Merge branch 'dev' of gitlab.rezometz.org:guillaume/miniprojet into dev

tests/CMakeLists.txt

@@ -3,6 +3,7 @@ project(miniprojet)
 
 set(PROJECT_CFLAGS "-Wall -Wextra -Wno-missing-braces -std=c++1z")
 find_package(OpenCV REQUIRED)
+find_package(Boost COMPONENTS system filesystem REQUIRED)
 
 add_compile_options(-std=c++17)
 

tests/examples/CMakeLists.txt

@@ -9,7 +9,7 @@ file(
 foreach(f ${usage_examples})
   get_filename_component(exampleName ${f} NAME_WE) 
   add_executable(${exampleName} ${f}) 
-	target_link_libraries(${exampleName} ${OpenCV_LIBS})
+	target_link_libraries(${exampleName} ${OpenCV_LIBS} ${Boost_FILESYSTEM_LIBRARY} ${Boost_SYSTEM_LIBRARY})
   install(PROGRAMS ${CMAKE_CURRENT_BINARY_DIR}/${exampleName}
     DESTINATION bin
     RENAME ${CMAKE_PROJECT_NAME}-${exampleName})

tests/examples/test-csv.cpp

@@ -0,0 +1,28 @@
+#include <math.hpp>
+#include <fstream>
+#include <iostream>
+#include <file.hpp>
+#include <math.hpp>
+
+int main(int argc, char** argv) {
+  math::complex c1 = {0.1, 0.2};
+  math::complex c2 = {0.3, 0.4};
+  math::complex c3 = {0.5, 0.6};
+  math::complex c4 = {0.7, 0.8};
+  math::csignal s1 = {c1, c2};
+  math::csignal s2 = {c3, c4};
+  std::pair<math::csignal, std::string> p1 = {s1, "label1"};
+  std::pair<math::csignal, std::string> p2 = {s2, "label2"};
+  math::dataset d = {p1, p2};
+  save_as_csv(d, "test.csv");
+
+  math::dataset d2 = load_csv("test.csv", s1.size());
+
+  for (auto p: d2) {
+    for (auto x: p.first) {
+      std::cout << x << " ";
+    }
+    std::cout << p.second << std::endl;
+  }
+  return 0;
+}

tests/src/CMakeLists.txt

@@ -1,10 +1,8 @@
 add_executable(traitement traitement.cpp)
 target_link_libraries(traitement ${OpenCV_LIBS})
 
-find_package(Boost COMPONENTS system filesystem REQUIRED)
-
 add_executable(knn knn.cpp)
-target_link_libraries(knn ${OpenCV_LIBS} ${Boost_FILESYSTEM_LIBRARY} ${Boost_SYSTEM_LIBRARY})
+target_link_libraries(knn ${OpenCV_LIBS} ${Boost_SYSTEM_LIBRARY} ${Boost_FILESYSTEM_LIBRARY})
 
 add_executable(neural_network neural_network.cpp)
 target_link_libraries(neural_network ${OpenCV_LIBS} ${Boost_FILESYSTEM_LIBRARY} ${Boost_SYSTEM_LIBRARY})

tests/src/file.hpp

@@ -0,0 +1,93 @@
+#include <boost/filesystem.hpp>
+#include <iostream>
+#include <string>
+#include "math.hpp"
+
+struct path_leaf_string {
+  std::string operator()(const boost::filesystem::directory_entry& entry) const
+  {
+    return entry.path().leaf().string();
+  }
+};
+
+void read_directory(const std::string& name, std::vector<std::string>& v) {
+  boost::filesystem::path p(name);
+  boost::filesystem::directory_iterator start(p);
+  boost::filesystem::directory_iterator end;
+  std::transform(start, end, std::back_inserter(v), path_leaf_string());
+}
+
+void save_as_csv(const math::dataset& dataset, std::string filename) {
+	// file pointer
+  std::fstream fout;
+
+	// opens an existing csv file or creates a new file.
+	fout.open(filename, std::ios::out);
+
+  std::string name;
+
+  // Insert the data to file
+  for (auto p: dataset) {
+    for (auto x: p.first) {
+      fout << x.real() << ','
+           << x.imag() << ',';
+    }
+    fout << p.second;
+    fout << '\n';
+  }
+}
+
+math::dataset& load_csv(std::string filename, int size) {
+  math::dataset* d = new math::dataset();
+  std::fstream fin; 
+
+	// Open an existing file 
+	fin.open(filename, std::ios::in); 
+  std::string line, word, temp; 
+
+	while (fin >> temp) { 
+    std::pair<math::csignal, std::string> p;
+
+    std::getline(fin, line); 
+    std::stringstream s(temp); 
+
+    int count = 0;
+		while (std::getline(s, word, ',')) { 
+      if (count == size) {
+        p.second = word;
+      } else {
+        double a = atof(word.c_str());
+        std::getline(s, word, ',');
+        double b = atof(word.c_str());
+        p.first.push_back(math::complex(a, b));
+      }
+      count++;
+		} 
+    d->push_back(p); 
+	} 
+  return *d;
+}
+
+math::dataset get_data(std::string path, int size, int cmax, int threshold) {
+  math::dataset res;
+  std::vector<std::string> dirs;
+  read_directory(path, dirs);
+  for (auto dir: dirs) {
+    std::vector<std::string> files;
+    read_directory(path+"/"+dir, files);
+
+    std::string label = dir;
+    int count = 0;
+    for (int i=0; count<size/4 && i<files.size(); ++i) {
+      try {
+        math::csignal d = math::img2desc(path+"/"+dir+"/"+files[i], cmax, threshold);
+        res.push_back({d, label});
+        count++;
+      } catch (std::length_error& e) {
+        std::cout << "No contour: image skiped." << std::endl;
+      }
+    }
+    std::cout << res.size() << std::endl;
+  }
+  return res;
+}

