Fix some compiler warnings

src/api/baseapi.cpp

@@ -1402,7 +1402,9 @@ char *TessBaseAPI::GetTSVText(int page_number) {
     return nullptr;
   }
 
+#if !defined(NDEBUG)
   int lcnt = 1, bcnt = 1, pcnt = 1, wcnt = 1;
+#endif
   int page_id = page_number + 1; // we use 1-based page numbers.
 
   int page_num = page_id;
@@ -1484,6 +1486,7 @@ char *TessBaseAPI::GetTSVText(int page_number) {
     tsv_str += "\t" + std::to_string(res_it->Confidence(RIL_WORD));
     tsv_str += "\t";
 
+#if !defined(NDEBUG)
     // Increment counts if at end of block/paragraph/textline.
     if (res_it->IsAtFinalElement(RIL_TEXTLINE, RIL_WORD)) {
       lcnt++;
@@ -1494,13 +1497,16 @@ char *TessBaseAPI::GetTSVText(int page_number) {
     if (res_it->IsAtFinalElement(RIL_BLOCK, RIL_WORD)) {
       bcnt++;
     }
+#endif
 
     do {
       tsv_str += std::unique_ptr<const char[]>(res_it->GetUTF8Text(RIL_SYMBOL)).get();
       res_it->Next(RIL_SYMBOL);
     } while (!res_it->Empty(RIL_BLOCK) && !res_it->IsAtBeginningOf(RIL_WORD));
     tsv_str += "\n"; // end of row
+#if !defined(NDEBUG)
     wcnt++;
+#endif
   }
 
   char *ret = new char[tsv_str.length() + 1];

src/api/pagerenderer.cpp

@@ -391,7 +391,7 @@ Pta *SortBaseline(Pta *baseline_pts,
   Pta *sorted_baseline_pts;
 
   sorted_baseline_pts =
-      ptaSort(baseline_pts, L_SORT_BY_X, L_SORT_INCREASING, NULL);
+      ptaSort(baseline_pts, L_SORT_BY_X, L_SORT_INCREASING, nullptr);
 
   do {
     ptaGetPt(sorted_baseline_pts, index, &x0, &y0);
@@ -557,8 +557,8 @@ Pta *FitBaselineIntoLinePolygon(Pta *bottom_pts, Pta *baseline_pts,
 
   // Calculate quartiles to find outliers
   numaGetMedian(poly_bl_delta, &delta_median);
-  numaGetRankValue(poly_bl_delta, 0.25, NULL, 0, &delta_median_Q1);
-  numaGetRankValue(poly_bl_delta, 0.75, NULL, 0, &delta_median_Q3);
+  numaGetRankValue(poly_bl_delta, 0.25, nullptr, 0, &delta_median_Q1);
+  numaGetRankValue(poly_bl_delta, 0.75, nullptr, 0, &delta_median_Q3);
 
   // Fit baseline into the polygon
   // Todo: Needs maybe some adjustments to suppress fitting to superscript

src/ccmain/osdetect.cpp

@@ -223,7 +223,9 @@ int orientation_and_script_detection(const char *filename, OSResults *osr,
 // Returns a non-zero number of blobs if the page was successfully processed, or
 // zero if the page had too few characters to be reliable
 int os_detect(TO_BLOCK_LIST *port_blocks, OSResults *osr, tesseract::Tesseract *tess) {
+#if !defined(NDEBUG)
   int blobs_total = 0;
+#endif
   TO_BLOCK_IT block_it;
   block_it.set_to_list(port_blocks);
 
@@ -241,7 +243,9 @@ int os_detect(TO_BLOCK_LIST *port_blocks, OSResults *osr, tesseract::Tesseract *
       BLOBNBOX *bbox = bbox_it.data();
       C_BLOB *blob = bbox->cblob();
       TBOX box = blob->bounding_box();
+#if !defined(NDEBUG)
       ++blobs_total;
+#endif
 
       // Catch illegal value of box width and avoid division by zero.
       if (box.width() == 0) {

src/ccstruct/points.h

@@ -77,7 +77,7 @@ class ICOORD {
 
   /// find sq length
   float sqlength() const {
-    return (float)(xcoord * xcoord + ycoord * ycoord);
+    return static_cast<float>(xcoord * xcoord + ycoord * ycoord);
   }
 
