tesseract/classify/float2int.cpp

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