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更新vs工程到端到端模型

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iss
2019-07-02 19:47:23 +08:00
parent 33b6f6e346
commit 846d4c7a29
27 changed files with 628 additions and 300 deletions
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Prj-Win/Prj-Win/Prj-Win.vcxproj
+13 -10
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@@ -1,5 +1,5 @@
<?xml version="1.0" encoding="utf-8"?> <?xml version="1.0" encoding="utf-8"?>
<Project DefaultTargets="Build" ToolsVersion="14.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003"> <Project DefaultTargets="Build" ToolsVersion="15.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
<ItemGroup Label="ProjectConfigurations"> <ItemGroup Label="ProjectConfigurations">
<ProjectConfiguration Include="Debug|Win32"> <ProjectConfiguration Include="Debug|Win32">
<Configuration>Debug</Configuration> <Configuration>Debug</Configuration>
@@ -22,32 +22,32 @@
<ProjectGuid>{69FAD143-D7C9-4804-A186-90254BD80549}</ProjectGuid> <ProjectGuid>{69FAD143-D7C9-4804-A186-90254BD80549}</ProjectGuid>
<Keyword>Win32Proj</Keyword> <Keyword>Win32Proj</Keyword>
<RootNamespace>PrjWin</RootNamespace> <RootNamespace>PrjWin</RootNamespace>
<WindowsTargetPlatformVersion>8.1</WindowsTargetPlatformVersion> <WindowsTargetPlatformVersion>10.0.17763.0</WindowsTargetPlatformVersion>
</PropertyGroup> </PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.Default.props" /> <Import Project="$(VCTargetsPath)\Microsoft.Cpp.Default.props" />
<PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'" Label="Configuration"> <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'" Label="Configuration">
<ConfigurationType>Application</ConfigurationType> <ConfigurationType>Application</ConfigurationType>
<UseDebugLibraries>true</UseDebugLibraries> <UseDebugLibraries>true</UseDebugLibraries>
<PlatformToolset>v140</PlatformToolset> <PlatformToolset>v141</PlatformToolset>
<CharacterSet>Unicode</CharacterSet> <CharacterSet>Unicode</CharacterSet>
</PropertyGroup> </PropertyGroup>
<PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'" Label="Configuration"> <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'" Label="Configuration">
<ConfigurationType>Application</ConfigurationType> <ConfigurationType>Application</ConfigurationType>
<UseDebugLibraries>false</UseDebugLibraries> <UseDebugLibraries>false</UseDebugLibraries>
<PlatformToolset>v140</PlatformToolset> <PlatformToolset>v141</PlatformToolset>
<WholeProgramOptimization>true</WholeProgramOptimization> <WholeProgramOptimization>true</WholeProgramOptimization>
<CharacterSet>Unicode</CharacterSet> <CharacterSet>Unicode</CharacterSet>
</PropertyGroup> </PropertyGroup>
<PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'" Label="Configuration"> <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'" Label="Configuration">
<ConfigurationType>Application</ConfigurationType> <ConfigurationType>Application</ConfigurationType>
<UseDebugLibraries>true</UseDebugLibraries> <UseDebugLibraries>true</UseDebugLibraries>
<PlatformToolset>v140</PlatformToolset> <PlatformToolset>v141</PlatformToolset>
<CharacterSet>Unicode</CharacterSet> <CharacterSet>Unicode</CharacterSet>
</PropertyGroup> </PropertyGroup>
<PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'" Label="Configuration"> <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'" Label="Configuration">
<ConfigurationType>Application</ConfigurationType> <ConfigurationType>Application</ConfigurationType>
<UseDebugLibraries>false</UseDebugLibraries> <UseDebugLibraries>false</UseDebugLibraries>
<PlatformToolset>v140</PlatformToolset> <PlatformToolset>v141</PlatformToolset>
<WholeProgramOptimization>true</WholeProgramOptimization> <WholeProgramOptimization>true</WholeProgramOptimization>
<CharacterSet>Unicode</CharacterSet> <CharacterSet>Unicode</CharacterSet>
</PropertyGroup> </PropertyGroup>
@@ -76,9 +76,9 @@
</PropertyGroup> </PropertyGroup>
<PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'"> <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'">
<LinkIncremental>true</LinkIncremental> <LinkIncremental>true</LinkIncremental>
<IncludePath>D:\Prj-Win\lpr\include;D:\opencv\build\include\opencv2;D:\opencv\build\include\opencv;D:\opencv\build\include;$(IncludePath)</IncludePath> <IncludePath>D:\Prj-Win\lpr\include;D:\opencv\build\include;D:\opencv\build\include\opencv2;$(IncludePath)</IncludePath>
<LibraryPath>D:\opencv\build\x64\vc14\lib;$(LibraryPath)</LibraryPath> <LibraryPath>D:\opencv\build\x64\vc15\lib;$(LibraryPath)</LibraryPath>
<OutDir>$(SolutionDir)Build</OutDir> <OutDir>$(SolutionDir)Build\</OutDir>
</PropertyGroup> </PropertyGroup>
<PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'"> <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">
<LinkIncremental>false</LinkIncremental> <LinkIncremental>false</LinkIncremental>
@@ -112,7 +112,7 @@
<Link> <Link>
<SubSystem>Console</SubSystem> <SubSystem>Console</SubSystem>
<GenerateDebugInformation>true</GenerateDebugInformation> <GenerateDebugInformation>true</GenerateDebugInformation>
<AdditionalDependencies>opencv_world330d.lib;%(AdditionalDependencies)</AdditionalDependencies> <AdditionalDependencies>opencv_world400d.lib;opencv_world400.lib;%(AdditionalDependencies)</AdditionalDependencies>
