mirror of
https://github.com/tesseract-ocr/tesseract.git
synced 2024-11-24 02:59:07 +08:00
edf765b952
This fixes compiler warnings like this one: api/baseapi.h:739:32: warning: type qualifiers ignored on function return type [-Wignored-qualifiers] Signed-off-by: Stefan Weil <sw@weilnetz.de>
577 lines
20 KiB
C++
577 lines
20 KiB
C++
///////////////////////////////////////////////////////////////////////
|
|
// File: osdetect.cpp
|
|
// Description: Orientation and script detection.
|
|
// Author: Samuel Charron
|
|
// Ranjith Unnikrishnan
|
|
//
|
|
// (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.
|
|
//
|
|
///////////////////////////////////////////////////////////////////////
|
|
|
|
#include "osdetect.h"
|
|
|
|
#include "blobbox.h"
|
|
#include "blread.h"
|
|
#include "colfind.h"
|
|
#include "fontinfo.h"
|
|
#include "imagefind.h"
|
|
#include "linefind.h"
|
|
#include "oldlist.h"
|
|
#include "qrsequence.h"
|
|
#include "ratngs.h"
|
|
#include "strngs.h"
|
|
#include "tabvector.h"
|
|
#include "tesseractclass.h"
|
|
#include "textord.h"
|
|
|
|
const int kMinCharactersToTry = 50;
|
|
const int kMaxCharactersToTry = 5 * kMinCharactersToTry;
|
|
|
|
const float kSizeRatioToReject = 2.0;
|
|
const int kMinAcceptableBlobHeight = 10;
|
|
|
|
const float kOrientationAcceptRatio = 1.3;
|
|
const float kScriptAcceptRatio = 1.3;
|
|
|
|
const float kHanRatioInKorean = 0.7;
|
|
const float kHanRatioInJapanese = 0.3;
|
|
|
|
const float kNonAmbiguousMargin = 1.0;
|
|
|
|
// General scripts
|
|
static const char* han_script = "Han";
|
|
static const char* latin_script = "Latin";
|
|
static const char* katakana_script = "Katakana";
|
|
static const char* hiragana_script = "Hiragana";
|
|
static const char* hangul_script = "Hangul";
|
|
|
|
// Pseudo-scripts Name
|
|
const char* ScriptDetector::korean_script_ = "Korean";
|
|
const char* ScriptDetector::japanese_script_ = "Japanese";
|
|
const char* ScriptDetector::fraktur_script_ = "Fraktur";
|
|
|
|
// Minimum believable resolution.
|
|
const int kMinCredibleResolution = 70;
|
|
// Default resolution used if input is not believable.
|
|
const int kDefaultResolution = 300;
|
|
|
|
void OSResults::update_best_orientation() {
|
|
float first = orientations[0];
|
|
float second = orientations[1];
|
|
best_result.orientation_id = 0;
|
|
if (orientations[0] < orientations[1]) {
|
|
first = orientations[1];
|
|
second = orientations[0];
|
|
best_result.orientation_id = 1;
|
|
}
|
|
for (int i = 2; i < 4; ++i) {
|
|
if (orientations[i] > first) {
|
|
second = first;
|
|
first = orientations[i];
|
|
best_result.orientation_id = i;
|
|
} else if (orientations[i] > second) {
|
|
second = orientations[i];
|
|
}
|
|
}
|
|
// Store difference of top two orientation scores.
|
|
best_result.oconfidence = first - second;
|
|
}
|
|
|
|
void OSResults::set_best_orientation(int orientation_id) {
|
|
best_result.orientation_id = orientation_id;
|
|
best_result.oconfidence = 0;
|
|
}
|
|
|
|
void OSResults::update_best_script(int orientation) {
|
|
// We skip index 0 to ignore the "Common" script.
