up e2e cpp

Prj-Android/app/src/main/cpp/CMakeLists.txt

@@ -1,37 +0,0 @@
-cmake_minimum_required(VERSION 3.6)
-project(SwiftPR)
-
-set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11")
-add_library( lib_opencv SHARED IMPORTED )
-
-
-find_library( # Sets the name of the path variable.
-              log-lib
-
-              # Specifies the name of the NDK library that
-              # you want CMake to locate.
-              log )
-
-
-include_directories(/Users/yujinke/Downloads/OpenCV-android-sdk-3.3/sdk/native/jni/include)
-include_directories(include)
-
-set_target_properties(lib_opencv PROPERTIES IMPORTED_LOCATION ${CMAKE_CURRENT_SOURCE_DIR}/../jniLibs/${ANDROID_ABI}/libopencv_java3.so)
-
-set(SRC_DETECTION src/PlateDetection.cpp  src/util.h include/PlateDetection.h)
-
-set(SRC_FINEMAPPING src/FineMapping.cpp )
-
-set(SRC_FASTDESKEW src/FastDeskew.cpp )
-
-set(SRC_SEGMENTATION src/PlateSegmentation.cpp )
-
-set(SRC_RECOGNIZE src/Recognizer.cpp src/CNNRecognizer.cpp)
-
-set(SRC_PIPLINE src/Pipeline.cpp)
-
-
-
-add_library(hyperlpr SHARED  ${SRC_DETECTION} ${SRC_FINEMAPPING} ${SRC_FASTDESKEW} ${SRC_SEGMENTATION} ${SRC_RECOGNIZE} ${SRC_PIPLINE} javaWarpper.cpp)
-
-target_link_libraries(hyperlpr lib_opencv ${log-lib})

Prj-Android/app/src/main/cpp/include/Pipeline.h

@@ -12,25 +12,40 @@
 #include "FastDeskew.h"
 #include "FineMapping.h"
 #include "Recognizer.h"
+#include "SegmentationFreeRecognizer.h"
 
 namespace pr{
+
+    const std::vector<std::string> CH_PLATE_CODE{"京", "沪", "津", "渝", "冀", "晋", "蒙", "辽", "吉", "黑", "苏", "浙", "皖", "闽", "赣", "鲁", "豫", "鄂", "湘", "粤", "桂",
+                                        "琼", "川", "贵", "云", "藏", "陕", "甘", "青", "宁", "新", "0", "1", "2", "3", "4", "5", "6", "7", "8", "9", "A",
+                                        "B", "C", "D", "E", "F", "G", "H", "J", "K", "L", "M", "N", "P", "Q", "R", "S", "T", "U", "V", "W", "X",
+                                        "Y", "Z","港","学","使","警","澳","挂","军","北","南","广","沈","兰","成","济","海","民","航","空"};
+
+
+
+    const int SEGMENTATION_FREE_METHOD = 0;
+    const int SEGMENTATION_BASED_METHOD = 1;
+
     class PipelinePR{
         public:
             GeneralRecognizer *generalRecognizer;
             PlateDetection *plateDetection;
             PlateSegmentation *plateSegmentation;
             FineMapping *fineMapping;
+            SegmentationFreeRecognizer *segmentationFreeRecognizer;
+
             PipelinePR(std::string detector_filename,
                        std::string finemapping_prototxt,std::string finemapping_caffemodel,
                        std::string segmentation_prototxt,std::string segmentation_caffemodel,
-                       std::string charRecognization_proto,std::string charRecognization_caffemodel
+                       std::string charRecognization_proto,std::string charRecognization_caffemodel,
+                       std::string segmentationfree_proto,std::string segmentationfree_caffemodel
                        );
             ~PipelinePR();
 
 
 
             std::vector<std::string> plateRes;
-            std::vector<PlateInfo> RunPiplineAsImage(cv::Mat plateImage);
+            std::vector<PlateInfo> RunPiplineAsImage(cv::Mat plateImage,int method);
 
