Improved SVM Training CLI.

CMakeLists.txt

@@ -23,7 +23,6 @@ set(SOURCE_FILES
     src/train/ann_train.cpp
     src/train/svm_train.cpp
     src/preprocess/deface.cpp
-    src/preprocess/general_test_prepare.cpp
     src/preprocess/gdts.cpp
     src/preprocess/mc_data.cpp
     src/util/util.cpp

include/easypr/svm_train.h

@@ -3,13 +3,11 @@
 
 #include <vector>
 #include <opencv2/opencv.hpp>
-#include "easypr/feature.h"
 
 namespace easypr {
 
 class Svm {
  public:
-
   typedef enum {
     kForward = 1, // correspond to "has plate"
     kInverse = 0  // correspond to "no plate"
@@ -17,23 +15,8 @@ class Svm {
 
   Svm(const char* forward_data_folder, const char* inverse_data_folder);
 
-  void train(bool divide = true, bool train = true,
-            float divide_percentage = 0.7,
-            svmCallback getFeatures = getHistogramFeatures);
-
-//  void getNoPlateTest(std::vector<cv::Mat>& testingImages,
-//                      std::vector<int>& testingLabels);
-//
-//  void getHasPlateTest(std::vector<cv::Mat>& testingImages,
-//                       std::vector<int>& testingLabels);
-//
-//  void getNoPlateTrain(cv::Mat& trainingImages,
-//                       std::vector<int>& trainingLabels,
-//                       svmCallback getFeatures = getHisteqFeatures);
-//
-//  void getHasPlateTrain(cv::Mat& trainingImages,
-//                        std::vector<int>& trainingLabels,
-//                        svmCallback getFeatures = getHisteqFeatures);
+  void train(bool divide = true, float divide_percentage = 0.7,
+             bool train = true, const char* out_svm_folder = NULL);
 
  private:
   /*

src/preprocess/general_test_prepare.cpp

@@ -1,74 +0,0 @@
-// 辅助生成general_test中的图片
-// 通用做法是使用easypr依次读取图片，并用其中的一个车牌识别文字给图片重命名
-// easypr识别的文字不一定准确，因此需要人再次确认与手工调整下
-
-#include "easypr/plate_recognize.h"
-#include "easypr/util.h"
-#include "easypr/feature.h"
-
-using namespace easypr;
-using namespace std;
-using namespace cv;
-
-extern const string GENERAL_TEST_PATH;
-
-// TODO 将下面的路径改成你的
-const string src_path = "F:/data/easypr-data/tmp-5";
-
-// TODO 将下面的路径改成你的
-const string dst_path = "F:/data/easypr-data/tmp-6";
-
-int general_test() {
-  auto files = Utils::getFiles(src_path);
-
-  CPlateRecognize pr;
-
-  pr.LoadANN("resources/model/ann.xml");
-  pr.LoadSVM("resources/model/svm.xml");
-  pr.setLifemode(true);
-
-  size_t size = files.size();
-
-  if (0 == size) {
-    cout << "No File Found!" << endl;
-    return 0;
-  }
-
-  cout << "Begin to prepare general_test!" << endl;
-
-  for (int i = 0; i < size; i++) {
-    string filepath = files[i].c_str();
-    cout << "------------------" << endl;
-
-    // EasyPR开始判断车牌
-    Mat src = imread(filepath);
-    vector<string> plateVec;
-
-    int result = pr.plateRecognize(src, plateVec);
-    if (result == 0) {
-      size_t num = plateVec.size();
-
-      if (num == 0) {
-        cout << "" << "无车牌" << endl;
-      }
-      else {
-        cout << plateVec[0] << endl;
-        string colorplate = plateVec[0];
-
-        // 输出"蓝牌:苏E7KU22"中冒号后面的车牌
-        vector<string> spilt_plate = Utils::splitString(colorplate, ':');
-
-        if (spilt_plate.size() == 2) {
-          stringstream ss(stringstream::in | stringstream::out);
-          ss << dst_path << "/" << spilt_plate[size - 1] << ".jpg";
-          imwrite(ss.str(), src);
-        }
-      }
-    }
-    else {
-      cout << "错误码:" << result << endl;
-    }
-  }
-
-  return 0;
-}