   /// find length
@@ -101,7 +101,7 @@ class ICOORD {
 
   /// find angle
   float angle() const {
-    return (float)std::atan2(ycoord, xcoord);
+    return std::atan2(static_cast<float>(ycoord), static_cast<float>(xcoord));
   }
 
   /// test equality

src/classify/normmatch.cpp

@@ -52,17 +52,17 @@ struct NORM_PROTOS {
  * normalization adjustment.  The equation that represents the transform is:
  *       1 / (1 + (NormAdj / midpoint) ^ curl)
  */
-static double NormEvidenceOf(double NormAdj) {
-  NormAdj /= classify_norm_adj_midpoint;
+static float NormEvidenceOf(float NormAdj) {
+  NormAdj /= static_cast<float>(classify_norm_adj_midpoint);
 
   if (classify_norm_adj_curl == 3) {
     NormAdj = NormAdj * NormAdj * NormAdj;
   } else if (classify_norm_adj_curl == 2) {
     NormAdj = NormAdj * NormAdj;
   } else {
-    NormAdj = pow(NormAdj, classify_norm_adj_curl);
+    NormAdj = std::pow(NormAdj, static_cast<float>(classify_norm_adj_curl));
   }
-  return (1.0 / (1.0 + NormAdj));
+  return (1 / (1 + NormAdj));
 }
 
 /*----------------------------------------------------------------------------
@@ -73,7 +73,7 @@ static double NormEvidenceOf(double NormAdj) {
 double_VAR(classify_norm_adj_midpoint, 32.0, "Norm adjust midpoint ...");
 double_VAR(classify_norm_adj_curl, 2.0, "Norm adjust curl ...");
 /** Weight of width variance against height and vertical position. */
-const double kWidthErrorWeighting = 0.125;
+const float kWidthErrorWeighting = 0.125f;
 
 /*----------------------------------------------------------------------------
               Public Code
@@ -102,7 +102,7 @@ float Classify::ComputeNormMatch(CLASS_ID ClassId, const FEATURE_STRUCT &feature
     float Match = (feature.Params[CharNormLength] * feature.Params[CharNormLength] * 500.0f +
                    feature.Params[CharNormRx] * feature.Params[CharNormRx] * 8000.0f +
                    feature.Params[CharNormRy] * feature.Params[CharNormRy] * 8000.0f);
-    return (1.0f - NormEvidenceOf(Match));
+    return (1 - NormEvidenceOf(Match));
   }
 
   float BestMatch = FLT_MAX;
@@ -112,7 +112,6 @@ float Classify::ComputeNormMatch(CLASS_ID ClassId, const FEATURE_STRUCT &feature
     tprintf("\nChar norm for class %s\n", unicharset.id_to_unichar(ClassId));
   }
 
-  int ProtoId = 0;
   iterate(Protos) {
     auto Proto = reinterpret_cast<PROTOTYPE *>(Protos->first_node());
     float Delta = feature.Params[CharNormY] - Proto->Mean[CharNormY];
@@ -145,10 +144,8 @@ float Classify::ComputeNormMatch(CLASS_ID ClassId, const FEATURE_STRUCT &feature
     if (Match < BestMatch) {
       BestMatch = Match;
     }
-
-    ProtoId++;
   }
-  return 1.0 - NormEvidenceOf(BestMatch);
+  return 1 - NormEvidenceOf(BestMatch);
 } /* ComputeNormMatch */
 
 void Classify::FreeNormProtos() {

src/dict/dawg.h

@@ -34,10 +34,10 @@
 
 #ifndef __GNUC__
 #  ifdef _WIN32
-#    define NO_EDGE (int64_t)0xffffffffffffffffi64
+#    define NO_EDGE static_cast<int64_t>(0xffffffffffffffffi64)
 #  endif /*_WIN32*/
 #else
-#  define NO_EDGE (int64_t)0xffffffffffffffffll
+#  define NO_EDGE static_cast<int64_t>(0xffffffffffffffffll)
 #endif /*__GNUC__*/
 
 namespace tesseract {
@@ -74,12 +74,12 @@ enum DawgType {
               C o n s t a n t s
 ----------------------------------------------------------------------*/
 