</Link> </Link>
</ItemDefinitionGroup> </ItemDefinitionGroup>
<ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'"> <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">
@@ -161,15 +161,18 @@
<ClInclude Include="..\lpr\include\PlateInfo.h" /> <ClInclude Include="..\lpr\include\PlateInfo.h" />
<ClInclude Include="..\lpr\include\PlateSegmentation.h" /> <ClInclude Include="..\lpr\include\PlateSegmentation.h" />
<ClInclude Include="..\lpr\include\Recognizer.h" /> <ClInclude Include="..\lpr\include\Recognizer.h" />
<ClInclude Include="..\lpr\include\SegmentationFreeRecognizer.h" />
<ClInclude Include="..\lpr\src\util.h" /> <ClInclude Include="..\lpr\src\util.h" />
</ItemGroup> </ItemGroup>
<ItemGroup> <ItemGroup>
<ClCompile Include="..\lpr\src\CNNRecognizer.cpp" /> <ClCompile Include="..\lpr\src\CNNRecognizer.cpp" />
<ClCompile Include="..\lpr\src\FastDeskew.cpp" /> <ClCompile Include="..\lpr\src\FastDeskew.cpp" />
<ClCompile Include="..\lpr\src\FineMapping.cpp" /> <ClCompile Include="..\lpr\src\FineMapping.cpp" />
<ClCompile Include="..\lpr\src\Pipeline.cpp" />
<ClCompile Include="..\lpr\src\PlateDetection.cpp" /> <ClCompile Include="..\lpr\src\PlateDetection.cpp" />
<ClCompile Include="..\lpr\src\PlateSegmentation.cpp" /> <ClCompile Include="..\lpr\src\PlateSegmentation.cpp" />
<ClCompile Include="..\lpr\src\Recognizer.cpp" /> <ClCompile Include="..\lpr\src\Recognizer.cpp" />
<ClCompile Include="..\lpr\src\SegmentationFreeRecognizer.cpp" />
<ClCompile Include="..\lpr\tests\test_pipeline.cpp" /> <ClCompile Include="..\lpr\tests\test_pipeline.cpp" />
</ItemGroup> </ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" /> <Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
Prj-Win/Prj-Win/Prj-Win.vcxproj.filters
+9
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@@ -48,6 +48,9 @@
<ClInclude Include="..\lpr\src\util.h"> <ClInclude Include="..\lpr\src\util.h">
<Filter>源文件</Filter> <Filter>源文件</Filter>
</ClInclude> </ClInclude>
<ClInclude Include="..\lpr\include\SegmentationFreeRecognizer.h">
<Filter>头文件</Filter>
</ClInclude>
</ItemGroup> </ItemGroup>
<ItemGroup> <ItemGroup>
<ClCompile Include="..\lpr\src\CNNRecognizer.cpp"> <ClCompile Include="..\lpr\src\CNNRecognizer.cpp">
@@ -71,5 +74,11 @@
<ClCompile Include="..\lpr\tests\test_pipeline.cpp"> <ClCompile Include="..\lpr\tests\test_pipeline.cpp">
<Filter>源文件\test</Filter> <Filter>源文件\test</Filter>
</ClCompile> </ClCompile>
<ClCompile Include="..\lpr\src\Pipeline.cpp">
<Filter>源文件</Filter>
</ClCompile>
<ClCompile Include="..\lpr\src\SegmentationFreeRecognizer.cpp">
<Filter>源文件</Filter>
</ClCompile>
</ItemGroup> </ItemGroup>
</Project> </Project>
Prj-Win/lpr/include/CNNRecognizer.h
+1 -1
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@@ -1,5 +1,5 @@
// //
// Created by 庾金科 on 21/10/2017. // Created by Jack Yu on 21/10/2017.
// //
#ifndef SWIFTPR_CNNRECOGNIZER_H #ifndef SWIFTPR_CNNRECOGNIZER_H
Prj-Win/lpr/include/Pipeline.h
+28 -53
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@@ -1,5 +1,5 @@
// //
// Created by �׽�� on 22/10/2017. // Created by 庾金科 on 22/10/2017.
// //
#ifndef SWIFTPR_PIPLINE_H #ifndef SWIFTPR_PIPLINE_H
@@ -12,68 +12,43 @@
#include "FastDeskew.h" #include "FastDeskew.h"
#include "FineMapping.h" #include "FineMapping.h"
#include "Recognizer.h" #include "Recognizer.h"
#include "SegmentationFreeRecognizer.h"
namespace pr{ 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{ class PipelinePR{
public: public:
GeneralRecognizer *generalRecognizer; GeneralRecognizer *generalRecognizer;
PlateDetection *plateDetection; PlateDetection *plateDetection;
PlateSegmentation *plateSegmentation; PlateSegmentation *plateSegmentation;
FineMapping *fineMapping; FineMapping *fineMapping;
PipelinePR(std::string detector_filename, SegmentationFreeRecognizer *segmentationFreeRecognizer;
std::string finemapping_prototxt, std::string finemapping_caffemodel,
std::string segmentation_prototxt, std::string segmentation_caffemodel,
std::string charRecognization_proto, std::string charRecognization_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);
}
~PipelinePR() { PipelinePR(std::string detector_filename,
std::string finemapping_prototxt,std::string finemapping_caffemodel,
delete plateDetection; std::string segmentation_prototxt,std::string segmentation_caffemodel,
delete fineMapping; std::string charRecognization_proto,std::string charRecognization_caffemodel,
delete plateSegmentation; std::string segmentationfree_proto,std::string segmentationfree_caffemodel
delete generalRecognizer; );
} ~PipelinePR();
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" };
std::vector<std::string> plateRes; std::vector<std::string> plateRes;
std::vector<PlateInfo> RunPiplineAsImage(cv::Mat plateImage) { std::vector<PlateInfo> RunPiplineAsImage(cv::Mat plateImage,int method);
std::vector<PlateInfo> results;
std::vector<pr::PlateInfo> plates;
plateDetection->plateDetectionRough(plateImage, plates);
for (pr::PlateInfo plateinfo : plates) {
cv::Mat image_finemapping = plateinfo.getPlateImage();
image_finemapping = fineMapping->FineMappingVertical(image_finemapping);
image_finemapping = pr::fastdeskew(image_finemapping, 5);