 
 

Prj-Android/app/src/main/cpp/include/PlateInfo.h

@@ -10,17 +10,14 @@ namespace pr {
     typedef std::vector<cv::Mat> Character;
 
     enum PlateColor { BLUE, YELLOW, WHITE, GREEN, BLACK,UNKNOWN};
-    enum CharType {CHINESE,LETTER,LETTER_NUMS};
+    enum CharType {CHINESE,LETTER,LETTER_NUMS,INVALID};
 
 
     class PlateInfo {
         public:
             std::vector<std::pair<CharType,cv::Mat>> plateChars;
             std::vector<std::pair<CharType,cv::Mat>> plateCoding;
-
             float confidence = 0;
-
-
             PlateInfo(const cv::Mat &plateData, std::string plateName, cv::Rect plateRect, PlateColor plateType) {
                     licensePlate = plateData;
                     name = plateName;
@@ -93,17 +90,21 @@ namespace pr {
 
                     }
 
-                    if(plate.first == LETTER) {
+                    else if(plate.first == LETTER) {
                         decode += mappingTable[std::max_element(prob+41,prob+65)- prob];
                         confidence+=*std::max_element(prob+41,prob+65);
                     }
 
-                    if(plate.first == LETTER_NUMS) {
+                    else if(plate.first == LETTER_NUMS) {
                         decode += mappingTable[std::max_element(prob+31,prob+65)- prob];
                         confidence+=*std::max_element(prob+31,prob+65);
 //                        std::cout<<*std::max_element(prob+31,prob+65)<<std::endl;
 
                     }
+                    else if(plate.first == INVALID)
+                    {
+                        decode+='*';
+                    }
 
                 }
                 name = decode;
@@ -113,12 +114,10 @@ namespace pr {
                 return decode;
             }
 
-
-
     private:
         cv::Mat licensePlate;
         cv::Rect ROI;
-        std::string name;
+        std::string name ;
         PlateColor Type;
     };
 }

Prj-Android/app/src/main/cpp/include/Recognizer.h

@@ -13,7 +13,9 @@ namespace pr{
     class GeneralRecognizer{
         public:
             virtual label recognizeCharacter(cv::Mat character) = 0;
+//            virtual cv::Mat SegmentationFreeForSinglePlate(cv::Mat plate) = 0;
             void SegmentBasedSequenceRecognition(PlateInfo &plateinfo);
+            void SegmentationFreeSequenceRecognition(PlateInfo &plateInfo);
 
     };
 

Prj-Android/app/src/main/cpp/include/SegmentationFreeRecognizer.h

@@ -0,0 +1,28 @@
+//
+// Created by 庾金科 on 28/11/2017.
+//
+
+#ifndef SWIFTPR_SEGMENTATIONFREERECOGNIZER_H
+#define SWIFTPR_SEGMENTATIONFREERECOGNIZER_H
+
+#include "Recognizer.h"
+namespace pr{
+
+
+    class SegmentationFreeRecognizer{
+    public:
+        const int CHAR_INPUT_W = 14;
+        const int CHAR_INPUT_H = 30;
+        const int CHAR_LEN = 84;
+
+        SegmentationFreeRecognizer(std::string prototxt,std::string caffemodel);
+        std::pair<std::string,float> SegmentationFreeForSinglePlate(cv::Mat plate,std::vector<std::string> mapping_table);
+
+
+    private:
+        cv::dnn::Net net;
+
+    };
+
+}
+#endif //SWIFTPR_SEGMENTATIONFREERECOGNIZER_H