|
|
float first = scripts_na[orientation][1];
|
|
float second = scripts_na[orientation][2];
|
|
best_result.script_id = 1;
|
|
if (scripts_na[orientation][1] < scripts_na[orientation][2]) {
|
|
first = scripts_na[orientation][2];
|
|
second = scripts_na[orientation][1];
|
|
best_result.script_id = 2;
|
|
}
|
|
for (int i = 3; i < kMaxNumberOfScripts; ++i) {
|
|
if (scripts_na[orientation][i] > first) {
|
|
best_result.script_id = i;
|
|
second = first;
|
|
first = scripts_na[orientation][i];
|
|
} else if (scripts_na[orientation][i] > second) {
|
|
second = scripts_na[orientation][i];
|
|
}
|
|
}
|
|
best_result.sconfidence =
|
|
(first / second - 1.0) / (kScriptAcceptRatio - 1.0);
|
|
}
|
|
|
|
int OSResults::get_best_script(int orientation_id) const {
|
|
int max_id = -1;
|
|
for (int j = 0; j < kMaxNumberOfScripts; ++j) {
|
|
const char *script = unicharset->get_script_from_script_id(j);
|
|
if (strcmp(script, "Common") && strcmp(script, "NULL")) {
|
|
if (max_id == -1 ||
|
|
scripts_na[orientation_id][j] > scripts_na[orientation_id][max_id])
|
|
max_id = j;
|
|
}
|
|
}
|
|
return max_id;
|
|
}
|
|
|
|
// Print the script scores for all possible orientations.
|
|
void OSResults::print_scores(void) const {
|
|
for (int i = 0; i < 4; ++i) {
|
|
tprintf("Orientation id #%d", i);
|
|
print_scores(i);
|
|
}
|
|
}
|
|
|
|
// Print the script scores for the given candidate orientation.
|
|
void OSResults::print_scores(int orientation_id) const {
|
|
for (int j = 0; j < kMaxNumberOfScripts; ++j) {
|
|
if (scripts_na[orientation_id][j]) {
|
|
tprintf("%12s\t: %f\n", unicharset->get_script_from_script_id(j),
|
|
scripts_na[orientation_id][j]);
|
|
}
|
|
}
|
|
}
|
|
|
|
// Accumulate scores with given OSResults instance and update the best script.
|
|
void OSResults::accumulate(const OSResults& osr) {
|
|
for (int i = 0; i < 4; ++i) {
|
|
orientations[i] += osr.orientations[i];
|
|
for (int j = 0; j < kMaxNumberOfScripts; ++j)
|
|
scripts_na[i][j] += osr.scripts_na[i][j];
|
|
}
|
|
unicharset = osr.unicharset;
|
|
update_best_orientation();
|
|
update_best_script(best_result.orientation_id);
|
|
}
|
|
|
|
// Detect and erase horizontal/vertical lines and picture regions from the
|
|
// image, so that non-text blobs are removed from consideration.
|
|
void remove_nontext_regions(tesseract::Tesseract *tess, BLOCK_LIST *blocks,
|
|
TO_BLOCK_LIST *to_blocks) {
|
|
Pix *pix = tess->pix_binary();
|
|
ASSERT_HOST(pix != NULL);
|
|
int vertical_x = 0;
|
|
int vertical_y = 1;
|
|
tesseract::TabVector_LIST v_lines;
|
|
tesseract::TabVector_LIST h_lines;
|
|
const int kMinCredibleResolution = 70;
|
|
int resolution = (kMinCredibleResolution > pixGetXRes(pix)) ?
|
|
kMinCredibleResolution : pixGetXRes(pix);
|
|
|
|
tesseract::LineFinder::FindAndRemoveLines(resolution, false, pix,
|
|
&vertical_x, &vertical_y,
|
|
NULL, &v_lines, &h_lines);
|
|
Pix* im_pix = tesseract::ImageFind::FindImages(pix);
|
|
if (im_pix != NULL) {
|
|
pixSubtract(pix, pix, im_pix);
|
|
pixDestroy(&im_pix);
|
|
}
|
|
tess->mutable_textord()->find_components(tess->pix_binary(),
|
|
blocks, to_blocks);
|
|
}
|
|
|
|
// Find connected components in the page and process a subset until finished or
|
|
// a stopping criterion is met.
|
|
// Returns the number of blobs used in making the estimate. 0 implies failure.
|
|
int orientation_and_script_detection(STRING& filename,
|
|
OSResults* osr,
|
|
tesseract::Tesseract* tess) {
|
|
STRING name = filename; //truncated name
|
|
const char *lastdot; //of name
|
|
TBOX page_box;
|
|
|
|
lastdot = strrchr (name.string (), '.');
|
|
if (lastdot != NULL)
|
|
name[lastdot-name.string()] = '\0';
|
|
|
|
ASSERT_HOST(tess->pix_binary() != NULL)
|
|
int width = pixGetWidth(tess->pix_binary());
|
|
int height = pixGetHeight(tess->pix_binary());
|
|
|
|
BLOCK_LIST blocks;
|
|
if (!read_unlv_file(name, width, height, &blocks))
|
|
FullPageBlock(width, height, &blocks);
|
|
|
|
// Try to remove non-text regions from consideration.
