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https://github.com/tesseract-ocr/tesseract.git
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4523ce9f7d
git-svn-id: https://tesseract-ocr.googlecode.com/svn/trunk@526 d0cd1f9f-072b-0410-8dd7-cf729c803f20
302 lines
11 KiB
C++
302 lines
11 KiB
C++
/**********************************************************************
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* File: word_size_model.cpp
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* Description: Implementation of the Word Size Model Class
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* Author: Ahmad Abdulkader
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* Created: 2008
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*
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* (C) Copyright 2008, Google Inc.
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** Licensed under the Apache License, Version 2.0 (the "License");
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** you may not use this file except in compliance with the License.
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** You may obtain a copy of the License at
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** http://www.apache.org/licenses/LICENSE-2.0
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** Unless required by applicable law or agreed to in writing, software
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** distributed under the License is distributed on an "AS IS" BASIS,
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** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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** See the License for the specific language governing permissions and
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** limitations under the License.
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*
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**********************************************************************/
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#include <math.h>
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#include <string>
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#include <vector>
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#include "word_size_model.h"
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#include "cube_utils.h"
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namespace tesseract {
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WordSizeModel::WordSizeModel(CharSet * char_set, bool contextual) {
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char_set_ = char_set;
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contextual_ = contextual;
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}
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WordSizeModel::~WordSizeModel() {
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for (int fnt = 0; fnt < font_pair_size_models_.size(); fnt++) {
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FontPairSizeInfo fnt_info = font_pair_size_models_[fnt];
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delete []fnt_info.pair_size_info[0];
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delete []fnt_info.pair_size_info;
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}
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}
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WordSizeModel *WordSizeModel::Create(const string &data_file_path,
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const string &lang,
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CharSet *char_set,
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bool contextual) {
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WordSizeModel *obj = new WordSizeModel(char_set, contextual);
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if (!obj) {
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fprintf(stderr, "Cube ERROR (WordSizeModel::Create): unable to allocate "
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"new word size model object\n");
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return NULL;
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}
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if (!obj->Init(data_file_path, lang)) {
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delete obj;
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return NULL;
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}
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return obj;
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}
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bool WordSizeModel::Init(const string &data_file_path, const string &lang) {
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string stats_file_name;
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stats_file_name = data_file_path + lang;
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stats_file_name += ".cube.size";
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// read file to memory
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string str_data;
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if (!CubeUtils::ReadFileToString(stats_file_name, &str_data)) {
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return false;
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}
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// split to words
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vector<string> tokens;
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CubeUtils::SplitStringUsing(str_data, "\t\r\n", &tokens);
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if (tokens.size() < 1) {
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fprintf(stderr, "Cube ERROR (WordSizeModel::Init): invalid "
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"file contents: %s\n", stats_file_name.c_str());
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return false;
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}
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font_pair_size_models_.clear();
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// token count per line depends on whether the language is contextual or not
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int token_cnt = contextual_ ?
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(kExpectedTokenCount + 4) : kExpectedTokenCount;
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// the count of size classes depends on whether the language is contextual
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// or not. For non contextual languages (Ex: Eng), it is equal to the class
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// count. For contextual languages (Ex: Ara), it is equal to the class count
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// multiplied by the position count (4: start, middle, final, isolated)
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int size_class_cnt = contextual_ ?