Prj-Android/app/src/main/cpp/src/FineMapping.cpp

@@ -5,8 +5,8 @@
 #include "FineMapping.h"
 namespace pr{
 
-    const int FINEMAPPING_H = 50;
+    const int FINEMAPPING_H = 60 ;
-    const int FINEMAPPING_W = 120;
+    const int FINEMAPPING_W = 140;
     const int PADDING_UP_DOWN = 30;
     void drawRect(cv::Mat image,cv::Rect rect)
     {
@@ -71,12 +71,10 @@ namespace pr{
         cv::Mat proposal;
 
         cv::resize(InputProposal,PreInputProposal,cv::Size(FINEMAPPING_W,FINEMAPPING_H));
-        int x = InputProposal.channels();
+//        cv::imwrite("res/cache/finemapping.jpg",PreInputProposal);
 
         if(InputProposal.channels() == 3)
             cv::cvtColor(PreInputProposal,proposal,cv::COLOR_BGR2GRAY);
-        else if(InputProposal.channels() == 4)
-            cv::cvtColor(PreInputProposal,proposal,cv::COLOR_BGRA2GRAY);
         else
             PreInputProposal.copyTo(proposal);
 
@@ -110,7 +108,6 @@ namespace pr{
                 if ((   lwRatio>0.7&&bdbox.width*bdbox.height>100 && bdboxAera<300)
                     || (lwRatio>3.0 && bdboxAera<100 && bdboxAera>10))
                 {
-
                     cv::Point p1(bdbox.x, bdbox.y);
                     cv::Point p2(bdbox.x + bdbox.width, bdbox.y + bdbox.height);
                     line_upper.push_back(p1);
@@ -120,7 +117,6 @@ namespace pr{
             }
         }
 
-        std:: cout<<"contours_nums "<<contours_nums<<std::endl;
 
         if(contours_nums<41)
         {
@@ -166,7 +162,7 @@ namespace pr{
         }
 
             cv::Mat rgb;
-            cv::copyMakeBorder(PreInputProposal, rgb, 30, 30, 0, 0, cv::BORDER_REPLICATE);
+            cv::copyMakeBorder(PreInputProposal, rgb, PADDING_UP_DOWN, PADDING_UP_DOWN, 0, 0, cv::BORDER_REPLICATE);
 //        cv::imshow("rgb",rgb);
 //        cv::waitKey(0);
 //
@@ -174,8 +170,8 @@ namespace pr{
 
             std::pair<int, int> A;
             std::pair<int, int> B;
-            A = FitLineRansac(line_upper, -2);
+            A = FitLineRansac(line_upper, -1);
-            B = FitLineRansac(line_lower, 2);
+            B = FitLineRansac(line_lower, 1);
             int leftyB = A.first;
             int rightyB = A.second;
             int leftyA = B.first;

Prj-Android/app/src/main/cpp/src/Pipeline.cpp

@@ -7,18 +7,20 @@
 
 namespace pr {
 
-    std::vector<std::string> chars_code{"京","沪","津","渝","冀","晋","蒙","辽","吉","黑","苏","浙","皖","闽","赣","鲁","豫","鄂","湘","粤","桂","琼","川","贵","云","藏","陕","甘","青","宁","新","0","1","2","3","4","5","6","7","8","9","A","B","C","D","E","F","G","H","J","K","L","M","N","P","Q","R","S","T","U","V","W","X","Y","Z"};
-
 
 
+    const int HorizontalPadding = 4;
     PipelinePR::PipelinePR(std::string detector_filename,
                            std::string finemapping_prototxt, std::string finemapping_caffemodel,
                            std::string segmentation_prototxt, std::string segmentation_caffemodel,
-                           std::string charRecognization_proto, std::string charRecognization_caffemodel) {
+                           std::string charRecognization_proto, std::string charRecognization_caffemodel,
+                           std::string segmentationfree_proto,std::string segmentationfree_caffemodel) {
         plateDetection = new PlateDetection(detector_filename);
         fineMapping = new FineMapping(finemapping_prototxt, finemapping_caffemodel);
         plateSegmentation = new PlateSegmentation(segmentation_prototxt, segmentation_caffemodel);
         generalRecognizer = new CNNRecognizer(charRecognization_proto, charRecognization_caffemodel);
+        segmentationFreeRecognizer =  new SegmentationFreeRecognizer(segmentationfree_proto,segmentationfree_caffemodel);
+
     }
 