|
|
TO_BLOCK_LIST land_blocks, port_blocks;
|
|
remove_nontext_regions(tess, &blocks, &port_blocks);
|
|
|
|
if (port_blocks.empty()) {
|
|
// page segmentation did not succeed, so we need to find_components first.
|
|
tess->mutable_textord()->find_components(tess->pix_binary(),
|
|
&blocks, &port_blocks);
|
|
} else {
|
|
page_box.set_left(0);
|
|
page_box.set_bottom(0);
|
|
page_box.set_right(width);
|
|
page_box.set_top(height);
|
|
// Filter_blobs sets up the TO_BLOCKs the same as find_components does.
|
|
tess->mutable_textord()->filter_blobs(page_box.topright(),
|
|
&port_blocks, true);
|
|
}
|
|
|
|
return os_detect(&port_blocks, osr, tess);
|
|
}
|
|
|
|
// Filter and sample the blobs.
|
|
// Returns a non-zero number of blobs if the page was successfully processed, or
|
|
// zero if the page had too few characters to be reliable
|
|
int os_detect(TO_BLOCK_LIST* port_blocks, OSResults* osr,
|
|
tesseract::Tesseract* tess) {
|
|
int blobs_total = 0;
|
|
TO_BLOCK_IT block_it;
|
|
block_it.set_to_list(port_blocks);
|
|
|
|
BLOBNBOX_CLIST filtered_list;
|
|
BLOBNBOX_C_IT filtered_it(&filtered_list);
|
|
|
|
for (block_it.mark_cycle_pt(); !block_it.cycled_list();
|
|
block_it.forward ()) {
|
|
TO_BLOCK* to_block = block_it.data();
|
|
if (to_block->block->poly_block() &&
|
|
!to_block->block->poly_block()->IsText()) continue;
|
|
BLOBNBOX_IT bbox_it;
|
|
bbox_it.set_to_list(&to_block->blobs);
|
|
for (bbox_it.mark_cycle_pt (); !bbox_it.cycled_list ();
|
|
bbox_it.forward ()) {
|
|
BLOBNBOX* bbox = bbox_it.data();
|
|
C_BLOB* blob = bbox->cblob();
|
|
TBOX box = blob->bounding_box();
|
|
++blobs_total;
|
|
|
|
float y_x = fabs((box.height() * 1.0) / box.width());
|
|
float x_y = 1.0f / y_x;
|
|
// Select a >= 1.0 ratio
|
|
float ratio = x_y > y_x ? x_y : y_x;
|
|
// Blob is ambiguous
|
|
if (ratio > kSizeRatioToReject) continue;
|
|
if (box.height() < kMinAcceptableBlobHeight) continue;
|
|
filtered_it.add_to_end(bbox);
|
|
}
|
|
}
|
|
return os_detect_blobs(NULL, &filtered_list, osr, tess);
|
|
}
|
|
|
|
// Detect orientation and script from a list of blobs.
|
|
// Returns a non-zero number of blobs if the list was successfully processed, or
|
|
// zero if the list had too few characters to be reliable.
|
|
// If allowed_scripts is non-null and non-empty, it is a list of scripts that
|
|
// constrains both orientation and script detection to consider only scripts
|
|
// from the list.
|
|
int os_detect_blobs(const GenericVector<int>* allowed_scripts,
|
|
BLOBNBOX_CLIST* blob_list, OSResults* osr,
|
|
tesseract::Tesseract* tess) {
|
|
OSResults osr_;
|
|
if (osr == NULL)
|
|
osr = &osr_;
|
|
|
|
osr->unicharset = &tess->unicharset;
|
|
OrientationDetector o(allowed_scripts, osr);
|
|
ScriptDetector s(allowed_scripts, osr, tess);
|
|
|
|
BLOBNBOX_C_IT filtered_it(blob_list);
|
|
int real_max = MIN(filtered_it.length(), kMaxCharactersToTry);
|
|
// tprintf("Total blobs found = %d\n", blobs_total);
|
|
// tprintf("Number of blobs post-filtering = %d\n", filtered_it.length());
|
|
// tprintf("Number of blobs to try = %d\n", real_max);
|
|
|
|
// If there are too few characters, skip this page entirely.
