                             int word_left, int word_top, Boxa *regions_to_clear) {

  if (split_strategy == NO_SPLIT) {

    return;

  }

  int width = pixGetWidth(pix);

  int height = pixGetHeight(pix);

  // Statistically determine the yextents of the shiro-rekha.

  int shirorekha_top, shirorekha_bottom, shirorekha_ylevel;

  GetShiroRekhaYExtents(pix, &shirorekha_top, &shirorekha_bottom, &shirorekha_ylevel);

  // Since the shiro rekha is also a stroke, its width is equal to the stroke

  // width.

  int stroke_width = shirorekha_bottom - shirorekha_top + 1;

  // Some safeguards to protect CCs we do not want to be split.

  // These are particularly useful when the word wasn't eliminated earlier

  // because xheight information was unavailable.

  if (shirorekha_ylevel > height / 2) {

    // Shirorekha shouldn't be in the bottom half of the word.

    if (devanagari_split_debuglevel > 0) {

      tprintf("Skipping splitting CC at (%d, %d): shirorekha in lower half..\n", word_left,

              word_top);

    }

    return;

  }

  if (stroke_width > height / 3) {

    // Even the boldest of fonts shouldn't do this.

    if (devanagari_split_debuglevel > 0) {

      tprintf("Skipping splitting CC at (%d, %d): stroke width too huge..\n", word_left, word_top);

    }

    return;

  }

  // Clear the ascender and descender regions of the word.

  // Obtain a vertical projection histogram for the resulting image.

  Box *box_to_clear = boxCreate(0, shirorekha_top - stroke_width / 3, width, 5 * stroke_width / 3);

  Image word_in_xheight = pix.copy();

  pixClearInRect(word_in_xheight, box_to_clear);

  // Also clear any pixels which are below shirorekha_bottom + some leeway.

  // The leeway is set to xheight if the information is available, else it is a

  // multiplier applied to the stroke width.

  int leeway_to_keep = stroke_width * 3;

  if (xheight != kUnspecifiedXheight) {

    // This is because the xheight-region typically includes the shiro-rekha

    // inside it, i.e., the top of the xheight range corresponds to the top of

    // shiro-rekha.

    leeway_to_keep = xheight - stroke_width;

  }

  auto y = shirorekha_bottom + leeway_to_keep;

  boxSetGeometry(box_to_clear, -1, y, -1, height - y);

  pixClearInRect(word_in_xheight, box_to_clear);

  boxDestroy(&box_to_clear);

  PixelHistogram vert_hist;

  vert_hist.ConstructVerticalCountHist(word_in_xheight);

  word_in_xheight.destroy();

  // If the number of black pixel in any column of the image is less than a

  // fraction of the stroke width, treat it as noise / a stray mark. Perform

  // these changes inside the vert_hist data itself, as that is used later on as

  // a bit vector for the final split decision at every column.

  for (int i = 0; i < width; ++i) {

    if (vert_hist.hist()[i] <= stroke_width / 4) {

      vert_hist.hist()[i] = 0;

    } else {

      vert_hist.hist()[i] = 1;

    }

  }

  // In order to split the line at any point, we make sure that the width of the

  // gap is at least half the stroke width.

  int i = 0;

  int cur_component_width = 0;

  while (i < width) {

    if (!vert_hist.hist()[i]) {

      int j = 0;

      while (i + j < width && !vert_hist.hist()[i + j]) {

        ++j;

      }

      if (j >= stroke_width / 2 && cur_component_width >= stroke_width / 2) {

        // Perform a shiro-rekha split. The intervening region lies from i to

        // i+j-1.

        // A minimal single-pixel split makes the estimation of intra- and

        // inter-word spacing easier during page layout analysis,

        // whereas a maximal split may be needed for OCR, depending on

        // how the engine was trained.

        bool minimal_split = (split_strategy == MINIMAL_SPLIT);

        int split_width = minimal_split ? 1 : j;

        int split_left = minimal_split ? i + (j / 2) - (split_width / 2) : i;

        if (!minimal_split || (i != 0 && i + j != width)) {

          Box *box_to_clear =

              boxCreate(word_left + split_left, word_top + shirorekha_top - stroke_width / 3,

                        split_width, 5 * stroke_width / 3);

          if (box_to_clear) {

            boxaAddBox(regions_to_clear, box_to_clear, L_CLONE);

            // Mark this in the debug image if needed.

            if (devanagari_split_debugimage) {

              pixRenderBoxArb(debug_image_, box_to_clear, 1, 128, 255, 128);

            }

            boxDestroy(&box_to_clear);

            cur_component_width = 0;

          }

        }

      }

      i += j;

    } else {

      ++i;

      ++cur_component_width;

    }

  }

}

// Refreshes the words in the segmentation block list by using blobs in the

// input block list.

// The segmentation block list must be set.

void ShiroRekhaSplitter::RefreshSegmentationWithNewBlobs(C_BLOB_LIST *new_blobs) {

  // The segmentation block list must have been specified.

  ASSERT_HOST(segmentation_block_list_);

  if (devanagari_split_debuglevel > 0) {

    tprintf("Before refreshing blobs:\n");

    PrintSegmentationStats(segmentation_block_list_);

    tprintf("New Blobs found: %d\n", new_blobs->length());

  }

  C_BLOB_LIST not_found_blobs;

  RefreshWordBlobsFromNewBlobs(

      segmentation_block_list_, new_blobs,

      ((devanagari_split_debugimage && debug_image_) ? &not_found_blobs : nullptr));

  if (devanagari_split_debuglevel > 0) {

    tprintf("After refreshing blobs:\n");

    PrintSegmentationStats(segmentation_block_list_);

  }

  if (devanagari_split_debugimage && debug_image_) {

    // Plot out the original blobs for which no match was found in the new

    // all_blobs list.