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);
results.push_back(plateinfo);
std::cout << plateinfo.getPlateName() << std::endl;
}
// for (auto str:results) {
// std::cout << str << std::endl;
// }
return results;
}
Prj-Win/lpr/include/PlateDetection.h
+1 -1
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@@ -6,7 +6,7 @@
#define SWIFTPR_PLATEDETECTION_H #define SWIFTPR_PLATEDETECTION_H
#include <opencv2/opencv.hpp> #include <opencv2/opencv.hpp>
#include "PlateInfo.h" #include <PlateInfo.h>
#include <vector> #include <vector>
namespace pr{ namespace pr{
class PlateDetection{ class PlateDetection{
Prj-Win/lpr/include/PlateInfo.h
+9 -10
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@@ -10,17 +10,14 @@ namespace pr {
typedef std::vector<cv::Mat> Character; typedef std::vector<cv::Mat> Character;
enum PlateColor { BLUE, YELLOW, WHITE, GREEN, BLACK,UNKNOWN}; enum PlateColor { BLUE, YELLOW, WHITE, GREEN, BLACK,UNKNOWN};
enum CharType {CHINESE,LETTER,LETTER_NUMS}; enum CharType {CHINESE,LETTER,LETTER_NUMS,INVALID};
class PlateInfo { class PlateInfo {
public: public:
std::vector<std::pair<CharType,cv::Mat>> plateChars; std::vector<std::pair<CharType,cv::Mat>> plateChars;
std::vector<std::pair<CharType,cv::Mat>> plateCoding; std::vector<std::pair<CharType,cv::Mat>> plateCoding;
float confidence = 0; float confidence = 0;
PlateInfo(const cv::Mat &plateData, std::string plateName, cv::Rect plateRect, PlateColor plateType) { PlateInfo(const cv::Mat &plateData, std::string plateName, cv::Rect plateRect, PlateColor plateType) {
licensePlate = plateData; licensePlate = plateData;
name = plateName; 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]; decode += mappingTable[std::max_element(prob+41,prob+65)- prob];
confidence+=*std::max_element(prob+41,prob+65); 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]; decode += mappingTable[std::max_element(prob+31,prob+65)- prob];
confidence+=*std::max_element(prob+31,prob+65); confidence+=*std::max_element(prob+31,prob+65);
// std::cout<<*std::max_element(prob+31,prob+65)<<std::endl; // std::cout<<*std::max_element(prob+31,prob+65)<<std::endl;
} }
else if(plate.first == INVALID)
{
decode+='*';
}
} }
name = decode; name = decode;
@@ -113,12 +114,10 @@ namespace pr {
return decode; return decode;
} }
private: private:
cv::Mat licensePlate; cv::Mat licensePlate;
cv::Rect ROI; cv::Rect ROI;
std::string name; std::string name ;
PlateColor Type; PlateColor Type;
}; };
} }
Prj-Win/lpr/include/PlateSegmentation.h
-4
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@@ -1,7 +1,3 @@
//
// Created by 庾金科 on 16/10/2017.
//
#ifndef SWIFTPR_PLATESEGMENTATION_H #ifndef SWIFTPR_PLATESEGMENTATION_H
#define SWIFTPR_PLATESEGMENTATION_H #define SWIFTPR_PLATESEGMENTATION_H
Prj-Win/lpr/include/Recognizer.h
+2
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@@ -13,7 +13,9 @@ namespace pr{
class GeneralRecognizer{ class GeneralRecognizer{
public: public:
virtual label recognizeCharacter(cv::Mat character) = 0; virtual label recognizeCharacter(cv::Mat character) = 0;
// virtual cv::Mat SegmentationFreeForSinglePlate(cv::Mat plate) = 0;
void SegmentBasedSequenceRecognition(PlateInfo &plateinfo); void SegmentBasedSequenceRecognition(PlateInfo &plateinfo);
void SegmentationFreeSequenceRecognition(PlateInfo &plateInfo);
}; };
Prj-Win/lpr/include/SegmentationFreeRecognizer.h
+28
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@@ -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-Win/lpr/include/niBlackThreshold.h
+5 -3
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@@ -62,8 +62,9 @@ void niBlackThreshold( InputArray _src, OutputArray _dst, double maxValue,
thresh = mean + static_cast<float>(k) * sqrtVarianceMeanSum; thresh = mean + static_cast<float>(k) * sqrtVarianceMeanSum;
break; break;
default: default:
CV_Error( CV_StsBadArg, "Unknown binarization method" ); // CV_Error( CV_StsBadArg, "Unknown binarization method" );
break; CV_Error(-5, "Unknown binarization method");
break;
} }
thresh.convertTo(thresh, src.depth()); thresh.convertTo(thresh, src.depth());
@@ -99,7 +100,8 @@ void niBlackThreshold( InputArray _src, OutputArray _dst, double maxValue,
src.copyTo(dst, mask); src.copyTo(dst, mask);
break; break;
default: default:
CV_Error( CV_StsBadArg, "Unknown threshold type" ); // CV_Error( CV_StsBadArg, "Unknown threshold type" );
CV_Error(-5, "Unknown threshold type");
break; break;
} }
} }
Prj-Win/lpr/model/README.md
+2 -2
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@@ -10,8 +10,8 @@ HorizonalFinemapping.caffemodel
HorizonalFinemapping.prototxt HorizonalFinemapping.prototxt
Segmentation.caffemodel SegmentationFree.caffemodel
Segmentation.prototxt SegmentationFree.prototxt
放置在该目录 放置在该目录
Prj-Win/lpr/res/test.jpg
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Prj-Win/lpr/src/CNNRecognizer.cpp
+1 -1
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@@ -1,5 +1,5 @@
// //
// Created by 庾金科 on 21/10/2017. // Created by Jack Yu on 21/10/2017.
// //
#include "../include/CNNRecognizer.h" #include "../include/CNNRecognizer.h"
Prj-Win/lpr/src/FastDeskew.cpp
+4 -29
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@@ -1,15 +1,13 @@
// //
// Created by 庾金科 on 02/10/2017. // Created by Jack Yu on 02/10/2017.