|
|
if (real_max < kMinCharactersToTry / 2) {
|
|
tprintf("Too few characters. Skipping this page\n");
|
|
return 0;
|
|
}
|
|
|
|
BLOBNBOX** blobs = new BLOBNBOX*[filtered_it.length()];
|
|
int number_of_blobs = 0;
|
|
for (filtered_it.mark_cycle_pt (); !filtered_it.cycled_list ();
|
|
filtered_it.forward ()) {
|
|
blobs[number_of_blobs++] = (BLOBNBOX*)filtered_it.data();
|
|
}
|
|
QRSequenceGenerator sequence(number_of_blobs);
|
|
int num_blobs_evaluated = 0;
|
|
for (int i = 0; i < real_max; ++i) {
|
|
if (os_detect_blob(blobs[sequence.GetVal()], &o, &s, osr, tess)
|
|
&& i > kMinCharactersToTry) {
|
|
break;
|
|
}
|
|
++num_blobs_evaluated;
|
|
}
|
|
delete [] blobs;
|
|
|
|
// Make sure the best_result is up-to-date
|
|
int orientation = o.get_orientation();
|
|
osr->update_best_script(orientation);
|
|
return num_blobs_evaluated;
|
|
}
|
|
|
|
// Processes a single blob to estimate script and orientation.
|
|
// Return true if estimate of orientation and script satisfies stopping
|
|
// criteria.
|
|
bool os_detect_blob(BLOBNBOX* bbox, OrientationDetector* o,
|
|
ScriptDetector* s, OSResults* osr,
|
|
tesseract::Tesseract* tess) {
|
|
tess->tess_cn_matching.set_value(true); // turn it on
|
|
tess->tess_bn_matching.set_value(false);
|
|
C_BLOB* blob = bbox->cblob();
|
|
TBLOB* tblob = TBLOB::PolygonalCopy(tess->poly_allow_detailed_fx, blob);
|
|
TBOX box = tblob->bounding_box();
|
|
FCOORD current_rotation(1.0f, 0.0f);
|
|
FCOORD rotation90(0.0f, 1.0f);
|
|
BLOB_CHOICE_LIST ratings[4];
|
|
// Test the 4 orientations
|
|
for (int i = 0; i < 4; ++i) {
|
|
// Normalize the blob. Set the origin to the place we want to be the
|
|
// bottom-middle after rotation.
|
|
// Scaling is to make the rotated height the x-height.
|
|
float scaling = static_cast<float>(kBlnXHeight) / box.height();
|
|
float x_origin = (box.left() + box.right()) / 2.0f;
|
|
float y_origin = (box.bottom() + box.top()) / 2.0f;
|
|
if (i == 0 || i == 2) {
|
|
// Rotation is 0 or 180.
|
|
y_origin = i == 0 ? box.bottom() : box.top();
|
|
} else {
|
|
// Rotation is 90 or 270.
|
|
scaling = static_cast<float>(kBlnXHeight) / box.width();
|
|
x_origin = i == 1 ? box.left() : box.right();
|
|
}
|
|
TBLOB* rotated_blob = new TBLOB(*tblob);
|
|
rotated_blob->Normalize(NULL, ¤t_rotation, NULL,
|
|
x_origin, y_origin, scaling, scaling,
|
|
0.0f, static_cast<float>(kBlnBaselineOffset),
|
|
false, NULL);
|
|
tess->AdaptiveClassifier(rotated_blob, ratings + i);
|
|
delete rotated_blob;
|
|
current_rotation.rotate(rotation90);
|
|
}
|
|
delete tblob;
|
|
|
|
bool stop = o->detect_blob(ratings);
|
|
s->detect_blob(ratings);
|
|
int orientation = o->get_orientation();
|
|
stop = s->must_stop(orientation) && stop;
|
|
return stop;
|
|
}
|
|
|
|
|
|
OrientationDetector::OrientationDetector(
|
|
const GenericVector<int>* allowed_scripts, OSResults* osr) {
|
|
osr_ = osr;
|
|
allowed_scripts_ = allowed_scripts;
|
|
}
|
|
|
|
// Score the given blob and return true if it is now sure of the orientation
|
|
// after adding this block.
