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 (stdout, TRUE);
tprintf ("SPACE stats\n");
cluster_stats[2].print (stdout, FALSE);
tprintf ("NONSPACE stats\n");
cluster_stats[1].print (stdout, FALSE);
}
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;
}
#include "mfcpch.h"
#include <string.h>
#ifdef __UNIX__
#include <assert.h>
#endif
#include "coutln.h"
#include <allheaders.h>
// Include automatically generated configuration file if running autoconf.
#ifdef HAVE_CONFIG_H
#include "config_auto.h"
#endif
ELISTIZE (C_OUTLINE)
ICOORD C_OUTLINE::step_coords[4] = {
ICOORD (-1, 0), ICOORD (0, -1), ICOORD (1, 0), ICOORD (0, 1)
};
/**********************************************************************
* C_OUTLINE::C_OUTLINE
*
* Constructor to build a C_OUTLINE from a CRACKEDGE LOOP.
**********************************************************************/
C_OUTLINE::C_OUTLINE (
//constructor
CRACKEDGE * startpt, //outline to convert
ICOORD bot_left, //bounding box
ICOORD top_right, inT16 length //length of loop
):box (bot_left, top_right), start (startpt->pos) {
inT16 stepindex; //index to step
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 (stdout, TRUE);
}
}
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 (stdout, TRUE);
}
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 (stdout, TRUE);
}
}
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 (stdout, TRUE);
tprintf ("SPACE stats\n");
cluster_stats[2].print (stdout, FALSE);
tprintf ("NONSPACE stats\n");
cluster_stats[1].print (stdout, FALSE);
}
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 ();
}
void BLOBNBOX::chop( //chop blobs
BLOBNBOX_IT *start_it, //location of this
BLOBNBOX_IT *end_it, //iterator
FCOORD rotation, //for landscape
float xheight //of line
) {
inT16 blobcount; //no of blobs
BLOBNBOX *newblob; //fake blob
BLOBNBOX *blob; //current blob
inT16 blobindex; //number of chop
inT16 leftx; //left edge of blob
float blobwidth; //width of each
float rightx; //right edge to scan
float ymin, ymax; //limits of new blob
float test_ymin, test_ymax; //limits of part blob
ICOORD bl, tr; //corners of box
BLOBNBOX_IT blob_it; //blob iterator
//get no of chops
blobcount = (inT16) floor (box.width () / xheight);
if (blobcount > 1 && (blob_ptr != NULL || cblob_ptr != NULL)) {
//width of each
blobwidth = (float) (box.width () + 1) / blobcount;
for (blobindex = blobcount - 1, rightx = box.right ();
blobindex >= 0; blobindex--, rightx -= blobwidth) {
ymin = (float) MAX_INT32;
ymax = (float) -MAX_INT32;
blob_it = *start_it;
do {
blob = blob_it.data ();
if (blob->blob_ptr != NULL)
find_blob_limits (blob->blob_ptr, rightx - blobwidth, rightx,
rotation, test_ymin, test_ymax);
else
find_cblob_vlimits (blob->cblob_ptr, rightx - blobwidth,
rightx,
/*rotation, */ test_ymin, test_ymax);
blob_it.forward ();
if (test_ymin < ymin)
ymin = test_ymin;
if (test_ymax > ymax)
ymax = test_ymax;
}
while (blob != end_it->data ());
if (ymin < ymax) {
leftx = (inT16) floor (rightx - blobwidth);
if (leftx < box.left ())
leftx = box.left (); //clip to real box
bl = ICOORD (leftx, (inT16) floor (ymin));
tr = ICOORD ((inT16) ceil (rightx), (inT16) ceil (ymax));
if (blobindex == 0)
box = TBOX (bl, tr); //change box
else {
newblob = new BLOBNBOX;
//box is all it has
newblob->box = TBOX (bl, tr);
//stay on current
end_it->add_after_stay_put (newblob);
}
}
}
}
}
