/****************************************************************************** ** 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: * - PreTrainedTemplates current set of built-in templates * * @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_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