// //
#include "FastDeskew.h" #include <../include/FastDeskew.h>
namespace pr{ namespace pr{
const int ANGLE_MIN = 30 ;
const int ANGLE_MIN = 30 ;
const int ANGLE_MAX = 150 ; const int ANGLE_MAX = 150 ;
const int PLATE_H = 36; const int PLATE_H = 36;
const int PLATE_W = 136; const int PLATE_W = 136;
@@ -51,59 +49,38 @@ namespace pr{
cv::Mat correctPlateImage(cv::Mat skewPlate,float angle,float maxAngle) cv::Mat correctPlateImage(cv::Mat skewPlate,float angle,float maxAngle)
{ {
cv::Mat dst; cv::Mat dst;
cv::Size size_o(skewPlate.cols,skewPlate.rows); cv::Size size_o(skewPlate.cols,skewPlate.rows);
int extend_padding = 0; int extend_padding = 0;
// if(angle<0) extend_padding = static_cast<int>(skewPlate.rows*tan(cv::abs(angle)/180* 3.14) );
extend_padding = static_cast<int>(skewPlate.rows*tan(cv::abs(angle)/180* 3.14) );
// else
// extend_padding = static_cast<int>(skewPlate.rows/tan(cv::abs(angle)/180* 3.14) );
// std::cout<<"extend:"<<extend_padding<<std::endl;
cv::Size size(skewPlate.cols + extend_padding ,skewPlate.rows); cv::Size size(skewPlate.cols + extend_padding ,skewPlate.rows);
float interval = abs(sin((angle /180) * 3.14)* skewPlate.rows); float interval = abs(sin((angle /180) * 3.14)* skewPlate.rows);
// std::cout<<interval<<std::endl;
cv::Point2f pts1[4] = {cv::Point2f(0,0),cv::Point2f(0,size_o.height),cv::Point2f(size_o.width,0),cv::Point2f(size_o.width,size_o.height)}; cv::Point2f pts1[4] = {cv::Point2f(0,0),cv::Point2f(0,size_o.height),cv::Point2f(size_o.width,0),cv::Point2f(size_o.width,size_o.height)};
if(angle>0) { if(angle>0) {
cv::Point2f pts2[4] = {cv::Point2f(interval, 0), cv::Point2f(0, size_o.height), cv::Point2f pts2[4] = {cv::Point2f(interval, 0), cv::Point2f(0, size_o.height),
cv::Point2f(size_o.width, 0), cv::Point2f(size_o.width - interval, size_o.height)}; cv::Point2f(size_o.width, 0), cv::Point2f(size_o.width - interval, size_o.height)};
cv::Mat M = cv::getPerspectiveTransform(pts1,pts2); cv::Mat M = cv::getPerspectiveTransform(pts1,pts2);
cv::warpPerspective(skewPlate,dst,M,size); cv::warpPerspective(skewPlate,dst,M,size);
} }
else { else {
cv::Point2f pts2[4] = {cv::Point2f(0, 0), cv::Point2f(interval, size_o.height), cv::Point2f(size_o.width-interval, 0), cv::Point2f pts2[4] = {cv::Point2f(0, 0), cv::Point2f(interval, size_o.height), cv::Point2f(size_o.width-interval, 0),
cv::Point2f(size_o.width, size_o.height)}; cv::Point2f(size_o.width, size_o.height)};
cv::Mat M = cv::getPerspectiveTransform(pts1,pts2); cv::Mat M = cv::getPerspectiveTransform(pts1,pts2);
cv::warpPerspective(skewPlate,dst,M,size,cv::INTER_CUBIC); cv::warpPerspective(skewPlate,dst,M,size,cv::INTER_CUBIC);
} }
return dst; return dst;
} }
cv::Mat fastdeskew(cv::Mat skewImage,int blockSize){ cv::Mat fastdeskew(cv::Mat skewImage,int blockSize){
const int FILTER_WINDOWS_SIZE = 5; const int FILTER_WINDOWS_SIZE = 5;
std::vector<float> angle_list(180); std::vector<float> angle_list(180);
memset(angle_list.data(),0,angle_list.size()*sizeof(int)); memset(angle_list.data(),0,angle_list.size()*sizeof(int));
cv::Mat bak; cv::Mat bak;
skewImage.copyTo(bak); skewImage.copyTo(bak);
if(skewImage.channels() == 3) if(skewImage.channels() == 3)
cv::cvtColor(skewImage,skewImage,cv::COLOR_RGB2GRAY); cv::cvtColor(skewImage,skewImage,cv::COLOR_RGB2GRAY);
if(skewImage.channels() == 1) if(skewImage.channels() == 1)
{ {
cv::Mat eigen; cv::Mat eigen;
cv::cornerEigenValsAndVecs(skewImage,eigen,blockSize,5); cv::cornerEigenValsAndVecs(skewImage,eigen,blockSize,5);
for( int j = 0; j < skewImage.rows; j+=blockSize ) for( int j = 0; j < skewImage.rows; j+=blockSize )
{ for( int i = 0; i < skewImage.cols; i+=blockSize ) { for( int i = 0; i < skewImage.cols; i+=blockSize )
@@ -112,12 +89,10 @@ namespace pr{
float y2 = eigen.at<cv::Vec6f>(j, i)[5]; float y2 = eigen.at<cv::Vec6f>(j, i)[5];
int angle_cell = angle(x2,y2); int angle_cell = angle(x2,y2);
angle_list[(angle_cell + 180)%180]+=1.0; angle_list[(angle_cell + 180)%180]+=1.0;
} }
} }
} }
std::vector<float> filtered = avgfilter(angle_list,5); std::vector<float> filtered = avgfilter(angle_list,5);
int maxPos = std::max_element(filtered.begin(),filtered.end()) - filtered.begin() + FILTER_WINDOWS_SIZE/2; int maxPos = std::max_element(filtered.begin(),filtered.end()) - filtered.begin() + FILTER_WINDOWS_SIZE/2;
if(maxPos>ANGLE_MAX) if(maxPos>ANGLE_MAX)
maxPos = (-maxPos+90+180)%180; maxPos = (-maxPos+90+180)%180;
Prj-Win/lpr/src/FineMapping.cpp
+5 -40
View File
@@ -1,12 +1,8 @@
//
// Created by 庾金科 on 22/09/2017.