-#define FORWARD_EDGE (int32_t)0
-#define BACKWARD_EDGE (int32_t)1
-#define MAX_NODE_EDGES_DISPLAY (int64_t)100
-#define MARKER_FLAG (int64_t)1
-#define DIRECTION_FLAG (int64_t)2
-#define WERD_END_FLAG (int64_t)4
+#define FORWARD_EDGE static_cast<int32_t>(0)
+#define BACKWARD_EDGE static_cast<int32_t>(1)
+#define MAX_NODE_EDGES_DISPLAY static_cast<int64_t>(100)
+#define MARKER_FLAG static_cast<int64_t>(1)
+#define DIRECTION_FLAG static_cast<int64_t>(2)
+#define WERD_END_FLAG static_cast<int64_t>(4)
 #define LETTER_START_BIT 0
 #define NUM_FLAG_BITS 3
 #define REFFORMAT "%" PRId64

src/textord/topitch.cpp

@@ -151,7 +151,6 @@ void fix_row_pitch(TO_ROW *bad_row,        // row to fix
   int like_votes;                // votes over page
   int other_votes;               // votes of unlike blocks
   int block_index;               // number of block
-  int row_index;                 // number of row
   int maxwidth;                  // max pitch
   TO_BLOCK_IT block_it = blocks; // block iterator
   TO_BLOCK *block;               // current block
@@ -172,7 +171,6 @@ void fix_row_pitch(TO_ROW *bad_row,        // row to fix
       if (pb != nullptr && !pb->IsText()) {
         continue; // Non text doesn't exist!
       }
-      row_index = 1;
       TO_ROW_IT row_it(block->get_rows());
       for (row_it.mark_cycle_pt(); !row_it.cycled_list(); row_it.forward()) {
         row = row_it.data();
@@ -226,7 +224,6 @@ void fix_row_pitch(TO_ROW *bad_row,        // row to fix
             other_votes--;
           }
         }
-        row_index++;
       }
       block_index++;
     }
@@ -518,7 +515,6 @@ bool try_rows_fixed(     // find line stats
     bool testing_on      // correct orientation
 ) {
   TO_ROW *row;           // current row
-  int32_t row_index;     // row number.
   int32_t def_fixed = 0; // counters
   int32_t def_prop = 0;
   int32_t maybe_fixed = 0;
@@ -529,7 +525,6 @@ bool try_rows_fixed(     // find line stats
   float lower, upper; // cluster thresholds
   TO_ROW_IT row_it = block->get_rows();
 
-  row_index = 1;
   for (row_it.mark_cycle_pt(); !row_it.cycled_list(); row_it.forward()) {
     row = row_it.data();
     ASSERT_HOST(row->xheight > 0);
@@ -541,7 +536,6 @@ bool try_rows_fixed(     // find line stats
         row->kern_size = lower;
       }
     }
-    row_index++;
   }
   count_block_votes(block, def_fixed, def_prop, maybe_fixed, maybe_prop, corr_fixed, corr_prop,
                     dunno);

src/training/cntraining.cpp

@@ -116,15 +116,19 @@ int main(int argc, char *argv[]) {
   InitFeatureDefs(&FeatureDefs);
 
   ParseArguments(&argc, &argv);
+#if !defined(NDEBUG)
   int num_fonts = 0;
+#endif
   for (const char *PageName = *++argv; PageName != nullptr; PageName = *++argv) {
     printf("Reading %s ...\n", PageName);
     FILE *TrainingPage = fopen(PageName, "rb");
     ASSERT_HOST(TrainingPage);
     if (TrainingPage) {
       ReadTrainingSamples(FeatureDefs, PROGRAM_FEATURE_TYPE, 100, nullptr, TrainingPage, &CharList);
       fclose(TrainingPage);
+#if !defined(NDEBUG)
       ++num_fonts;
+#endif
     }
   }
   printf("Clustering ...\n");

src/training/common/errorcounter.cpp

@@ -114,7 +114,9 @@ void ErrorCounter::DebugNewErrors(ShapeClassifier *new_classifier, ShapeClassifi
   ErrorCounter new_counter(new_classifier->GetUnicharset(), fontsize);
   std::vector<UnicharRating> results;
 
