mirror of
https://github.com/tesseract-ocr/tesseract.git
synced 2024-11-30 23:49:05 +08:00
4d514d5a60
git-svn-id: https://tesseract-ocr.googlecode.com/svn/trunk@878 d0cd1f9f-072b-0410-8dd7-cf729c803f20
90 lines
3.0 KiB
C++
90 lines
3.0 KiB
C++
///////////////////////////////////////////////////////////////////////
|
|
// File: params_model.h
|
|
// Description: Trained feature serialization for language parameter training.
|
|
// Author: David Eger
|
|
// Created: Mon Jun 11 11:26:42 PDT 2012
|
|
//
|
|
// (C) Copyright 2011, 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.
|
|
//
|
|
///////////////////////////////////////////////////////////////////////
|
|
|
|
#ifndef TESSERACT_WORDREC_PARAMS_MODEL_H_
|
|
#define TESSERACT_WORDREC_PARAMS_MODEL_H_
|
|
|
|
#include "params_training_featdef.h"
|
|
#include "ratngs.h"
|
|
#include "strngs.h"
|
|
|
|
namespace tesseract {
|
|
|
|
// Represents the learned weights for a given language.
|
|
class ParamsModel {
|
|
public:
|
|
// Enum for expressing OCR pass.
|
|
enum PassEnum {
|
|
PTRAIN_PASS1,
|
|
PTRAIN_PASS2,
|
|
|
|
PTRAIN_NUM_PASSES
|
|
};
|
|
|
|
ParamsModel() : pass_(PTRAIN_PASS1) {}
|
|
ParamsModel(const char *lang, const GenericVector<float> &weights) :
|
|
lang_(lang), pass_(PTRAIN_PASS1) { weights_vec_[pass_] = weights; }
|
|
inline bool Initialized() {
|
|
return weights_vec_[pass_].size() == PTRAIN_NUM_FEATURE_TYPES;
|
|
}
|
|
// Prints out feature weights.
|
|
void Print();
|
|
// Clears weights for all passes.
|
|
void Clear() {
|
|
for (int p = 0; p < PTRAIN_NUM_PASSES; ++p) weights_vec_[p].clear();
|
|
}
|
|
// Copies the weights of the given params model.
|
|
void Copy(const ParamsModel &other_model);
|
|
// Applies params model weights to the given features.
|
|
// Assumes that features is an array of size PTRAIN_NUM_FEATURE_TYPES.
|
|
float ComputeCost(const float features[]) const;
|
|
bool Equivalent(const ParamsModel &that) const;
|
|
|
|
// Returns true on success.
|
|
bool SaveToFile(const char *full_path) const;
|
|
|
|
// Returns true on success.
|
|
bool LoadFromFile(const char *lang, const char *full_path);
|
|
bool LoadFromFp(const char *lang, FILE *fp, inT64 end_offset);
|
|
|
|
const GenericVector<float>& weights() const {
|
|
return weights_vec_[pass_];
|
|
}
|
|
const GenericVector<float>& weights_for_pass(PassEnum pass) const {
|
|
return weights_vec_[pass];
|
|
}
|
|
void SetPass(PassEnum pass) { pass_ = pass; }
|
|
|
|
private:
|
|
bool ParseLine(char *line, char **key, float *val);
|
|
|
|
STRING lang_;
|
|
// Set to the current pass type and used to determine which set of weights
|
|
// should be used for ComputeCost() and other functions.
|
|
PassEnum pass_;
|
|
// Several sets of weights for various OCR passes (e.g. pass1 with adaption,
|
|
// pass2 without adaption, etc).
|
|
GenericVector<float> weights_vec_[PTRAIN_NUM_PASSES];
|
|
};
|
|
|
|
} // namespace tesseract
|
|
|
|
#endif // TESSERACT_WORDREC_PARAMS_MODEL_H_
|
|
|