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(char_set_->ClassCount() * 4) : char_set_->ClassCount();
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string fnt_name = "";
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for (int tok = 0; tok < tokens.size(); tok += token_cnt) {
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// a new font, write the old font data and re-init
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if (tok == 0 || fnt_name != tokens[tok]) {
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FontPairSizeInfo fnt_info;
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fnt_info.pair_size_info = new PairSizeInfo *[size_class_cnt];
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if (!fnt_info.pair_size_info) {
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fprintf(stderr, "Cube ERROR (WordSizeModel::Init): error allcoating "
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"memory for font pair size info\n");
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return false;
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}
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fnt_info.pair_size_info[0] =
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new PairSizeInfo[size_class_cnt * size_class_cnt];
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if (!fnt_info.pair_size_info[0]) {
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fprintf(stderr, "Cube ERROR (WordSizeModel::Init): error allocating "
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"memory for font pair size info\n");
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return false;
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}
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memset(fnt_info.pair_size_info[0], 0, size_class_cnt * size_class_cnt *
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sizeof(PairSizeInfo));
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for (int cls = 1; cls < size_class_cnt; cls++) {
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fnt_info.pair_size_info[cls] =
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fnt_info.pair_size_info[cls - 1] + size_class_cnt;
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}
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// strip out path and extension
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string stripped_font_name = tokens[tok].substr(0, tokens[tok].find('.'));
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string::size_type strt_pos = stripped_font_name.find_last_of("/\\");
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if (strt_pos != string::npos) {
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fnt_info.font_name = stripped_font_name.substr(strt_pos);
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} else {
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fnt_info.font_name = stripped_font_name;
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}
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font_pair_size_models_.push_back(fnt_info);
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}
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// parse the data
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int cls_0;
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int cls_1;
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double delta_top;
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double wid_0;
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double hgt_0;
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double wid_1;
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double hgt_1;
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int size_code_0;
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int size_code_1;
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// read and parse the tokens
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if (contextual_) {
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int start_0;
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int end_0;
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int start_1;
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int end_1;
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// The expected format for a character size bigram is as follows:
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// ClassId0<delim>Start-flag0<delim>End-flag0<delim>String0(ignored)
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// Width0<delim>Height0<delim>
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// ClassId1<delim>Start-flag1<delim>End-flag1<delim>String1(ignored)
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// HeightDelta<delim>Width1<delim>Height0<delim>
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// In case of non-contextual languages, the Start and End flags are
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// omitted
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if (sscanf(tokens[tok + 1].c_str(), "%d", &cls_0) != 1 ||
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sscanf(tokens[tok + 2].c_str(), "%d", &start_0) != 1 ||
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sscanf(tokens[tok + 3].c_str(), "%d", &end_0) != 1 ||
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sscanf(tokens[tok + 5].c_str(), "%lf", &wid_0) != 1 ||
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sscanf(tokens[tok + 6].c_str(), "%lf", &hgt_0) != 1 ||
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sscanf(tokens[tok + 7].c_str(), "%d", &cls_1) != 1 ||
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sscanf(tokens[tok + 8].c_str(), "%d", &start_1) != 1 ||
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sscanf(tokens[tok + 9].c_str(), "%d", &end_1) != 1 ||
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sscanf(tokens[tok + 11].c_str(), "%lf", &delta_top) != 1 ||
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sscanf(tokens[tok + 12].c_str(), "%lf", &wid_1) != 1 ||
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sscanf(tokens[tok + 13].c_str(), "%lf", &hgt_1) != 1 ||
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(start_0 != 0 && start_0 != 1) || (end_0 != 0 && end_0 != 1) ||
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(start_1 != 0 && start_1 != 1) || (end_1 != 0 && end_1 != 1)) {
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fprintf(stderr, "Cube ERROR (WordSizeModel::Init): bad format at "
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"line %d\n", 1 + (tok / token_cnt));
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return false;
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}
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size_code_0 = SizeCode(cls_0, start_0, end_0);
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size_code_1 = SizeCode(cls_1, start_1, end_1);
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} else {
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if (sscanf(tokens[tok + 1].c_str(), "%d", &cls_0) != 1 ||
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sscanf(tokens[tok + 3].c_str(), "%lf", &wid_0) != 1 ||
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sscanf(tokens[tok + 4].c_str(), "%lf", &hgt_0) != 1 ||
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sscanf(tokens[tok + 5].c_str(), "%d", &cls_1) != 1 ||
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sscanf(tokens[tok + 7].c_str(), "%lf", &delta_top) != 1 ||
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sscanf(tokens[tok + 8].c_str(), "%lf", &wid_1) != 1 ||
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sscanf(tokens[tok + 9].c_str(), "%lf", &hgt_1) != 1) {
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fprintf(stderr, "Cube ERROR (WordSizeModel::Init): bad format at "
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"line %d\n", 1 + (tok / token_cnt));
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return false;
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}
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size_code_0 = cls_0;
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size_code_1 = cls_1;
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}
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// copy the data to the size tables
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FontPairSizeInfo fnt_info = font_pair_size_models_.back();
