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https://github.com/tesseract-ocr/tesseract.git
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124 lines
4.6 KiB
C++
124 lines
4.6 KiB
C++
/******************************************************************************
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** Filename: float2int.c
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** Purpose: Routines for converting float features to int features
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** Author: Dan Johnson
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** History: Wed Mar 13 07:47:48 1991, DSJ, Created.
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**
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** (c) Copyright Hewlett-Packard Company, 1988.
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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 Files and Type Defines
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-----------------------------------------------------------------------------*/
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#include "float2int.h"
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#include "normmatch.h"
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#include "mfoutline.h"
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#include "classify.h"
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#include "helpers.h"
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#include "picofeat.h"
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#define MAX_INT_CHAR_NORM (INT_CHAR_NORM_RANGE - 1)
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/*-----------------------------------------------------------------------------
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Public Code
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-----------------------------------------------------------------------------*/
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/*---------------------------------------------------------------------------*/
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namespace tesseract {
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/**
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* For each class in the unicharset, clears the corresponding
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* entry in char_norm_array. char_norm_array is indexed by unichar_id.
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*
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* Globals:
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* - none
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*
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* @param char_norm_array array to be cleared
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*
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* @note Exceptions: none
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* @note History: Wed Feb 20 11:20:54 1991, DSJ, Created.
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*/
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void Classify::ClearCharNormArray(uinT8* char_norm_array) {
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memset(char_norm_array, 0, sizeof(*char_norm_array) * unicharset.size());
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} /* ClearCharNormArray */
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/*---------------------------------------------------------------------------*/
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/**
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* For each class in unicharset, computes the match between
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* norm_feature and the normalization protos for that class.
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* Converts this number to the range from 0 - 255 and stores it
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* into char_norm_array. CharNormArray is indexed by unichar_id.
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*
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* Globals:
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* - PreTrainedTemplates current set of built-in templates
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*
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* @param norm_feature character normalization feature
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* @param[out] char_norm_array place to put results of size unicharset.size()
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*
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* @note Exceptions: none
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* @note History: Wed Feb 20 11:20:54 1991, DSJ, Created.
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*/
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void Classify::ComputeIntCharNormArray(const FEATURE_STRUCT& norm_feature,
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uinT8* char_norm_array) {
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for (int i = 0; i < unicharset.size(); i++) {
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if (i < PreTrainedTemplates->NumClasses) {
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int norm_adjust = static_cast<int>(INT_CHAR_NORM_RANGE *
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ComputeNormMatch(i, norm_feature, FALSE));
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char_norm_array[i] = ClipToRange(norm_adjust, 0, MAX_INT_CHAR_NORM);
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} else {
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// Classes with no templates (eg. ambigs & ligatures) default
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// to worst match.
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char_norm_array[i] = MAX_INT_CHAR_NORM;
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}
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}
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} /* ComputeIntCharNormArray */
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/*---------------------------------------------------------------------------*/
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/**
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* This routine converts each floating point pico-feature
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* in Features into integer format and saves it into
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* IntFeatures.
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*
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* Globals:
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* - none
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*
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* @param Features floating point pico-features to be converted
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* @param[out] IntFeatures array to put converted features into
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*
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* @note Exceptions: none
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* @note History: Wed Feb 20 10:58:45 1991, DSJ, Created.
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*/
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void Classify::ComputeIntFeatures(FEATURE_SET Features,
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INT_FEATURE_ARRAY IntFeatures) {
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int Fid;
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FEATURE Feature;
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FLOAT32 YShift;
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if (classify_norm_method == baseline)
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YShift = BASELINE_Y_SHIFT;
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else
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YShift = Y_SHIFT;
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for (Fid = 0; Fid < Features->NumFeatures; Fid++) {
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Feature = Features->Features[Fid];
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IntFeatures[Fid].X =
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Bucket8For(Feature->Params[PicoFeatX], X_SHIFT, INT_FEAT_RANGE);
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IntFeatures[Fid].Y =
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Bucket8For(Feature->Params[PicoFeatY], YShift, INT_FEAT_RANGE);
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IntFeatures[Fid].Theta = CircBucketFor(Feature->Params[PicoFeatDir],
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ANGLE_SHIFT, INT_FEAT_RANGE);
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IntFeatures[Fid].CP_misses = 0;
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}
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} /* ComputeIntFeatures */
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} // namespace tesseract
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