/**
* @name uniformly_spaced()
* Return true if one of the following are true:
* - All inter-char gaps are the same width
* - The largest gap is no larger than twice the mean/median of the others
* - The largest gap is < normalised_max_nonspace
* **** REMEMBER - WE'RE NOW WORKING WITH A BLN WERD !!!
*/
BOOL8 Tesseract::uniformly_spaced(WERD_RES *word) {
TBOX box;
inT16 prev_right = -MAX_INT16;
inT16 gap;
inT16 max_gap = -MAX_INT16;
inT16 max_gap_count = 0;
STATS gap_stats(0, MAXSPACING);
BOOL8 result;
const ROW *row = word->denorm.row();
float max_non_space;
float normalised_max_nonspace;
inT16 i = 0;
inT16 offset = 0;
STRING punct_chars = "\"`',.:;";
for (TBLOB* blob = word->rebuild_word->blobs; blob != NULL;
blob = blob->next) {
box = blob->bounding_box();
if ((prev_right > -MAX_INT16) &&
(!punct_chars.contains(
word->best_choice->unichar_string()
[offset - word->best_choice->unichar_lengths()[i - 1]]) &&
!punct_chars.contains(
word->best_choice->unichar_string()[offset]))) {
gap = box.left() - prev_right;
if (gap < max_gap) {
gap_stats.add(gap, 1);
} else if (gap == max_gap) {
max_gap_count++;
} else {
if (max_gap_count > 0)
gap_stats.add(max_gap, max_gap_count);
max_gap = gap;
max_gap_count = 1;
}
}
prev_right = box.right();
offset += word->best_choice->unichar_lengths()[i++];
}
max_non_space = (row->space() + 3 * row->kern()) / 4;
normalised_max_nonspace = max_non_space * kBlnXHeight / row->x_height();
result = (
gap_stats.get_total() == 0 ||
max_gap <= normalised_max_nonspace ||
(gap_stats.get_total() > 2 && max_gap <= 2 * gap_stats.median()) ||
(gap_stats.get_total() <= 2 && max_gap <= 2 * gap_stats.mean()));
#ifndef SECURE_NAMES
if ((debug_fix_space_level > 1)) {
if (result) {
tprintf(
"ACCEPT SPACING FOR: \"%s\" norm_maxnon = %f max=%d maxcount=%d "
"total=%d mean=%f median=%f\n",
word->best_choice->unichar_string().string(), normalised_max_nonspace,
max_gap, max_gap_count, gap_stats.get_total(), gap_stats.mean(),
gap_stats.median());
} else {
tprintf(
"REJECT SPACING FOR: \"%s\" norm_maxnon = %f max=%d maxcount=%d "
"total=%d mean=%f median=%f\n",
word->best_choice->unichar_string().string(), normalised_max_nonspace,
max_gap, max_gap_count, gap_stats.get_total(), gap_stats.mean(),
gap_stats.median());
}
}
#endif
return result;
}
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;
}
/*************************************************************************
* uniformly_spaced()
* Return true if one of the following are true:
* - All inter-char gaps are the same width
* - The largest gap is no larger than twice the mean/median of the others
* - The largest gap is < 64/5 = 13 and all others are <= 0
* **** REMEMBER - WE'RE NOW WORKING WITH A BLN WERD !!!
*************************************************************************/
BOOL8 uniformly_spaced( //sensible word
WERD_RES *word) {
PBLOB_IT blob_it;
TBOX box;
inT16 prev_right = -MAX_INT16;
inT16 gap;
inT16 max_gap = -MAX_INT16;
inT16 max_gap_count = 0;
STATS gap_stats (0, MAXSPACING);
BOOL8 result;
const ROW *row = word->denorm.row ();
float max_non_space;
float normalised_max_nonspace;
inT16 i = 0;
inT16 offset = 0;
STRING punct_chars = "\"`',.:;";
blob_it.set_to_list (word->outword->blob_list ());
for (blob_it.mark_cycle_pt (); !blob_it.cycled_list (); blob_it.forward ()) {
box = blob_it.data ()->bounding_box ();
if ((prev_right > -MAX_INT16) &&
(!fixsp_ignore_punct ||
(!punct_chars.contains (word->best_choice->string ()
[offset - word->best_choice->lengths()[i - 1]]) &&
!punct_chars.contains (word->best_choice->string ()[offset])))) {
gap = box.left () - prev_right;
if (gap < max_gap)
gap_stats.add (gap, 1);
else if (gap == max_gap)
max_gap_count++;
else {
if (max_gap_count > 0)
gap_stats.add (max_gap, max_gap_count);
max_gap = gap;
max_gap_count = 1;
}
}
prev_right = box.right ();
offset += word->best_choice->lengths()[i++];
}
max_non_space = (row->space () + 3 * row->kern ()) / 4;
normalised_max_nonspace = max_non_space * bln_x_height / row->x_height ();
result = ((gap_stats.get_total () == 0) ||
(max_gap <= normalised_max_nonspace) ||
((gap_stats.get_total () > 2) &&
(max_gap <= 2 * gap_stats.median ())) ||
((gap_stats.get_total () <= 2) &&
(max_gap <= 2 * gap_stats.mean ())));
#ifndef SECURE_NAMES
if ((debug_fix_space_level > 1)) {
if (result)
tprintf
("ACCEPT SPACING FOR: \"%s\" norm_maxnon = %f max=%d maxcount=%d total=%d mean=%f median=%f\n",
word->best_choice->string ().string (), normalised_max_nonspace,
max_gap, max_gap_count, gap_stats.get_total (), gap_stats.mean (),
gap_stats.median ());
else
tprintf
("REJECT SPACING FOR: \"%s\" norm_maxnon = %f max=%d maxcount=%d total=%d mean=%f median=%f\n",
word->best_choice->string ().string (), normalised_max_nonspace,
max_gap, max_gap_count, gap_stats.get_total (), gap_stats.mean (),
gap_stats.median ());
}
#endif
return result;
}
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 ();
}