     PipelinePR::~PipelinePR() {
@@ -27,42 +29,64 @@ namespace pr {
         delete fineMapping;
         delete plateSegmentation;
         delete generalRecognizer;
+        delete segmentationFreeRecognizer;
+
 
     }
 
-    std::vector<PlateInfo> PipelinePR:: RunPiplineAsImage(cv::Mat plateImage) {
+    std::vector<PlateInfo> PipelinePR:: RunPiplineAsImage(cv::Mat plateImage,int method) {
         std::vector<PlateInfo> results;
         std::vector<pr::PlateInfo> plates;
-        plateDetection->plateDetectionRough(plateImage,plates);
+        plateDetection->plateDetectionRough(plateImage,plates,36,700);
 
         for (pr::PlateInfo plateinfo:plates) {
 
             cv::Mat image_finemapping = plateinfo.getPlateImage();
-
             image_finemapping = fineMapping->FineMappingVertical(image_finemapping);
-
             image_finemapping = pr::fastdeskew(image_finemapping, 5);
-//
+
-//            cv::imshow("image_finemapping", image_finemapping);
+
+
+            //Segmentation-based
+
+            if(method==SEGMENTATION_BASED_METHOD)
+            {
+                image_finemapping = fineMapping->FineMappingHorizon(image_finemapping, 2, HorizontalPadding);
+                cv::resize(image_finemapping, image_finemapping, cv::Size(136+HorizontalPadding, 36));
+//            cv::imshow("image_finemapping",image_finemapping);
 //            cv::waitKey(0);
-
-            image_finemapping = fineMapping->FineMappingHorizon(image_finemapping, 2, 5);
-
-            cv::resize(image_finemapping, image_finemapping, cv::Size(136, 36));
                 plateinfo.setPlateImage(image_finemapping);
                 std::vector<cv::Rect> rects;
+
                 plateSegmentation->segmentPlatePipline(plateinfo, 1, rects);
                 plateSegmentation->ExtractRegions(plateinfo, rects);
-
                 cv::copyMakeBorder(image_finemapping, image_finemapping, 0, 0, 0, 20, cv::BORDER_REPLICATE);
-
                 plateinfo.setPlateImage(image_finemapping);
                 generalRecognizer->SegmentBasedSequenceRecognition(plateinfo);
-            plateinfo.decodePlateNormal(chars_code);
+                plateinfo.decodePlateNormal(pr::CH_PLATE_CODE);
+
+            }
+                //Segmentation-free
+            else if(method==SEGMENTATION_FREE_METHOD)
+            {
+
+                image_finemapping = fineMapping->FineMappingHorizon(image_finemapping, 4, HorizontalPadding+3);
+
+                cv::resize(image_finemapping, image_finemapping, cv::Size(136+HorizontalPadding, 36));
+//                cv::imwrite("./test.png",image_finemapping);
+//                cv::imshow("image_finemapping",image_finemapping);
+//                cv::waitKey(0);
+                plateinfo.setPlateImage(image_finemapping);
+//                std::vector<cv::Rect> rects;
+
+                std::pair<std::string,float> res = segmentationFreeRecognizer->SegmentationFreeForSinglePlate(plateinfo.getPlateImage(),pr::CH_PLATE_CODE);
+                plateinfo.confidence = res.second;
+                plateinfo.setPlateName(res.first);
+            }
+
+
+
             results.push_back(plateinfo);
-            std::cout << plateinfo.getPlateName() << std::endl;
-
-
         }
 