src/preprocess/mc_data.cpp

@@ -9,7 +9,6 @@
 #include <io.h>
 #endif
 
-#include <opencv2/opencv.hpp>
 #include "easypr/util.h"
 
 namespace easypr {
@@ -66,7 +65,7 @@ cv::Mat cut_top_bottom(const cv::Mat& img) {
   int width = img.size().width;
   int height = img.size().height;
   // TODO: it seems not correctly.
-  cv::Rect rect(0, 0, width, height * 0.97);
+  cv::Rect rect(0, 0, width, int(height * 0.97));
   return img(rect);
 }
 

test/chars.hpp

@@ -6,43 +6,43 @@ namespace easypr {
 namespace demo {
 
 int test_chars_segment() {
-  cout << "test_chars_segment" << endl;
+  std::cout << "test_chars_segment" << std::endl;
 
-  Mat src = imread("resources/image/chars_segment.jpg");
+  cv::Mat src = cv::imread("resources/image/chars_segment.jpg");
 
-  vector <Mat> resultVec;
+  std::vector<cv::Mat> resultVec;
   CCharsSegment plate;
 
   int result = plate.charsSegment(src, resultVec);
   if (result == 0) {
     size_t num = resultVec.size();
     for (int j = 0; j < num; j++) {
-      Mat resultMat = resultVec[j];
-      imshow("chars_segment", resultMat);
-      waitKey(0);
+      cv::Mat resultMat = resultVec[j];
+      cv::imshow("chars_segment", resultMat);
+      cv::waitKey(0);
     }
-    destroyWindow("chars_segment");
+    cv::destroyWindow("chars_segment");
   }
 
   return result;
 }
 
 int test_chars_identify() {
-  cout << "test_chars_identify" << endl;
+  std::cout << "test_chars_identify" << std::endl;
 
-  Mat src = imread("resources/image/chars_identify.jpg");
+  cv::Mat src = cv::imread("resources/image/chars_identify.jpg");
 
-  vector <Mat> resultVec;
+  std::vector<cv::Mat> resultVec;
   CCharsSegment cs;
   CCharsIdentify ci;
 
-  string plateIdentify = "";
+  std::string plateIdentify = "";
 
   int result = cs.charsSegment(src, resultVec);
   if (result == 0) {
     size_t num = resultVec.size();
     for (int j = 0; j < num; j++) {
-      Mat resultMat = resultVec[j];
+      cv::Mat resultMat = resultVec[j];
       bool isChinses = false;
       bool isSpec = false;
 
@@ -53,36 +53,36 @@ int test_chars_identify() {
       if (j == 1)
         isSpec = true;
 
-      string charcater = ci.charsIdentify(resultMat, isChinses, isSpec);
+      std::string charcater = ci.charsIdentify(resultMat, isChinses, isSpec);
       plateIdentify = plateIdentify + charcater;
     }
   }
 
-  const string plateLicense = "苏E771H6";
+  const std::string plateLicense = "苏E771H6";
 
-  cout << "plateLicense: " << plateLicense << endl;
-  cout << "plateIdentify: " << plateIdentify << endl;
+  std::cout << "plateLicense: " << plateLicense << std::endl;
+  std::cout << "plateIdentify: " << plateIdentify << std::endl;
 
   if (plateLicense != plateIdentify) {
-    cout << "Identify Not Correct!" << endl;
+    std::cout << "Identify Not Correct!" << std::endl;
     return -1;
   }
-  cout << "Identify Correct!" << endl;
+  std::cout << "Identify Correct!" << std::endl;
 
   return result;
 }
 
 int test_chars_recognise() {
-  cout << "test_chars_recognise" << endl;
+  std::cout << "test_chars_recognise" << std::endl;
 
-  Mat src = imread("resources/image/chars_recognise.jpg");
+  cv::Mat src = cv::imread("resources/image/chars_recognise.jpg");
 
