minor cosmetic changes

* use `erase_if` to avoid copying around the data
* use `ASSERT_EQ` on the size to get better debug output in case it
  differs

Author: rursprung

include/banana-lib/lib.hpp

@@ -88,6 +88,9 @@ namespace banana {
         /// Color used to annotate the contours on the analyzed image.
         cv::Scalar const contour_annotation_color_{0, 255, 0};
 
+        /// Maximum score of `cv::matchShapes` which we still accept as a banana.
+        float match_max_score_ = 0.8f;
+
         /// Reference contour for the banana, used in filtering.
         Contour reference_contour_;
 
@@ -100,12 +103,12 @@ namespace banana {
         auto ColorFilter(cv::Mat const& image) const -> cv::Mat;
 
         /**
-         * Compares the input with a banana contour and only passes on those that are similar to it
-         * @param contours
-         * @return banana contour
+         * Checks whether the passed contour is - with a good likelihood - a banana.
+         * @param contour the contour which may or may not be a banana
+         * @return whether it is a banana
          */
         [[nodiscard]]
-        auto FilterContours(Contours const& contours) const -> Contours;
+        auto IsBananaContour(Contour const& contour) const -> bool;
 
         /**
          * Identify all bananas present in an image and return their contours.

src/lib.cpp

@@ -82,16 +82,8 @@ namespace banana {
         return mask;
     }
 
-    auto Analyzer::FilterContours(Contours const& contours) const -> Contours {
-        Contours filtered_contours;
-        auto const match_max_score_ = 0.8;
-        for (auto& contour : contours) {
-            auto const match_score = cv::matchShapes(contour, this->reference_contour_, cv::CONTOURS_MATCH_I1, 0.0);
-            if (match_score < match_max_score_) {
-                filtered_contours.push_back(contour);
-            }
-        }
-        return filtered_contours;
+    auto Analyzer::IsBananaContour(Contour const& contour) const -> bool {
+        return cv::matchShapes(contour, this->reference_contour_, cv::CONTOURS_MATCH_I1, 0.0) > match_max_score_;
     }
 
     auto Analyzer::FindBananaContours(cv::Mat const& image) const -> Contours {
@@ -104,13 +96,17 @@ namespace banana {
         SHOW_DEBUG_IMAGE(filtered_image, "morph");
 
         // Smooth the image
-        cv::medianBlur(filtered_image, filtered_image, 37);    // 41
+        cv::medianBlur(filtered_image, filtered_image, 37); // TODO: test again with 41
         SHOW_DEBUG_IMAGE(filtered_image, "blur");
 
         Contours contours;
         cv::findContours(filtered_image, contours, cv::RETR_EXTERNAL, cv::CHAIN_APPROX_SIMPLE);
 
-        return FilterContours(contours);
+        std::erase_if(contours, [this](auto const& contour) -> auto {
+            return this->IsBananaContour(contour);
+        });
+
+        return contours;
     }
 
     auto Analyzer::AnalyzeBanana(const cv::Mat &image, const Contour &banana_contour) const -> std::expected<AnalysisResult, AnalysisError> {

test/banana-lib-test.cpp

@@ -5,9 +5,7 @@
 
 #include "banana-lib/lib.hpp"
 
-/**
- * Assert that two matrices are identical (same values  for all pixels).
- */
+/// Assert that two matrices are identical (same values  for all pixels).
 #define ASSERT_SAME_MAT(a,b) ASSERT_EQ(cv::Scalar(), cv::sum(a != b))
 
 TEST(GeneralBananaTestSuite, FailOnNonExistingImage) {
@@ -23,7 +21,7 @@ TEST(BananaContourFinderTestSuite, AnalyzeEmptyPicture) {
     auto const result = analyzer.AnalyzeImage(image);
     ASSERT_TRUE(result.has_value());
     auto const& results = result.value();
-    ASSERT_TRUE(results.empty());
+    ASSERT_EQ(0, results.size());
 }
 
 TEST(BananaContourFinderTestSuite, AnalyzeAndAnnotateEmptyPicture) {
@@ -32,7 +30,7 @@ TEST(BananaContourFinderTestSuite, AnalyzeAndAnnotateEmptyPicture) {
     auto const result = analyzer.AnalyzeAndAnnotateImage(image);
     ASSERT_TRUE(result.has_value());
     auto const& analysis_result = result.value();
-    ASSERT_TRUE(analysis_result.banana.empty());
+    ASSERT_EQ(0, analysis_result.banana.size());
     ASSERT_SAME_MAT(analysis_result.annotated_image, image);
 }