 //        for (auto str:results) {

Prj-Android/app/src/main/cpp/src/PlateDetection.cpp

@@ -36,10 +36,10 @@ namespace pr{
 //            w += w * 0.28
 //            y -= h * 0.6
 //            h += h * 1.1;
-            int zeroadd_w  = static_cast<int>(plate.width*0.28);
+            int zeroadd_w  = static_cast<int>(plate.width*0.30);
-            int zeroadd_h = static_cast<int>(plate.height*1.2);
+            int zeroadd_h = static_cast<int>(plate.height*2);
-            int zeroadd_x = static_cast<int>(plate.width*0.14);
+            int zeroadd_x = static_cast<int>(plate.width*0.15);
-            int zeroadd_y = static_cast<int>(plate.height*0.6);
+            int zeroadd_y = static_cast<int>(plate.height*1);
             plate.x-=zeroadd_x;
             plate.y-=zeroadd_y;
             plate.height += zeroadd_h;

Prj-Android/app/src/main/cpp/src/PlateSegmentation.cpp

@@ -94,7 +94,7 @@ namespace pr{
                 cv::Mat roi_thres;
 //                cv::threshold(roiImage,roi_thres,0,255,cv::THRESH_OTSU|cv::THRESH_BINARY);
 
-                niBlackThreshold(roiImage,roi_thres,255,cv::THRESH_BINARY,15,0.3,BINARIZATION_NIBLACK);
+                niBlackThreshold(roiImage,roi_thres,255,cv::THRESH_BINARY,15,0.27,BINARIZATION_NIBLACK);
 
                 std::vector<std::vector<cv::Point>> contours;
                 cv::findContours(roi_thres,contours,cv::RETR_LIST,cv::CHAIN_APPROX_SIMPLE);
@@ -220,7 +220,7 @@ namespace pr{
 
 
         int cp_list[7];
-        float loss_selected = -1;
+        float loss_selected = -10;
 
         for(int start = 0 ; start < 20 ; start+=2)
             for(int  width = windowsWidth-5; width < windowsWidth+5 ; width++ ){
@@ -248,14 +248,9 @@ namespace pr{
                         continue;
 //                    float loss = ch_prob[cp1_ch]+
 //                       engNum_prob[cp2_p0] +engNum_prob[cp3_p1]+engNum_prob[cp4_p2]+engNum_prob[cp5_p3]+engNum_prob[cp6_p4] +engNum_prob[cp7_p5]
-//                    + (false_prob[md2]+false_prob[md3]+false_prob[md4]+false_prob[md5]+false_prob[md5] + false_prob[md6]
+//                    + (false_prob[md2]+false_prob[md3]+false_prob[md4]+false_prob[md5]+false_prob[md5] + false_prob[md6]);
-//                                                                                                                                                                                          );
-
                     float loss = ch_prob[cp1_ch]*3 -(false_prob[cp3_p1]+false_prob[cp4_p2]+false_prob[cp5_p3]+false_prob[cp6_p4]+false_prob[cp7_p5]);
 
-
-
-
                     if(loss>loss_selected)
                     {
                         loss_selected = loss;
@@ -286,15 +281,15 @@ namespace pr{
     void PlateSegmentation::segmentPlateBySlidingWindows(cv::Mat &plateImage,int windowsWidth,int stride,cv::Mat &respones){
 
 
-        cv::resize(plateImage,plateImage,cv::Size(136,36));
+//        cv::resize(plateImage,plateImage,cv::Size(136,36));
 