tests/src/knn.cpp

@@ -1,28 +1,10 @@
 #include <map>
+#include "file.hpp"
 #include "math.hpp"
 #include <stdexcept>
 #include <queue>
 #include <opencv2/opencv.hpp>
-#include <boost/filesystem.hpp>
-#include <iterator>
 #include <iostream>
-#include <algorithm>
-
-using dataset = std::vector<std::pair<math::csignal, std::string>>;
-
-struct path_leaf_string {
-  std::string operator()(const boost::filesystem::directory_entry& entry) const
-  {
-    return entry.path().leaf().string();
-  }
-};
-
-void read_directory(const std::string& name, std::vector<std::string>& v) {
-  boost::filesystem::path p(name);
-  boost::filesystem::directory_iterator start(p);
-  boost::filesystem::directory_iterator end;
-  std::transform(start, end, std::back_inserter(v), path_leaf_string());
-}
 
 double distance(math::csignal& v1, math::csignal& v2, int n){
   if (v1.size() != v2.size()) {
@@ -64,37 +46,8 @@ struct pair_comp {
   };
 };
 
-math::csignal img2desc(std::string filename, int cmax, int threshold) {
-  cv::Mat img = cv::imread(filename, CV_LOAD_IMAGE_COLOR);
-  return math::descriptors(img, cmax, threshold);
-}
-
-dataset get_data(std::string path, int size, int cmax, int threshold) {
-  dataset res;
-  std::vector<std::string> dirs;
-  read_directory(path, dirs);
-  for (auto dir: dirs) {
-    std::vector<std::string> files;
-    read_directory(path+"/"+dir, files);
-
-    std::string label = dir;
-    int count = 0;
-    for (int i=0; count<size/4 && i<files.size(); ++i) {
-      try {
-        math::csignal d = img2desc(path+"/"+dir+"/"+files[i], cmax, threshold);
-        res.push_back({d, label});
-        count++;
-      } catch (std::length_error& e) {
-        std::cout << "No contour: image skiped." << std::endl;
-      }
-    }
-    std::cout << res.size() << std::endl;
-  }
-  return res;
-}
 
 int main(int argc, char** argv) {
-
   int k = 20;
   int size = 100;
   std::string path;
@@ -109,8 +62,8 @@ int main(int argc, char** argv) {
     return 0;
   }
 
-  dataset references = get_data(path, size, cmax, threshold);
-  math::csignal sample = img2desc(path+"/arret/arret0199.jpg", cmax, threshold);
+  math::dataset references = get_data(path, size, cmax, threshold);
+  math::csignal sample = math::img2desc(path+"/arret/arret0199.jpg", cmax, threshold);
   std::priority_queue<std::pair<double, std::string>, std::vector<std::pair<double, std::string>>, pair_comp> neighbors;
   std::map<std::string, int> labels;
 

tests/src/math.hpp

@@ -14,6 +14,7 @@ namespace math {
   using csignal = std::vector<complex>;
   using contour = std::vector<cv::Point>;
   constexpr double pi() {return std::atan(1)*4;}
+  using dataset = std::vector<std::pair<csignal, std::string>>;
 
   void display_abs(const csignal& s) {
     int count=0;
@@ -391,4 +392,9 @@ namespace math {
 
     return desc;
   }
+
+  math::csignal img2desc(std::string filename, int cmax, int threshold) {
+    cv::Mat img = cv::imread(filename, CV_LOAD_IMAGE_COLOR);
+    return descriptors(img, cmax, threshold);
+  }
 }