   CCharsRecognise cr;
-  string charsRecognise = "";
+  std::string charsRecognise = "";
 
   int result = cr.charsRecognise(src, charsRecognise);
   if (result == 0) {
-    cout << "charsRecognise: " << charsRecognise << endl;
+    std::cout << "charsRecognise: " << charsRecognise << std::endl;
   }
 
   return result;

test/main.cpp

@@ -1,8 +1,9 @@
 #include "easypr.h"
 #include "easypr/program_options.h"
+
 #include "accuracy.hpp"
-#include "plate.hpp"
 #include "chars.hpp"
+#include "plate.hpp"
 
 namespace easypr {
 
@@ -193,18 +194,32 @@ void command_line_handler(int argc, const char* argv[]) {
   options.add_subroutine("svm", "svm operations")
           .make_usage("Usage:");
   options("h,help", "show help information");
-  options("c,create", "create learn data, this function " \
+  options(",svm", "resources/model/svm.xml", "the svm model file," \
+          " this option is used for '--tag'(required)" \
+          " and '--train'(save svm model to) functions");
+  // create
+  options(",create", "create learn data, this function " \
           "will intercept (--max) raw images (--in) and preprocess into (--out)");
   options("i,in", "", "where is the raw images");
   options("o,out", "", "where to put the preprocessed images");
   options("m,max", "5000", "how many learn data would you want to create");
-  options("t,tag", "tag learn data, this function " \
+  // tag
+  options(",tag", "tag learn data, this function " \
           "will find plate blocks in your images(--source) " \
           "as well as classify them into (--has) and (--no)");
   options("s,source", "", "where is your images to be classified");
   options(",has", "", "put plates in this folder");
   options(",no", "", "put images without plate in this folder");
-  options(",svm", "resources/model/svm.xml", "the svm model file");
+  // train
+  options(",train", "train given data, " \
+          "including the forward(has plate) and the inverse(no plate).");
+  options(",has-plate", "", "where is the forward data");
+  options(",no-plate", "", "where is the inverse data");
+  options(",divide",
+          "whether divide train data into two parts by --percentage or not");
+  options(",percentage", "0.7", "70% train data will be used for training," \
+          " others will be used for testing");
+  options(",not-train", "don't train again, run testing directly");
 
   options.add_subroutine("locate", "locate plates in an image")
           .make_usage("Usage:");
@@ -245,6 +260,10 @@ void command_line_handler(int argc, const char* argv[]) {
     }
 
     if (parser->has("create")) {
+      assert(parser->has("in"));
+      assert(parser->has("out"));
+      assert(parser->has("max"));
+
       auto in = parser->get("in")->val();
       auto out = parser->get("out")->val();
       auto max = parser->get("max")->as<int>();
@@ -252,6 +271,11 @@ void command_line_handler(int argc, const char* argv[]) {
     }
 
     if (parser->has("tag")) {
+      assert(parser->has("source"));
+      assert(parser->has("has"));
+      assert(parser->has("no"));
+      assert(parser->has("svm"));
+
       auto source = parser->get("source")->val();
       auto has_path = parser->get("has")->val();
       auto no_path = parser->get("no")->val();
@@ -262,6 +286,24 @@ void command_line_handler(int argc, const char* argv[]) {
       << "and classify the wrong images manually." << std::endl;
     }
 
+    if (parser->has("train")) {
+      assert(parser->has("has-plate"));
+      assert(parser->has("no-plate"));
+      assert(parser->has("percentage"));
+      assert(parser->has("svm"));
+
+      auto forward_data_path = parser->get("has-plate")->val();
+      auto inverse_data_path = parser->get("no-plate")->val();
+      bool divide = parser->has("divide");
+      auto percentage = parser->get("percentage")->as<float>();
+      auto svm_model = parser->get("svm")->val();
+      bool not_train = parser->has("not-train");
+
+      easypr::Svm svm(forward_data_path.c_str(), inverse_data_path.c_str());
+
+      svm.train(divide, percentage, !not_train, svm_model.c_str());
+    }
+
     return;
   } else if (subname == "locate") {
     if (parser->has("help") || argc <= 2) {
@@ -284,6 +326,9 @@ void command_line_handler(int argc, const char* argv[]) {
     }
 
     if (parser->has("file")) {
+      assert(parser->has("file"));
+      assert(parser->has("svm"));
+
       auto image = parser->get("file")->val();
       auto svm = parser->get("svm")->val();