         cv::Mat plateImageGray;
         cv::cvtColor(plateImage,plateImageGray,cv::COLOR_BGR2GRAY);
-
+        int padding  =  plateImage.cols-136 ;
+//        int padding  =  0 ;
         int height = plateImage.rows - 1;
-        int width = plateImage.cols - 1;
+        int width = plateImage.cols - 1 - padding;
-
+        for(int i = 0 ; i < width - windowsWidth +1 ; i +=stride)
-        for(int i = 0 ; i < plateImage.cols - windowsWidth +1 ; i +=stride)
         {
             cv::Rect roi(i,0,windowsWidth,height);
             cv::Mat roiImage = plateImageGray(roi);
@@ -350,6 +345,11 @@ namespace pr{
         cv::Mat respones; //three response of every sub region from origin image .
         segmentPlateBySlidingWindows(plateImage,DEFAULT_WIDTH,1,respones);
         templateMatchFinding(respones,DEFAULT_WIDTH/stride,sections);
+        for(int i = 0; i < sections.second.size() ; i++)
+        {
+            sections.second[i]*=stride;
+
+        }
 
 //        std::cout<<sections<<std::endl;
 

Prj-Android/app/src/main/cpp/src/Recognizer.cpp

@@ -6,17 +6,20 @@
 
 namespace pr{
     void GeneralRecognizer::SegmentBasedSequenceRecognition(PlateInfo &plateinfo){
-
-
         for(auto char_instance:plateinfo.plateChars)
         {
-
-
             std::pair<CharType,cv::Mat> res;
-            cv::Mat code_table= recognizeCharacter(char_instance.second);
+            if(char_instance.second.rows*char_instance.second.cols>40) {
+                label code_table = recognizeCharacter(char_instance.second);
                 res.first = char_instance.first;
                 code_table.copyTo(res.second);
                 plateinfo.appendPlateCoding(res);
+            } else{
+                res.first = INVALID;
+                plateinfo.appendPlateCoding(res);
+
+            }
+
 
         }
 

Prj-Android/app/src/main/cpp/src/SegmentationFreeRecognizer.cpp

@@ -0,0 +1,118 @@
+//
+// Created by 庾金科 on 28/11/2017.
+//
+#include "../include/SegmentationFreeRecognizer.h"
+
+namespace pr {
+    SegmentationFreeRecognizer::SegmentationFreeRecognizer(std::string prototxt, std::string caffemodel) {
+        net = cv::dnn::readNetFromCaffe(prototxt, caffemodel);
+    }
+
+
+    inline int judgeCharRange(int id)
+    {return id<31 || id>63;
+    }
+
+
+    std::pair<std::string,float> decodeResults(cv::Mat code_table,std::vector<std::string> mapping_table,float thres)
+    {
+//        cv::imshow("imagea",code_table);
+//        cv::waitKey(0);
+
+        cv::MatSize mtsize = code_table.size;
+        int sequencelength = mtsize[2];
+        int labellength = mtsize[1];
+        cv::transpose(code_table.reshape(1,1).reshape(1,labellength),code_table);
+        std::string name = "";
+
+
+        std::vector<int> seq(sequencelength);
+        std::vector<std::pair<int,float>> seq_decode_res;
+
+        for(int i = 0 ; i < sequencelength;  i++) {
+            float *fstart = ((float *) (code_table.data) + i * labellength );
+            int id = std::max_element(fstart,fstart+labellength) - fstart;
+            seq[i] =id;
+        }
+
+        float sum_confidence = 0;
+
+        int plate_lenghth  = 0 ;
+
+
+        for(int i = 0 ; i< sequencelength ; i++)
+        {
+            if(seq[i]!=labellength-1 && (i==0 || seq[i]!=seq[i-1]))
+            {
+                float *fstart = ((float *) (code_table.data) + i * labellength );
+                float confidence = *(fstart+seq[i]);
+                std::pair<int,float> pair_(seq[i],confidence);
+                seq_decode_res.push_back(pair_);
+//
+
+            }
+        }
+
+        int  i = 0;
+
+        if(judgeCharRange(seq_decode_res[0].first) && judgeCharRange(seq_decode_res[1].first))
+        {
+            i=2;
+            int c = seq_decode_res[0].second<seq_decode_res[1].second;
+            name+=mapping_table[seq_decode_res[c].first];
+            sum_confidence+=seq_decode_res[c].second;
+            plate_lenghth++;
+        }
+
+        for(; i < seq_decode_res.size();i++)
+        {
+            name+=mapping_table[seq_decode_res[i].first];
+            sum_confidence +=seq_decode_res[i].second;
+            plate_lenghth++;
+        }
+
+
+        std::pair<std::string,float> res;
+
+        res.second = sum_confidence/plate_lenghth;
+        res.first = name;
+        return res;
+
+    }
+
+    std::string decodeResults(cv::Mat code_table,std::vector<std::string> mapping_table)
+    {
+        cv::MatSize mtsize = code_table.size;
+        int sequencelength = mtsize[2];
+        int labellength = mtsize[1];
+        cv::transpose(code_table.reshape(1,1).reshape(1,labellength),code_table);
+        std::string name = "";
+        std::vector<int> seq(sequencelength);
+        for(int i = 0 ; i < sequencelength;  i++) {
+            float *fstart = ((float *) (code_table.data) + i * labellength );
+            int id = std::max_element(fstart,fstart+labellength) - fstart;
+            seq[i] =id;
+        }
+        for(int i = 0 ; i< sequencelength ; i++)
+        {
+            if(seq[i]!=labellength-1 && (i==0 || seq[i]!=seq[i-1]))
+                name+=mapping_table[seq[i]];
+        }
+
+        std::cout<<name;
+        return name;
+    }
+
+
+
+    std::pair<std::string,float> SegmentationFreeRecognizer::SegmentationFreeForSinglePlate(cv::Mat Image,std::vector<std::string> mapping_table) {
+        cv::transpose(Image,Image);
+        cv::Mat inputBlob = cv::dnn::blobFromImage(Image, 1 / 255.0, cv::Size(40,160));
+        net.setInput(inputBlob, "data");
+        cv::Mat char_prob_mat = net.forward();
+        return decodeResults(char_prob_mat,mapping_table,0.00);
+
+    }
+
+
+}