//
#include "FineMapping.h" #include "FineMapping.h"
namespace pr{ 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; const int PADDING_UP_DOWN = 30;
void drawRect(cv::Mat image,cv::Rect rect) void drawRect(cv::Mat image,cv::Rect rect)
{ {
@@ -65,31 +61,21 @@ namespace pr{
} }
cv::Mat FineMapping::FineMappingVertical(cv::Mat InputProposal,int sliceNum,int upper,int lower,int windows_size){ cv::Mat FineMapping::FineMappingVertical(cv::Mat InputProposal,int sliceNum,int upper,int lower,int windows_size){
cv::Mat PreInputProposal; cv::Mat PreInputProposal;
cv::Mat proposal; cv::Mat proposal;
cv::resize(InputProposal,PreInputProposal,cv::Size(FINEMAPPING_W,FINEMAPPING_H)); cv::resize(InputProposal,PreInputProposal,cv::Size(FINEMAPPING_W,FINEMAPPING_H));
if(InputProposal.channels() == 3) if(InputProposal.channels() == 3)
cv::cvtColor(PreInputProposal,proposal,cv::COLOR_BGR2GRAY); cv::cvtColor(PreInputProposal,proposal,cv::COLOR_BGR2GRAY);
else else
PreInputProposal.copyTo(proposal); PreInputProposal.copyTo(proposal);
// proposal = PreInputProposal;
// this will improve some sen // this will improve some sen
cv::Mat kernal = cv::getStructuringElement(cv::MORPH_ELLIPSE,cv::Size(1,3)); cv::Mat kernal = cv::getStructuringElement(cv::MORPH_ELLIPSE,cv::Size(1,3));
// cv::erode(proposal,proposal,kernal);
float diff = static_cast<float>(upper-lower); float diff = static_cast<float>(upper-lower);
diff/=static_cast<float>(sliceNum-1); diff/=static_cast<float>(sliceNum-1);
cv::Mat binary_adaptive; cv::Mat binary_adaptive;
std::vector<cv::Point> line_upper; std::vector<cv::Point> line_upper;
std::vector<cv::Point> line_lower; std::vector<cv::Point> line_lower;
int contours_nums=0; int contours_nums=0;
for(int i = 0 ; i < sliceNum ; i++) for(int i = 0 ; i < sliceNum ; i++)
{ {
std::vector<std::vector<cv::Point> > contours; std::vector<std::vector<cv::Point> > contours;
@@ -106,7 +92,6 @@ namespace pr{
if (( lwRatio>0.7&&bdbox.width*bdbox.height>100 && bdboxAera<300) if (( lwRatio>0.7&&bdbox.width*bdbox.height>100 && bdboxAera<300)
|| (lwRatio>3.0 && bdboxAera<100 && bdboxAera>10)) || (lwRatio>3.0 && bdboxAera<100 && bdboxAera>10))
{ {
cv::Point p1(bdbox.x, bdbox.y); cv::Point p1(bdbox.x, bdbox.y);
cv::Point p2(bdbox.x + bdbox.width, bdbox.y + bdbox.height); cv::Point p2(bdbox.x + bdbox.width, bdbox.y + bdbox.height);
line_upper.push_back(p1); line_upper.push_back(p1);
@@ -115,9 +100,6 @@ namespace pr{
} }
} }
} }
std:: cout<<"contours_nums "<<contours_nums<<std::endl;
if(contours_nums<41) if(contours_nums<41)
{ {
cv::bitwise_not(InputProposal,InputProposal); cv::bitwise_not(InputProposal,InputProposal);
@@ -130,14 +112,11 @@ namespace pr{
else else
proposal = bak; proposal = bak;
int contours_nums=0; int contours_nums=0;
for(int i = 0 ; i < sliceNum ; i++) for(int i = 0 ; i < sliceNum ; i++)
{ {
std::vector<std::vector<cv::Point> > contours; std::vector<std::vector<cv::Point> > contours;
float k =lower + i*diff; float k =lower + i*diff;
cv::adaptiveThreshold(proposal,binary_adaptive,255,cv::ADAPTIVE_THRESH_MEAN_C,cv::THRESH_BINARY,windows_size,k); cv::adaptiveThreshold(proposal,binary_adaptive,255,cv::ADAPTIVE_THRESH_MEAN_C,cv::THRESH_BINARY,windows_size,k);
// cv::imshow("image",binary_adaptive);
// cv::waitKey(0);
cv::Mat draw; cv::Mat draw;
binary_adaptive.copyTo(draw); binary_adaptive.copyTo(draw);
cv::findContours(binary_adaptive,contours,cv::RETR_EXTERNAL,cv::CHAIN_APPROX_SIMPLE); cv::findContours(binary_adaptive,contours,cv::RETR_EXTERNAL,cv::CHAIN_APPROX_SIMPLE);
@@ -158,30 +137,19 @@ namespace pr{
} }
} }
} }
// std:: cout<<"contours_nums "<<contours_nums<<std::endl;
} }
cv::Mat rgb; 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);
//
std::pair<int, int> A; std::pair<int, int> A;
std::pair<int, int> B; 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 leftyB = A.first;
int rightyB = A.second; int rightyB = A.second;
int leftyA = B.first; int leftyA = B.first;
int rightyA = B.second; int rightyA = B.second;
int cols = rgb.cols; int cols = rgb.cols;
int rows = rgb.rows; int rows = rgb.rows;
// pts_map1 = np.float32([[cols - 1, rightyA], [0, leftyA],[cols - 1, rightyB], [0, leftyB]])
// pts_map2 = np.float32([[136,36],[0,36],[136,0],[0,0]])
// mat = cv2.getPerspectiveTransform(pts_map1,pts_map2)
// image = cv2.warpPerspective(rgb,mat,(136,36),flags=cv2.INTER_CUBIC)
std::vector<cv::Point2f> corners(4); std::vector<cv::Point2f> corners(4);
corners[0] = cv::Point2f(cols - 1, rightyA); corners[0] = cv::Point2f(cols - 1, rightyA);
corners[1] = cv::Point2f(0, leftyA); corners[1] = cv::Point2f(0, leftyA);
@@ -196,10 +164,7 @@ namespace pr{
cv::Mat quad = cv::Mat::zeros(36, 136, CV_8UC3); cv::Mat quad = cv::Mat::zeros(36, 136, CV_8UC3);
cv::warpPerspective(rgb, quad, transform, quad.size()); cv::warpPerspective(rgb, quad, transform, quad.size());
return quad; return quad;
} }
} }
Prj-Win/lpr/src/Pipeline.cpp
+85 -1
View File
@@ -1 +1,85 @@
//// //
// Created by Jack Yu on 23/10/2017.
//
#include "../include/Pipeline.h"
namespace pr {
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 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() {
delete plateDetection;
delete fineMapping;
delete plateSegmentation;
delete generalRecognizer;
delete segmentationFreeRecognizer;
}
std::vector<PlateInfo> PipelinePR:: RunPiplineAsImage(cv::Mat plateImage,int method) {
std::vector<PlateInfo> results;
std::vector<pr::PlateInfo> 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);
//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));
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(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));
plateinfo.setPlateImage(image_finemapping);
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);
}
return results;
}//namespace pr
}
Prj-Win/lpr/src/PlateDetection.cpp
+5 -34
View File
@@ -1,45 +1,24 @@
//
// Created by 庾金科 on 20/09/2017.