|
|
bool OrientationDetector::detect_blob(BLOB_CHOICE_LIST* scores) {
|
|
float blob_o_score[4] = {0.0f, 0.0f, 0.0f, 0.0f};
|
|
float total_blob_o_score = 0.0f;
|
|
|
|
for (int i = 0; i < 4; ++i) {
|
|
BLOB_CHOICE_IT choice_it(scores + i);
|
|
if (!choice_it.empty()) {
|
|
BLOB_CHOICE* choice = NULL;
|
|
if (allowed_scripts_ != NULL && !allowed_scripts_->empty()) {
|
|
// Find the top choice in an allowed script.
|
|
for (choice_it.mark_cycle_pt(); !choice_it.cycled_list() &&
|
|
choice == NULL; choice_it.forward()) {
|
|
int choice_script = choice_it.data()->script_id();
|
|
int s = 0;
|
|
for (s = 0; s < allowed_scripts_->size(); ++s) {
|
|
if ((*allowed_scripts_)[s] == choice_script) {
|
|
choice = choice_it.data();
|
|
break;
|
|
}
|
|
}
|
|
}
|
|
} else {
|
|
choice = choice_it.data();
|
|
}
|
|
if (choice != NULL) {
|
|
// The certainty score ranges between [-20,0]. This is converted here to
|
|
// [0,1], with 1 indicating best match.
|
|
blob_o_score[i] = 1 + 0.05 * choice->certainty();
|
|
total_blob_o_score += blob_o_score[i];
|
|
}
|
|
}
|
|
}
|
|
if (total_blob_o_score == 0.0) return false;
|
|
// Fill in any blanks with the worst score of the others. This is better than
|
|
// picking an arbitrary probability for it and way better than -inf.
|
|
float worst_score = 0.0f;
|
|
int num_good_scores = 0;
|
|
for (int i = 0; i < 4; ++i) {
|
|
if (blob_o_score[i] > 0.0f) {
|
|
++num_good_scores;
|
|
if (worst_score == 0.0f || blob_o_score[i] < worst_score)
|
|
worst_score = blob_o_score[i];
|
|
}
|
|
}
|
|
if (num_good_scores == 1) {
|
|
// Lower worst if there is only one.
|
|
worst_score /= 2.0f;
|
|
}
|
|
for (int i = 0; i < 4; ++i) {
|
|
if (blob_o_score[i] == 0.0f) {
|
|
blob_o_score[i] = worst_score;
|
|
total_blob_o_score += worst_score;
|
|
}
|
|
}
|
|
// Normalize the orientation scores for the blob and use them to
|
|
// update the aggregated orientation score.
|
|
for (int i = 0; total_blob_o_score != 0 && i < 4; ++i) {
|
|
osr_->orientations[i] += log(blob_o_score[i] / total_blob_o_score);
|
|
}
|
|
|
|
// TODO(ranjith) Add an early exit test, based on min_orientation_margin,
|
|
// as used in pagesegmain.cpp.
|
|
return false;
|
|
}
|
|
|
|
int OrientationDetector::get_orientation() {
|
|
osr_->update_best_orientation();
|
|
return osr_->best_result.orientation_id;
|
|
}
|
|
|
|
|
|
ScriptDetector::ScriptDetector(const GenericVector<int>* allowed_scripts,
|
|
OSResults* osr, tesseract::Tesseract* tess) {
|
|
osr_ = osr;
|
|
tess_ = tess;
|
|
allowed_scripts_ = allowed_scripts;
|
|
katakana_id_ = tess_->unicharset.add_script(katakana_script);
|
|
hiragana_id_ = tess_->unicharset.add_script(hiragana_script);
|
|
han_id_ = tess_->unicharset.add_script(han_script);
|
|
hangul_id_ = tess_->unicharset.add_script(hangul_script);
|
|
japanese_id_ = tess_->unicharset.add_script(japanese_script_);
|
|
korean_id_ = tess_->unicharset.add_script(korean_script_);
|
|
latin_id_ = tess_->unicharset.add_script(latin_script);
|
|
fraktur_id_ = tess_->unicharset.add_script(fraktur_script_);
|
|
}
|
|
|
|
|
|
// Score the given blob and return true if it is now sure of the script after
|
|
// adding this blob.
