--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/mupdf-source/thirdparty/tesseract/src/classify/float2int.cpp	Mon Sep 15 11:43:07 2025 +0200
@@ -0,0 +1,105 @@
+/******************************************************************************
+ ** Filename:    float2int.cpp
+ ** Purpose:     Routines for converting float features to int features
+ ** Author:      Dan Johnson
+ **
+ ** (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 "float2int.h"
+
+#include "classify.h"
+#include "mfoutline.h"
+#include "normmatch.h"
+#include "picofeat.h"
+
+#include "helpers.h"
+
+#define MAX_INT_CHAR_NORM (INT_CHAR_NORM_RANGE - 1)
+
+/*---------------------------------------------------------------------------*/
+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
+ */
+void Classify::ClearCharNormArray(uint8_t *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()
+ */
+void Classify::ComputeIntCharNormArray(const FEATURE_STRUCT &norm_feature,
+                                       uint8_t *char_norm_array) {
+  for (unsigned 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
+ */
+void Classify::ComputeIntFeatures(FEATURE_SET Features, INT_FEATURE_ARRAY IntFeatures) {
+  float YShift;
+
+  if (classify_norm_method == baseline) {
+    YShift = BASELINE_Y_SHIFT;
+  } else {
+    YShift = Y_SHIFT;
+  }
+
+  for (int Fid = 0; Fid < Features->NumFeatures; Fid++) {
+    FEATURE Feature = Features->Features[Fid];
+
+    IntFeatures[Fid].X = Bucket8For(Feature->Params[PicoFeatX], X_SHIFT, INT_FEAT_RANGE);
+    IntFeatures[Fid].Y = Bucket8For(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