//
#include "../include/PlateDetection.h" #include "../include/PlateDetection.h"
#include "util.h" #include "util.h"
namespace pr{ namespace pr{
PlateDetection::PlateDetection(std::string filename_cascade){ PlateDetection::PlateDetection(std::string filename_cascade){
cascade.load(filename_cascade); cascade.load(filename_cascade);
}; };
void PlateDetection::plateDetectionRough(cv::Mat InputImage,std::vector<pr::PlateInfo> &plateInfos,int min_w,int max_w){ void PlateDetection::plateDetectionRough(cv::Mat InputImage,std::vector<pr::PlateInfo> &plateInfos,int min_w,int max_w){
cv::Mat processImage; cv::Mat processImage;
cv::cvtColor(InputImage,processImage,cv::COLOR_BGR2GRAY);
cv::cvtColor(InputImage,processImage,cv::COLOR_BGR2GRAY);
std::vector<cv::Rect> platesRegions; std::vector<cv::Rect> platesRegions;
// std::vector<PlateInfo> plates;
cv::Size minSize(min_w,min_w/4); cv::Size minSize(min_w,min_w/4);
cv::Size maxSize(max_w,max_w/4); cv::Size maxSize(max_w,max_w/4);
// cv::imshow("input",InputImage);
// cv::waitKey(0);
cascade.detectMultiScale( processImage, platesRegions, cascade.detectMultiScale( processImage, platesRegions,
1.1, 3, cv::CASCADE_SCALE_IMAGE,minSize,maxSize); 1.1, 3, cv::CASCADE_SCALE_IMAGE,minSize,maxSize);
for(auto plate:platesRegions) for(auto plate:platesRegions)
{ {
// extend rects int zeroadd_w = static_cast<int>(plate.width*0.30);
// x -= w * 0.14 int zeroadd_h = static_cast<int>(plate.height*2);
// w += w * 0.28 int zeroadd_x = static_cast<int>(plate.width*0.15);
// y -= h * 0.6 int zeroadd_y = static_cast<int>(plate.height*1);
// h += h * 1.1;
int zeroadd_w = static_cast<int>(plate.width*0.28);
int zeroadd_h = static_cast<int>(plate.height*1.2);
int zeroadd_x = static_cast<int>(plate.width*0.14);
int zeroadd_y = static_cast<int>(plate.height*0.6);
plate.x-=zeroadd_x; plate.x-=zeroadd_x;
plate.y-=zeroadd_y; plate.y-=zeroadd_y;
plate.height += zeroadd_h; plate.height += zeroadd_h;
@@ -50,12 +29,4 @@ namespace pr{
} }
} }
// std::vector<pr::PlateInfo> PlateDetection::plateDetectionRough(cv::Mat InputImage,cv::Rect roi,int min_w,int max_w){
// cv::Mat roi_region = util::cropFromImage(InputImage,roi);
// return plateDetectionRough(roi_region,min_w,max_w);
// }
}//namespace pr }//namespace pr
Prj-Win/lpr/src/PlateSegmentation.cpp
+18 -16
View File
@@ -1,5 +1,5 @@
// //
// Created by 庾金科 on 16/10/2017. // Created by Jack Yu on 16/10/2017.
// //
#include "../include/PlateSegmentation.h" #include "../include/PlateSegmentation.h"
@@ -94,7 +94,7 @@ namespace pr{
cv::Mat roi_thres; cv::Mat roi_thres;
// cv::threshold(roiImage,roi_thres,0,255,cv::THRESH_OTSU|cv::THRESH_BINARY); // 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; std::vector<std::vector<cv::Point>> contours;
cv::findContours(roi_thres,contours,cv::RETR_LIST,cv::CHAIN_APPROX_SIMPLE); cv::findContours(roi_thres,contours,cv::RETR_LIST,cv::CHAIN_APPROX_SIMPLE);
@@ -110,7 +110,7 @@ namespace pr{
cv::Rect bdbox = cv::boundingRect(contour); cv::Rect bdbox = cv::boundingRect(contour);
cv::Point center(bdbox.x+(bdbox.width>>1),bdbox.y + (bdbox.height>>1)); cv::Point center(bdbox.x+(bdbox.width>>1),bdbox.y + (bdbox.height>>1));
int dist = (center.x - boxCenter.x)*(center.x - boxCenter.x); int dist = (center.x - boxCenter.x)*(center.x - boxCenter.x);
if(dist<final_dist && bdbox.height > rows>>1) if(dist<final_dist && bdbox.height > rows>>1)
{ final_dist =dist; { final_dist =dist;
final_center = center; final_center = center;
final_bdbox = bdbox; final_bdbox = bdbox;
@@ -220,7 +220,7 @@ namespace pr{
int cp_list[7]; int cp_list[7];
float loss_selected = -1; float loss_selected = -10;
for(int start = 0 ; start < 20 ; start+=2) for(int start = 0 ; start < 20 ; start+=2)
for(int width = windowsWidth-5; width < windowsWidth+5 ; width++ ){ for(int width = windowsWidth-5; width < windowsWidth+5 ; width++ ){
@@ -246,13 +246,10 @@ namespace pr{
if(cp7_p5>=cols) if(cp7_p5>=cols)
continue; continue;
float loss = ch_prob[cp1_ch]+ // 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] // 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]); 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) if(loss>loss_selected)
{ {
@@ -284,15 +281,15 @@ namespace pr{
void PlateSegmentation::segmentPlateBySlidingWindows(cv::Mat &plateImage,int windowsWidth,int stride,cv::Mat &respones){ 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::Mat plateImageGray;
cv::cvtColor(plateImage,plateImageGray,cv::COLOR_BGR2GRAY); cv::cvtColor(plateImage,plateImageGray,cv::COLOR_BGR2GRAY);
int padding = plateImage.cols-136 ;
// int padding = 0 ;
int height = plateImage.rows - 1; 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::Rect roi(i,0,windowsWidth,height);
cv::Mat roiImage = plateImageGray(roi); cv::Mat roiImage = plateImageGray(roi);
@@ -348,6 +345,11 @@ namespace pr{
cv::Mat respones; //three response of every sub region from origin image . cv::Mat respones; //three response of every sub region from origin image .
segmentPlateBySlidingWindows(plateImage,DEFAULT_WIDTH,1,respones); segmentPlateBySlidingWindows(plateImage,DEFAULT_WIDTH,1,respones);
templateMatchFinding(respones,DEFAULT_WIDTH/stride,sections); templateMatchFinding(respones,DEFAULT_WIDTH/stride,sections);
for(int i = 0; i < sections.second.size() ; i++)
{
sections.second[i]*=stride;
}
// std::cout<<sections<<std::endl; // std::cout<<sections<<std::endl;
Prj-Win/lpr/src/Recognizer.cpp
+10 -13
View File
@@ -1,26 +1,23 @@
// //
// Created by 庾金科 on 22/10/2017. // Created by Jack Yu on 22/10/2017.
