tesseract/training/commontraining.h

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// Copyright 2008 Google Inc. All Rights Reserved.
// Author: scharron@google.com (Samuel Charron)
//
// 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.
#ifndef TESSERACT_TRAINING_COMMONTRAINING_H_
#define TESSERACT_TRAINING_COMMONTRAINING_H_
#include "cluster.h"
#include "commandlineflags.h"
#include "featdefs.h"
#include "intproto.h"
#include "oldlist.h"
namespace tesseract {
class Classify;
class MasterTrainer;
class ShapeTable;
}
//////////////////////////////////////////////////////////////////////////////
// Globals ///////////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////////////////////
extern FEATURE_DEFS_STRUCT feature_defs;
// Must be defined in the file that "implements" commonTraining facilities.
extern CLUSTERCONFIG Config;
//////////////////////////////////////////////////////////////////////////////
// Structs ///////////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////////////////////
typedef struct
{
char *Label;
int SampleCount;
int font_sample_count;
LIST List;
}
LABELEDLISTNODE, *LABELEDLIST;
typedef struct
{
char* Label;
int NumMerged[MAX_NUM_PROTOS];
CLASS_TYPE Class;
}MERGE_CLASS_NODE;
typedef MERGE_CLASS_NODE* MERGE_CLASS;
//////////////////////////////////////////////////////////////////////////////
// Functions /////////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////////////////////
void ParseArguments(int* argc, char*** argv);
namespace tesseract {
// Helper loads shape table from the given file.
ShapeTable* LoadShapeTable(const STRING& file_prefix);
// Helper to write the shape_table.
void WriteShapeTable(const STRING& file_prefix, const ShapeTable& shape_table);
// Creates a MasterTraininer and loads the training data into it:
// Initializes feature_defs and IntegerFX.
// Loads the shape_table if shape_table != nullptr.
// Loads initial unicharset from -U command-line option.
// If FLAGS_input_trainer is set, loads the majority of data from there, else:
// Loads font info from -F option.
// Loads xheights from -X option.
// Loads samples from .tr files in remaining command-line args.
// Deletes outliers and computes canonical samples.
// If FLAGS_output_trainer is set, saves the trainer for future use.
// Computes canonical and cloud features.
// If shape_table is not nullptr, but failed to load, make a fake flat one,
// as shape clustering was not run.
MasterTrainer* LoadTrainingData(int argc, const char* const * argv,
bool replication,
ShapeTable** shape_table,
STRING* file_prefix);
} // namespace tesseract.
const char *GetNextFilename(int argc, const char* const * argv);
LABELEDLIST FindList(
LIST List,
char *Label);
LABELEDLIST NewLabeledList(
const char *Label);
void ReadTrainingSamples(const FEATURE_DEFS_STRUCT& feature_defs,
const char *feature_name, int max_samples,
UNICHARSET* unicharset,
FILE* file, LIST* training_samples);
void WriteTrainingSamples(
const FEATURE_DEFS_STRUCT &FeatureDefs,
char *Directory,
LIST CharList,
const char *program_feature_type);
void FreeTrainingSamples(
LIST CharList);
void FreeLabeledList(
LABELEDLIST LabeledList);
void FreeLabeledClassList(
LIST ClassListList);
CLUSTERER *SetUpForClustering(
const FEATURE_DEFS_STRUCT &FeatureDefs,
LABELEDLIST CharSample,
const char *program_feature_type);
LIST RemoveInsignificantProtos(
LIST ProtoList,
BOOL8 KeepSigProtos,
BOOL8 KeepInsigProtos,
int N);
void CleanUpUnusedData(
LIST ProtoList);
void MergeInsignificantProtos(
LIST ProtoList,
const char *label,
CLUSTERER *Clusterer,
CLUSTERCONFIG *Config);
MERGE_CLASS FindClass(
LIST List,
const char *Label);
MERGE_CLASS NewLabeledClass(
const char *Label);
void FreeTrainingSamples(
LIST CharList);
CLASS_STRUCT* SetUpForFloat2Int(const UNICHARSET& unicharset,
LIST LabeledClassList);
void Normalize(
float *Values);
void FreeNormProtoList(
LIST CharList);
void AddToNormProtosList(
LIST* NormProtoList,
LIST ProtoList,
char *CharName);
int NumberOfProtos(
LIST ProtoList,
BOOL8 CountSigProtos,
BOOL8 CountInsigProtos);
void allocNormProtos();
#endif // TESSERACT_TRAINING_COMMONTRAINING_H_