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