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Squashed commit from https://github.com/tesseract-ocr/tesseract/tree/more-doxygen closes #14 Commits:6317305
doxygen9f42f69
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language_model.cppfa85709
lm_pain_points.cpp lm_state.cpp6418da3
merge06190ba
Merge branch 'old_doxygen_merge' into more-doxygen84acf08
Merge branch 'master' into more-doxygen50fe1ff
pagewalk.cpp cube_reco_context.cpp2982583
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applybox.cpp, take one8eeb053
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modernise classify/ocrfeatures.cpp2a1cba6
modernise cutil/emalloc.cpp773e006
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doxygen classify/normfeat.cpp9bcbe16
doxygen classify/normmatch.cppaa9a971
doxygen ccmain/cube_control.cppc083ff2
doxygen ccmain/cube_reco_context.cppf842850
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doxygen ccmain/cubeclassifier.cpp15ba750
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doxygen classify/clusttool.cpp0267dec
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doxygen classify/fpoint.cpp512f3bd
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doxygen training/cntraining.cppcce044f
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135 lines
4.7 KiB
C++
135 lines
4.7 KiB
C++
// Copyright 2011 Google Inc. All Rights Reserved.
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// Author: rays@google.com (Ray Smith)
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///////////////////////////////////////////////////////////////////////
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// File: cubeclassifier.cpp
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// Description: Cube implementation of a ShapeClassifier.
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// Author: Ray Smith
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// Created: Wed Nov 23 10:39:45 PST 2011
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//
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// (C) Copyright 2011, 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 "cubeclassifier.h"
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#include "char_altlist.h"
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#include "char_set.h"
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#include "cube_object.h"
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#include "cube_reco_context.h"
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#include "tessclassifier.h"
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#include "tesseractclass.h"
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#include "trainingsample.h"
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#include "unicharset.h"
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namespace tesseract {
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CubeClassifier::CubeClassifier(tesseract::Tesseract* tesseract)
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: cube_cntxt_(tesseract->GetCubeRecoContext()),
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shape_table_(*tesseract->shape_table()) {
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}
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CubeClassifier::~CubeClassifier() {
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}
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/// Classifies the given [training] sample, writing to results.
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/// See ShapeClassifier for a full description.
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int CubeClassifier::UnicharClassifySample(
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const TrainingSample& sample, Pix* page_pix, int debug,
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UNICHAR_ID keep_this, GenericVector<UnicharRating>* results) {
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results->clear();
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if (page_pix == NULL) return 0;
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ASSERT_HOST(cube_cntxt_ != NULL);
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const TBOX& char_box = sample.bounding_box();
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CubeObject* cube_obj = new tesseract::CubeObject(
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cube_cntxt_, page_pix, char_box.left(),
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pixGetHeight(page_pix) - char_box.top(),
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char_box.width(), char_box.height());
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CharAltList* alt_list = cube_obj->RecognizeChar();
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if (alt_list != NULL) {
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alt_list->Sort();
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CharSet* char_set = cube_cntxt_->CharacterSet();
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for (int i = 0; i < alt_list->AltCount(); ++i) {
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// Convert cube representation to a shape_id.
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int alt_id = alt_list->Alt(i);
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int unichar_id = char_set->UnicharID(char_set->ClassString(alt_id));
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if (unichar_id >= 0)
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results->push_back(UnicharRating(unichar_id, alt_list->AltProb(i)));
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}
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delete alt_list;
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}
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delete cube_obj;
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return results->size();
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}
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/** Provides access to the ShapeTable that this classifier works with. */
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const ShapeTable* CubeClassifier::GetShapeTable() const {
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return &shape_table_;
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}
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CubeTessClassifier::CubeTessClassifier(tesseract::Tesseract* tesseract)
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: cube_cntxt_(tesseract->GetCubeRecoContext()),
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shape_table_(*tesseract->shape_table()),
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pruner_(new TessClassifier(true, tesseract)) {
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}
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CubeTessClassifier::~CubeTessClassifier() {
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delete pruner_;
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}
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/// Classifies the given [training] sample, writing to results.
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/// See ShapeClassifier for a full description.
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int CubeTessClassifier::UnicharClassifySample(
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const TrainingSample& sample, Pix* page_pix, int debug,
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UNICHAR_ID keep_this, GenericVector<UnicharRating>* results) {
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int num_results = pruner_->UnicharClassifySample(sample, page_pix, debug,
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keep_this, results);
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if (page_pix == NULL) return num_results;
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ASSERT_HOST(cube_cntxt_ != NULL);
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const TBOX& char_box = sample.bounding_box();
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CubeObject* cube_obj = new tesseract::CubeObject(
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cube_cntxt_, page_pix, char_box.left(),
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pixGetHeight(page_pix) - char_box.top(),
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char_box.width(), char_box.height());
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CharAltList* alt_list = cube_obj->RecognizeChar();
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CharSet* char_set = cube_cntxt_->CharacterSet();
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if (alt_list != NULL) {
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for (int r = 0; r < num_results; ++r) {
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// Get the best cube probability of the unichar in the result.
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double best_prob = 0.0;
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for (int i = 0; i < alt_list->AltCount(); ++i) {
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int alt_id = alt_list->Alt(i);
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int unichar_id = char_set->UnicharID(char_set->ClassString(alt_id));
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if (unichar_id == (*results)[r].unichar_id &&
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alt_list->AltProb(i) > best_prob) {
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best_prob = alt_list->AltProb(i);
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}
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}
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(*results)[r].rating = best_prob;
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}
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delete alt_list;
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// Re-sort by rating.
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results->sort(&UnicharRating::SortDescendingRating);
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}
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delete cube_obj;
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return results->size();
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}
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/** Provides access to the ShapeTable that this classifier works with. */
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const ShapeTable* CubeTessClassifier::GetShapeTable() const {
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return &shape_table_;
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}
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} // namespace tesseract
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