|
|
void ScriptDetector::detect_blob(BLOB_CHOICE_LIST* scores) {
|
|
bool done[kMaxNumberOfScripts];
|
|
for (int i = 0; i < 4; ++i) {
|
|
for (int j = 0; j < kMaxNumberOfScripts; ++j)
|
|
done[j] = false;
|
|
|
|
BLOB_CHOICE_IT choice_it;
|
|
choice_it.set_to_list(scores + i);
|
|
|
|
float prev_score = -1;
|
|
int script_count = 0;
|
|
int prev_id = -1;
|
|
int prev_fontinfo_id = -1;
|
|
const char* prev_unichar = "";
|
|
const char* unichar = "";
|
|
|
|
for (choice_it.mark_cycle_pt(); !choice_it.cycled_list();
|
|
choice_it.forward()) {
|
|
BLOB_CHOICE* choice = choice_it.data();
|
|
int id = choice->script_id();
|
|
if (allowed_scripts_ != NULL && !allowed_scripts_->empty()) {
|
|
// Check that the choice is in an allowed script.
|
|
int s = 0;
|
|
for (s = 0; s < allowed_scripts_->size(); ++s) {
|
|
if ((*allowed_scripts_)[s] == id) break;
|
|
}
|
|
if (s == allowed_scripts_->size()) continue; // Not found in list.
|
|
}
|
|
// Script already processed before.
|
|
if (done[id]) continue;
|
|
done[id] = true;
|
|
|
|
unichar = tess_->unicharset.id_to_unichar(choice->unichar_id());
|
|
// Save data from the first match
|
|
if (prev_score < 0) {
|
|
prev_score = -choice->certainty();
|
|
script_count = 1;
|
|
prev_id = id;
|
|
prev_unichar = unichar;
|
|
prev_fontinfo_id = choice->fontinfo_id();
|
|
} else if (-choice->certainty() < prev_score + kNonAmbiguousMargin) {
|
|
++script_count;
|
|
}
|
|
|
|
if (strlen(prev_unichar) == 1)
|
|
if (unichar[0] >= '0' && unichar[0] <= '9')
|
|
break;
|
|
|
|
// if script_count is >= 2, character is ambiguous, skip other matches
|
|
// since they are useless.
|
|
if (script_count >= 2)
|
|
break;
|
|
}
|
|
// Character is non ambiguous
|
|
if (script_count == 1) {
|
|
// Update the score of the winning script
|
|
osr_->scripts_na[i][prev_id] += 1.0;
|
|
|
|
// Workaround for Fraktur
|
|
if (prev_id == latin_id_) {
|
|
if (prev_fontinfo_id >= 0) {
|
|
const tesseract::FontInfo &fi =
|
|
tess_->get_fontinfo_table().get(prev_fontinfo_id);
|
|
//printf("Font: %s i:%i b:%i f:%i s:%i k:%i (%s)\n", fi.name,
|
|
// fi.is_italic(), fi.is_bold(), fi.is_fixed_pitch(),
|
|
// fi.is_serif(), fi.is_fraktur(),
|
|
// prev_unichar);
|
|
if (fi.is_fraktur()) {
|
|
osr_->scripts_na[i][prev_id] -= 1.0;
|
|
osr_->scripts_na[i][fraktur_id_] += 1.0;
|
|
}
|
|
}
|
|
}
|
|
|
|
// Update Japanese / Korean pseudo-scripts
|
|
if (prev_id == katakana_id_)
|
|
osr_->scripts_na[i][japanese_id_] += 1.0;
|
|
if (prev_id == hiragana_id_)
|
|
osr_->scripts_na[i][japanese_id_] += 1.0;
|
|
if (prev_id == hangul_id_)
|
|
osr_->scripts_na[i][korean_id_] += 1.0;
|
|
if (prev_id == han_id_) {
|
|
osr_->scripts_na[i][korean_id_] += kHanRatioInKorean;
|
|
osr_->scripts_na[i][japanese_id_] += kHanRatioInJapanese;
|
|
}
|
|
}
|
|
} // iterate over each orientation
|
|
}
|
|
|
|
bool ScriptDetector::must_stop(int orientation) {
|
|
osr_->update_best_script(orientation);
|
|
return osr_->best_result.sconfidence > 1;
|
|
}
|
|
|
|
// Helper method to convert an orientation index to its value in degrees.
|
|
// The value represents the amount of clockwise rotation in degrees that must be
|
|
// applied for the text to be upright (readable).
|
|
int OrientationIdToValue(const int& id) {
|
|
switch (id) {
|
|
case 0:
|
|
return 0;
|
|
case 1:
|
|
return 270;
|
|
case 2:
|
|
return 180;
|
|
case 3:
|
|
return 90;
|
|
default:
|
|
return -1;
|
|
}
|
|
}
|