    C_BLOB_IT not_found_it(&not_found_blobs);

    for (not_found_it.mark_cycle_pt(); !not_found_it.cycled_list(); not_found_it.forward()) {

      C_BLOB *not_found = not_found_it.data();

      TBOX not_found_box = not_found->bounding_box();

      Box *box_to_plot = GetBoxForTBOX(not_found_box);

      pixRenderBoxArb(debug_image_, box_to_plot, 1, 255, 0, 255);

      boxDestroy(&box_to_plot);

    }

    // Plot out the blobs unused from all blobs.

    C_BLOB_IT all_blobs_it(new_blobs);

    for (all_blobs_it.mark_cycle_pt(); !all_blobs_it.cycled_list(); all_blobs_it.forward()) {

      C_BLOB *a_blob = all_blobs_it.data();

      Box *box_to_plot = GetBoxForTBOX(a_blob->bounding_box());

      pixRenderBoxArb(debug_image_, box_to_plot, 3, 0, 127, 0);

      boxDestroy(&box_to_plot);

    }

  }

}

// Returns a new box object for the corresponding TBOX, based on the original

// image's coordinate system.

Box *ShiroRekhaSplitter::GetBoxForTBOX(const TBOX &tbox) const {

  return boxCreate(tbox.left(), pixGetHeight(orig_pix_) - tbox.top() - 1, tbox.width(),

                   tbox.height());

}

// This method returns the computed mode-height of blobs in the pix.

// It also prunes very small blobs from calculation.

int ShiroRekhaSplitter::GetModeHeight(Image pix) {

  Boxa *boxa = pixConnComp(pix, nullptr, 8);

  STATS heights(0, pixGetHeight(pix) - 1);

  heights.clear();

  for (int i = 0; i < boxaGetCount(boxa); ++i) {

    Box *box = boxaGetBox(boxa, i, L_CLONE);

    l_int32 x, y, w, h;

    boxGetGeometry(box, &x, &y, &w, &h);

    if (h >= 3 || w >= 3) {

      heights.add(h, 1);

    }

    boxDestroy(&box);

  }

  boxaDestroy(&boxa);

  return heights.mode();

}

// This method returns y-extents of the shiro-rekha computed from the input

// word image.

void ShiroRekhaSplitter::GetShiroRekhaYExtents(Image word_pix, int *shirorekha_top,

                                               int *shirorekha_bottom, int *shirorekha_ylevel) {

  // Compute a histogram from projecting the word on a vertical line.

  PixelHistogram hist_horiz;

  hist_horiz.ConstructHorizontalCountHist(word_pix);

  // Get the ylevel where the top-line exists. This is basically the global

  // maxima in the horizontal histogram.

  int topline_onpixel_count = 0;

  int topline_ylevel = hist_horiz.GetHistogramMaximum(&topline_onpixel_count);

  // Get the upper and lower extents of the shiro rekha.

  int thresh = (topline_onpixel_count * 70) / 100;

  int ulimit = topline_ylevel;

  int llimit = topline_ylevel;

  while (ulimit > 0 && hist_horiz.hist()[ulimit] >= thresh) {

    --ulimit;

  }

  while (llimit < pixGetHeight(word_pix) && hist_horiz.hist()[llimit] >= thresh) {

    ++llimit;

  }

  if (shirorekha_top) {

    *shirorekha_top = ulimit;

  }

  if (shirorekha_bottom) {

    *shirorekha_bottom = llimit;

  }

  if (shirorekha_ylevel) {

    *shirorekha_ylevel = topline_ylevel;

  }

}

// This method returns the global-maxima for the histogram. The frequency of

// the global maxima is returned in count, if specified.

int PixelHistogram::GetHistogramMaximum(int *count) const {

  int best_value = 0;

  for (int i = 0; i < length_; ++i) {

    if (hist_[i] > hist_[best_value]) {

      best_value = i;

    }

  }

  if (count) {

    *count = hist_[best_value];

  }

  return best_value;

}

// Methods to construct histograms from images.

void PixelHistogram::ConstructVerticalCountHist(Image pix) {

  Clear();

  int width = pixGetWidth(pix);

  int height = pixGetHeight(pix);

  hist_ = new int[width];

  length_ = width;

  int wpl = pixGetWpl(pix);

  l_uint32 *data = pixGetData(pix);

  for (int i = 0; i < width; ++i) {

    hist_[i] = 0;

  }

  for (int i = 0; i < height; ++i) {

    l_uint32 *line = data + i * wpl;

    for (int j = 0; j < width; ++j) {

      if (GET_DATA_BIT(line, j)) {

        ++(hist_[j]);

      }

    }

  }

}

void PixelHistogram::ConstructHorizontalCountHist(Image pix) {

  Clear();

  Numa *counts = pixCountPixelsByRow(pix, nullptr);

  length_ = numaGetCount(counts);

  hist_ = new int[length_];

  for (int i = 0; i < length_; ++i) {

    l_int32 val = 0;

    numaGetIValue(counts, i, &val);

    hist_[i] = val;

  }

  numaDestroy(&counts);

}

} // namespace tesseract.