classify: Fix typos in comments and strings

All of them were found by codespell.

Signed-off-by: Stefan Weil <sw@weilnetz.de>

classify/adaptmatch.cpp

@@ -515,7 +515,7 @@ void Classify::EndAdaptiveClassifier() {
  *      load_pre_trained_templates  Indicates whether the pre-trained
  *                     templates (inttemp, normproto and pffmtable components)
  *                     should be lodaded. Should only be set to true if the
- *                     necesary classifier components are present in the
+ *                     necessary classifier components are present in the
  *                     [lang].traineddata file.
  *  Globals:
  *      BuiltInTemplatesFile  file to get built-in temps from
@@ -1720,7 +1720,7 @@ bool Classify::LooksLikeGarbage(TBLOB *blob) {
  *
  * Globals:
  *
- * @return Number of features extracted or 0 if an error occured.
+ * @return Number of features extracted or 0 if an error occurred.
  * @note Exceptions: none
  * @note History: Tue May 28 10:40:52 1991, DSJ, Created.
  */
@@ -2082,7 +2082,7 @@ void Classify::PrintAdaptiveMatchResults(const ADAPT_RESULTS& results) {
 
 /*---------------------------------------------------------------------------*/
 /**
- * This routine steps thru each matching class in Results
+ * This routine steps through each matching class in Results
  * and removes it from the match list if its rating
  * is worse than the BestRating plus a pad.  In other words,
  * all good matches get moved to the front of the classes

classify/classify.cpp

@@ -151,7 +151,7 @@ Classify::Classify()
       INT_MEMBER(classify_integer_matcher_multiplier, 10,
                  "Integer Matcher Multiplier  0-255:   ", this->params()),
       EnableLearning(true),
-      INT_MEMBER(il1_adaption_test, 0, "Dont adapt to i/I at beginning of word",
+      INT_MEMBER(il1_adaption_test, 0, "Don't adapt to i/I at beginning of word",
                  this->params()),
       BOOL_MEMBER(classify_bln_numeric_mode, 0,
                   "Assume the input is numbers [0-9].", this->params()),

classify/classify.h

@@ -495,7 +495,7 @@ class Classify : public CCStruct {
   // font combinations that the shape represents.
   UnicityTable<FontSet> fontset_table_;
 
-  INT_VAR_H(il1_adaption_test, 0, "Dont adapt to i/I at beginning of word");
+  INT_VAR_H(il1_adaption_test, 0, "Don't adapt to i/I at beginning of word");
   BOOL_VAR_H(classify_bln_numeric_mode, 0,
              "Assume the input is numbers [0-9].");
   double_VAR_H(speckle_large_max_size, 0.30, "Max large speckle size");

classify/cluster.cpp

@@ -182,7 +182,7 @@ struct BUCKETS {
   FLOAT64 ChiSquared;            // test threshold
   uinT16 NumberOfBuckets;        // number of cells in histogram
   uinT16 Bucket[BUCKETTABLESIZE];// mapping to histogram buckets
-  uinT32 *Count;                 // frequency of occurence histogram
+  uinT32 *Count;                 // frequency of occurrence histogram
   FLOAT32 *ExpectedCount;        // expected histogram
 };
 

classify/clusttool.h

@@ -24,7 +24,7 @@
 #include <stdio.h>
 
 /*-------------------------------------------------------------------------
-        Public Funtion Prototype
+        Public Function Prototype
 --------------------------------------------------------------------------*/
 uinT16 ReadSampleSize(FILE *File);
 

classify/featdefs.cpp

@@ -285,7 +285,7 @@ CHAR_DESC ReadCharDescription(const FEATURE_DEFS_STRUCT &FeatureDefs,
 
 /*---------------------------------------------------------------------------*/
 /**
- * Search thru all features currently defined and return
+ * Search through all features currently defined and return
  * the feature type for the feature with the specified short
  * name.  Trap an error if the specified name is not found.
  *

classify/intfx.cpp

@@ -44,7 +44,7 @@ using tesseract::TrainingSample;
 // The entries are in binary degrees where a full circle is 256 binary degrees.
 static float cos_table[INT_CHAR_NORM_RANGE];
 static float sin_table[INT_CHAR_NORM_RANGE];
-// Guards write access to AtanTable so we dont create it more than once.
+// Guards write access to AtanTable so we don't create it more than once.
 tesseract::CCUtilMutex atan_table_mutex;
 
 

classify/kdtree.cpp

@@ -521,7 +521,7 @@ bool KDTreeSearch::BoxIntersectsSearch(FLOAT32 *lower, FLOAT32 *upper) {
  * Walk a tree, calling action once on each node.
  *
  * Operation:
- *   This routine walks thru the specified sub_tree and invokes action
+ *   This routine walks through the specified sub_tree and invokes action
  *   action at each node as follows:
  *       action(context, data, level)
  *   data  the data contents of the node being visited,

classify/mfoutline.cpp

@@ -104,7 +104,7 @@ LIST ConvertOutlines(TESSLINE *outline,
 
 /*---------------------------------------------------------------------------*/
 /**
- * This routine searches thru the specified outline, computes
+ * This routine searches through the specified outline, computes
  * a slope for each vector in the outline, and marks each
  * vector as having one of the following directions:
  *   N, S, E, W, NE, NW, SE, SW
@@ -182,7 +182,7 @@ void FreeOutlines(LIST Outlines) {
 
 /*---------------------------------------------------------------------------*/
 /**
- * This routine searches thru the specified outline and finds
+ * This routine searches through the specified outline and finds
  * the points at which the outline changes direction.  These
  * points are then marked as "extremities".  This routine is
  * used as an alternative to FindExtremities().  It forces the

classify/picofeat.cpp

@@ -147,7 +147,7 @@ void ConvertSegmentToPicoFeat(FPOINT *Start,
 
 /*---------------------------------------------------------------------------*/
 /**
- * This routine steps thru the specified outline and cuts it
+ * This routine steps through the specified outline and cuts it
  * up into pieces of equal length.  These pieces become the
  * desired pico-features.  Each segment in the outline
  * is converted into an integral number of pico-features.