+#if !defined(NDEBUG)
   int total_samples = 0;
+#endif
   int error_samples = 25;
   int total_new_errors = 0;
   // Iterate over all the samples, accumulating errors.
@@ -145,7 +147,9 @@ void ErrorCounter::DebugNewErrors(ShapeClassifier *new_classifier, ShapeClassifi
         }
       }
     }
+#if !defined(NDEBUG)
     ++total_samples;
+#endif
   }
   tprintf("Total new errors = %d\n", total_new_errors);
 }

src/training/common/networkbuilder.cpp

@@ -114,7 +114,6 @@ Network *NetworkBuilder::BuildFromString(const StaticShape &input_shape, const c
       return ParseOutput(input_shape, str);
     default:
       tprintf("Invalid network spec:%s\n", *str);
-      return nullptr;
   }
   return nullptr;
 }

src/training/common/sampleiterator.cpp

@@ -240,11 +240,9 @@ int SampleIterator::UniformSamples() {
 // to 1. Returns the minimum assigned sample weight.
 double SampleIterator::NormalizeSamples() {
   double total_weight = 0.0;
-  int sample_count = 0;
   for (Begin(); !AtEnd(); Next()) {
     const TrainingSample &sample = GetSample();
     total_weight += sample.weight();
-    ++sample_count;
   }
   // Normalize samples.
   double min_assigned_sample_weight = 1.0;

src/wordrec/chopper.cpp

@@ -344,7 +344,7 @@ SEAM *Wordrec::improve_one_blob(const std::vector<BLOB_CHOICE *> &blob_choices,
     // TODO(rays) it may eventually help to allow italic_blob to be true,
     seam = chop_numbered_blob(word->chopped_word, *blob_number, italic_blob, word->seam_array);
     if (seam != nullptr) {
-      return seam; // Success!
+      break; // Success!
     }
     if (blob_choices[*blob_number] == nullptr) {
       return nullptr;

unittest/applybox_test.cc

@@ -64,7 +64,6 @@ class ApplyBoxTest : public testing::Test {
     if (!SetImage(imagefile)) {
       // eng.traineddata not found or other problem during Init.
       GTEST_SKIP();
-      return;
     }
     if (line_mode) {
       api_.SetVariable("tessedit_resegment_from_line_boxes", "1");

unittest/baseapi_test.cc

@@ -124,7 +124,6 @@ TEST_F(TesseractTest, HOCRWorksWithoutSetInputName) {
   if (api.Init(TessdataPath().c_str(), "eng", tesseract::OEM_TESSERACT_ONLY) == -1) {
     // eng.traineddata not found.
     GTEST_SKIP();
-    return;
   }
   Image src_pix = pixRead(TestDataNameToPath("HelloGoogle.tif").c_str());
   CHECK(src_pix);
@@ -143,7 +142,6 @@ TEST_F(TesseractTest, HOCRContainsBaseline) {
   if (api.Init(TessdataPath().c_str(), "eng", tesseract::OEM_TESSERACT_ONLY) == -1) {
     // eng.traineddata not found.
     GTEST_SKIP();
-    return;
   }
   Image src_pix = pixRead(TestDataNameToPath("HelloGoogle.tif").c_str());
   CHECK(src_pix);
@@ -179,7 +177,6 @@ TEST_F(TesseractTest, AdaptToWordStrTest) {
   if (api.Init(TessdataPath().c_str(), "eng", tesseract::OEM_TESSERACT_ONLY) == -1) {
     // eng.traineddata not found.
     GTEST_SKIP();
-    return;
   }
   api.SetVariable("matcher_sufficient_examples_for_prototyping", "1");
   api.SetVariable("classify_class_pruner_threshold", "220");
@@ -215,7 +212,6 @@ TEST_F(TesseractTest, BasicLSTMTest) {
   if (api.Init(TessdataPath().c_str(), "eng", tesseract::OEM_LSTM_ONLY) == -1) {
     // eng.traineddata not found.
     GTEST_SKIP();
-    return;
   }
   Image src_pix = pixRead(TestDataNameToPath("phototest_2.tif").c_str());
   CHECK(src_pix);
@@ -239,7 +235,6 @@ TEST_F(TesseractTest, LSTMGeometryTest) {
   if (api.Init(TessdataPath().c_str(), "eng", tesseract::OEM_LSTM_ONLY) == -1) {
     // eng.traineddata not found.
     GTEST_SKIP();
-    return;
   }
   api.SetImage(src_pix);
   ASSERT_EQ(api.Recognize(nullptr), 0);