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fnt_info.pair_size_info[size_code_0][size_code_1].delta_top =
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static_cast<int>(delta_top * kShapeModelScale);
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fnt_info.pair_size_info[size_code_0][size_code_1].wid_0 =
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static_cast<int>(wid_0 * kShapeModelScale);
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fnt_info.pair_size_info[size_code_0][size_code_1].hgt_0 =
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static_cast<int>(hgt_0 * kShapeModelScale);
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fnt_info.pair_size_info[size_code_0][size_code_1].wid_1 =
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static_cast<int>(wid_1 * kShapeModelScale);
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fnt_info.pair_size_info[size_code_0][size_code_1].hgt_1 =
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static_cast<int>(hgt_1 * kShapeModelScale);
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fnt_name = tokens[tok];
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}
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return true;
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}
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int WordSizeModel::Cost(CharSamp **samp_array, int samp_cnt) const {
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if (samp_cnt < 2) {
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return 0;
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}
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double best_dist = static_cast<double>(WORST_COST);
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int best_fnt = -1;
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for (int fnt = 0; fnt < font_pair_size_models_.size(); fnt++) {
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const FontPairSizeInfo *fnt_info = &font_pair_size_models_[fnt];
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double mean_dist = 0;
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int pair_cnt = 0;
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for (int smp_0 = 0; smp_0 < samp_cnt; smp_0++) {
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int cls_0 = char_set_->ClassID(samp_array[smp_0]->StrLabel());
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if (cls_0 < 1) {
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continue;
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}
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// compute size code for samp 0 based on class id and position
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int size_code_0;
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if (contextual_) {
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size_code_0 = SizeCode(cls_0,
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samp_array[smp_0]->FirstChar() == 0 ? 0 : 1,
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samp_array[smp_0]->LastChar() == 0 ? 0 : 1);
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} else {
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size_code_0 = cls_0;
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}
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int char0_height = samp_array[smp_0]->Height();
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int char0_width = samp_array[smp_0]->Width();
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int char0_top = samp_array[smp_0]->Top();
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for (int smp_1 = smp_0 + 1; smp_1 < samp_cnt; smp_1++) {
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int cls_1 = char_set_->ClassID(samp_array[smp_1]->StrLabel());
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if (cls_1 < 1) {
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continue;
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}
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// compute size code for samp 0 based on class id and position
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int size_code_1;
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if (contextual_) {
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size_code_1 = SizeCode(cls_1,
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samp_array[smp_1]->FirstChar() == 0 ? 0 : 1,
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samp_array[smp_1]->LastChar() == 0 ? 0 : 1);
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} else {
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size_code_1 = cls_1;
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}
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double dist = PairCost(
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char0_width, char0_height, char0_top, samp_array[smp_1]->Width(),
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samp_array[smp_1]->Height(), samp_array[smp_1]->Top(),
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fnt_info->pair_size_info[size_code_0][size_code_1]);
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if (dist > 0) {
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mean_dist += dist;
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pair_cnt++;
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}
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} // smp_1
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} // smp_0
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if (pair_cnt == 0) {
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continue;
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}
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mean_dist /= pair_cnt;
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if (best_fnt == -1 || mean_dist < best_dist) {
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best_dist = mean_dist;
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best_fnt = fnt;
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}
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}
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if (best_fnt == -1) {
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return static_cast<int>(WORST_COST);
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} else {
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return static_cast<int>(best_dist);
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}
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}
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double WordSizeModel::PairCost(int width_0, int height_0, int top_0,
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int width_1, int height_1, int top_1,
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const PairSizeInfo& pair_info) {
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double scale_factor = static_cast<double>(pair_info.hgt_0) /
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static_cast<double>(height_0);
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double dist = 0.0;
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if (scale_factor > 0) {
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double norm_width_0 = width_0 * scale_factor;
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double norm_width_1 = width_1 * scale_factor;
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double norm_height_1 = height_1 * scale_factor;
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double norm_delta_top = (top_1 - top_0) * scale_factor;
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// accumulate the distance between the model character and the
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// predicted one on all dimensions of the pair
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dist += fabs(pair_info.wid_0 - norm_width_0);
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dist += fabs(pair_info.wid_1 - norm_width_1);
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dist += fabs(pair_info.hgt_1 - norm_height_1);
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dist += fabs(pair_info.delta_top - norm_delta_top);
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}
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return dist;
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}
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} // namespace tesseract
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