// //
#include "../include/Recognizer.h" #include "../include/Recognizer.h"
namespace pr{ namespace pr{
void GeneralRecognizer::SegmentBasedSequenceRecognition(PlateInfo &plateinfo){ void GeneralRecognizer::SegmentBasedSequenceRecognition(PlateInfo &plateinfo){
for(auto char_instance:plateinfo.plateChars) for(auto char_instance:plateinfo.plateChars)
{ {
std::pair<CharType,cv::Mat> res; std::pair<CharType,cv::Mat> res;
cv::Mat code_table= recognizeCharacter(char_instance.second); if(char_instance.second.rows*char_instance.second.cols>40) {
res.first = char_instance.first; label code_table = recognizeCharacter(char_instance.second);
code_table.copyTo(res.second); res.first = char_instance.first;
plateinfo.appendPlateCoding(res); code_table.copyTo(res.second);
plateinfo.appendPlateCoding(res);
} else{
res.first = INVALID;
plateinfo.appendPlateCoding(res);
}
} }
} }
} }
Prj-Win/lpr/src/SegmentationFreeRecognizer.cpp
+89
View File
@@ -0,0 +1,89 @@
//
// Created by Jack Yu 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::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 (seq_decode_res.size()>1 && 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]];
}
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);
}
}
Prj-Win/lpr/src/util.h
+4 -15
View File
@@ -1,20 +1,16 @@
// //
// Created by 庾金科 on 04/04/2017. // Created by Jack Yu on 04/04/2017.
// //
#include <opencv2/opencv.hpp> #include <opencv2/opencv.hpp>
namespace util{ namespace util{
template <class T> void swap ( T& a, T& b ) template <class T> void swap ( T& a, T& b )
{ {
T c(a); a=b; b=c; T c(a); a=b; b=c;
} }
template <class T> T min(T& a,T& b ) template <class T> T min(T& a,T& b )
{ {
return a>b?b:a; return a>b?b:a;
} }
cv::Mat cropFromImage(const cv::Mat &image,cv::Rect rect){ cv::Mat cropFromImage(const cv::Mat &image,cv::Rect rect){
@@ -57,23 +53,16 @@ namespace util{
int histSize = 256; int histSize = 256;
float range[] = {0,255}; float range[] = {0,255};
const float* histRange = {range}; const float* histRange = {range};
cv::calcHist( &hsv_planes[0], 1, 0, cv::Mat(), hist, 1, &histSize, &histRange,true, true); cv::calcHist( &hsv_planes[0], 1, 0, cv::Mat(), hist, 1, &histSize, &histRange,true, true);
return hist; return hist;
} }
float computeSimilir(const cv::Mat &A,const cv::Mat &B) float computeSimilir(const cv::Mat &A,const cv::Mat &B)
{ {
cv::Mat histA,histB; cv::Mat histA,histB;
histA = calcHist(A); histA = calcHist(A);
histB = calcHist(B); histB = calcHist(B);
return cv::compareHist(histA,histB,CV_COMP_CORREL); // return cv::compareHist(histA,histB,CV_COMP_CORREL);
return cv::compareHist(histA, histB, 0);
} }
}//namespace util }//namespace util
Prj-Win/lpr/tests/test_fastdeskew.cpp
+1 -1
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@@ -1,5 +1,5 @@
// //
// Created by 庾金科 on 02/10/2017. // Created by Jack Yu on 02/10/2017.
// //
Prj-Win/lpr/tests/test_finemapping.cpp
+1 -1
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@@ -1,5 +1,5 @@
// //
// Created by 庾金科 on 24/09/2017. // Created by Jack Yu on 24/09/2017.
// //
#include "FineMapping.h" #include "FineMapping.h"
Prj-Win/lpr/tests/test_pipeline.cpp
+212 -25
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@@ -1,42 +1,229 @@
// //
// Created by 庾金科 on 23/10/2017. // Created by Jack Yu on 23/10/2017.
// //
#include "../include/Pipeline.h" #include "../include/Pipeline.h"
using namespace pr; #include<fstream>
#include<vector>
void TEST_PIPELINE(){
pr::PipelinePR prc("../lpr/model/cascade.xml",
"../lpr/model/HorizonalFinemapping.prototxt","../lpr/model/HorizonalFinemapping.caffemodel",
"../lpr/model/Segmentation.prototxt","../lpr/model/Segmentation.caffemodel",
"../lpr/model/CharacterRecognization.prototxt","../lpr/model/CharacterRecognization.caffemodel"
);
cv::Mat image = cv::imread("../6.jpg"); using namespace std;
cv::imshow("image",image);
cv::waitKey(0);
std::vector<pr::PlateInfo> res = prc.RunPiplineAsImage(image);
float conf = 0 ;
for(auto st:res) {
if(st.confidence>0.1) {
std::cout << st.getPlateName() << " " << st.confidence << std::endl;
conf += st.confidence;
}
}
std::cout<<conf<<std::endl;
system("pause");
template<class T>
static unsigned int levenshtein_distance(const T &s1, const T &s2) {
const size_t len1 = s1.size(), len2 = s2.size();
std::vector<unsigned int> col(len2 + 1), prevCol(len2 + 1);
for (unsigned int i = 0; i < prevCol.size(); i++) prevCol[i] = i;
for (unsigned int i = 0; i < len1; i++) {
col[0] = i + 1;
for (unsigned int j = 0; j < len2; j++)
col[j + 1] = min(
min(prevCol[1 + j] + 1, col[j] + 1),
prevCol[j] + (s1[i] == s2[j] ? 0 : 1));
col.swap(prevCol);
}
return prevCol[len2];
}
void TEST_CAM()
{
cv::VideoCapture capture("test1.mp4");
cv::Mat frame;
pr::PipelinePR prc("../lpr/model/cascade.xml",
"../lpr/model/HorizonalFinemapping.prototxt", "../lpr/model/HorizonalFinemapping.caffemodel",
"../lpr/model/Segmentation.prototxt", "../lpr/model/Segmentation.caffemodel",
"../lpr/model/CharacterRecognization.prototxt", "../lpr/model/CharacterRecognization.caffemodel",
"../lpr/model/SegmentationFree.prototxt", "../lpr/model/SegmentationFree.caffemodel"
);
while (1) {
//读取下一帧
if (!capture.read(frame)) {
std::cout << "读取视频失败" << std::endl;