README.md

@@ -81,6 +81,43 @@ cmake ../
 sudo make -j 
 ```
 
+### CPP demo
+
+```cpp
+#include "../include/Pipeline.h"
+int main(){
+    pr::PipelinePR prc("model/cascade.xml",
+                      "model/HorizonalFinemapping.prototxt","model/HorizonalFinemapping.caffemodel",
+                      "model/Segmentation.prototxt","model/Segmentation.caffemodel",
+                      "model/CharacterRecognization.prototxt","model/CharacterRecognization.caffemodel",
+                       "model/SegmentationFree.prototxt","model/SegmentationFree.caffemodel"
+                    );
+  //定义模型文件
+
+    cv::Mat image = cv::imread("/Users/yujinke/ClionProjects/cpp_ocr_demo/test.png");
+    std::vector<pr::PlateInfo> res = prc.RunPiplineAsImage(image,pr::SEGMENTATION_FREE_METHOD);
+  //使用端到端模型模型进行识别 识别结果将会保存在res里面
+ 
+    for(auto st:res) {
+        if(st.confidence>0.75) {
+            std::cout << st.getPlateName() << " " << st.confidence << std::endl;
+          //输出识别结果 、识别置信度
+            cv::Rect region = st.getPlateRect();
+          //获取车牌位置
+ cv::rectangle(image,cv::Point(region.x,region.y),cv::Point(region.x+region.width,region.y+region.height),cv::Scalar(255,255,0),2);
+          //画出车牌位置
+          
+        }
+    }
+
+    cv::imshow("image",image);
+    cv::waitKey(0);
+    return 0 ;
+}
+```
+
+### 
+
 ### 可识别和待支持的车牌的类型
 
 - [x] 单行蓝牌
@@ -130,3 +167,4 @@ sudo make -j
 
 + HyperLPR讨论QQ群：673071218, 加前请备注HyperLPR交流。
 
+