exit(1);
}
//
// cv::transpose(frame,frame);
// cv::flip(frame,frame,2);
// cv::resize(frame,frame,cv::Size(frame.cols/2,frame.rows/2));
std::vector<pr::PlateInfo> res = prc.RunPiplineAsImage(frame, pr::SEGMENTATION_FREE_METHOD);
for (auto st : res) {
if (st.confidence > 0.75) {
std::cout << st.getPlateName() << " " << st.confidence << std::endl;
cv::Rect region = st.getPlateRect();
cv::rectangle(frame, cv::Point(region.x, region.y), cv::Point(region.x + region.width, region.y + region.height), cv::Scalar(255, 255, 0), 2);
}
}
cv::imshow("image", frame);
cv::waitKey(1);
}
}
void TEST_ACC() {
pr::PipelinePR prc("../lpr/model/cascade.xml",
"../lpr/model/HorizonalFinemapping.prototxt", "../lpr/model/HorizonalFinemapping.caffemodel",
"../lpr/model/Segmentation.prototxt", "../lpr/model/Segmentation.caffemodel",
"../lpr/model/CharacterRecognization.prototxt", "../lpr/model/CharacterRecognization.caffemodel",
"../lpr/model/SegmentationFree.prototxt", "../lpr/model/SegmentationFree.caffemodel"
);
ifstream file;
string imagename;
int n = 0, correct = 0, j = 0, sum = 0;
char filename[] = "/Users/yujinke/Downloads/general_test/1.txt";
string pathh = "/Users/yujinke/Downloads/general_test/";
file.open(filename, ios::in);
while (!file.eof())
{
file >> imagename;
string imgpath = pathh + imagename;
std::cout << "------------------------------------------------" << endl;
cout << "图片名：" << imagename << endl;
cv::Mat image = cv::imread(imgpath);
// cv::imshow("image", image);
// cv::waitKey(0);
std::vector<pr::PlateInfo> res = prc.RunPiplineAsImage(image, pr::SEGMENTATION_FREE_METHOD);
float conf = 0;
vector<float> con;
vector<string> name;
for (auto st : res) {
if (st.confidence > 0.1) {
//std::cout << st.getPlateName() << " " << st.confidence << std::endl;
con.push_back(st.confidence);
name.push_back(st.getPlateName());
//conf += st.confidence;
}
else
cout << "no string" << endl;
}
// std::cout << conf << std::endl;
int num = con.size();
float max = 0;
string platestr, chpr, ch;
int diff = 0, dif = 0;
for (int i = 0; i < num; i++) {
if (con.at(i) > max)
{
max = con.at(i);
platestr = name.at(i);
}
}
// cout << "max:"<<max << endl;
cout << "string:" << platestr << endl;
chpr = platestr.substr(0, 2);
ch = imagename.substr(0, 2);
diff = levenshtein_distance(imagename, platestr);
dif = diff - 4;
cout << "差距:" << dif << endl;
sum += dif;
if (ch != chpr) n++;
if (diff == 0) correct++;
j++;
}
float cha = 1 - float(n) / float(j);
std::cout << "------------------------------------------------" << endl;
cout << "车牌总数:" << j << endl;
cout << "汉字识别准确率：" << cha << endl;
float chaccuracy = 1 - float(sum - n * 2) / float(j * 8);
cout << "字符识别准确率：" << chaccuracy << endl;
} }
int main()
void TEST_PIPELINE() {
pr::PipelinePR prc("../lpr/model/cascade.xml",
"../lpr/model/HorizonalFinemapping.prototxt", "../lpr/model/HorizonalFinemapping.caffemodel",
"../lpr/model/Segmentation.prototxt", "../lpr/model/Segmentation.caffemodel",
"../lpr/model/CharacterRecognization.prototxt", "../lpr/model/CharacterRecognization.caffemodel",
"../lpr/model/SegmentationFree.prototxt", "../lpr/model/SegmentationFree.caffemodel"
);
cv::Mat image = cv::imread("../lpr/res/test.jpg");
std::vector<pr::PlateInfo> res = prc.RunPiplineAsImage(image, pr::SEGMENTATION_FREE_METHOD);
for (auto st : res) {
if (st.confidence > 0.75) {
std::cout << st.getPlateName() << " " << st.confidence << std::endl;
cv::Rect region = st.getPlateRect();
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);
}
}
cv::imshow("image", image);
cv::waitKey(0);
}
/*void TEST_CAM()
{ {
TEST_PIPELINE(); cv::VideoCapture capture("test1.mp4");
cv::Mat frame;
pr::PipelinePR prc("../lpr/model/cascade.xml",
"../lpr/model/HorizonalFinemapping.prototxt", "../lpr/model/HorizonalFinemapping.caffemodel",
"../lpr/model/Segmentation.prototxt", "../lpr/model/Segmentation.caffemodel",
"../lpr/model/CharacterRecognization.prototxt", "../lpr/model/CharacterRecognization.caffemodel",
"../lpr/model/SegmentationFree.prototxt", "../lpr/model/SegmentationFree.caffemodel"
);
while (1) {
//读取下一帧
if (!capture.read(frame)) {
std::cout << "读取视频失败" << std::endl;
exit(1);
}
//
// cv::transpose(frame,frame);
// cv::flip(frame,frame,2);
// cv::resize(frame,frame,cv::Size(frame.cols/2,frame.rows/2));
return 0 ;
std::vector<pr::PlateInfo> res = prc.RunPiplineAsImage(frame, pr::SEGMENTATION_FREE_METHOD);
for (auto st : res) {
if (st.confidence > 0.75) {
std::cout << st.getPlateName() << " " << st.confidence << std::endl;
cv::Rect region = st.getPlateRect();
cv::rectangle(frame, cv::Point(region.x, region.y), cv::Point(region.x + region.width, region.y + region.height), cv::Scalar(255, 255, 0), 2);
}
}
cv::imshow("image", frame);
cv::waitKey(1);
}
}*/
int main()
{
// TEST_ACC();
// TEST_CAM();
TEST_PIPELINE();
return 0;
} }
Prj-Win/lpr/tests/test_recognization.cpp
+2 -1
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@@ -1,5 +1,5 @@
// //
// Created by 庾金科 on 23/10/2017. // Created by Jack Yu on 23/10/2017.
// //
#include "../include/CNNRecognizer.h" #include "../include/CNNRecognizer.h"
@@ -16,6 +16,7 @@ void getMaxClass(cv::Mat &probBlob, int *classId, double *classProb)
cv::Point classNumber; cv::Point classNumber;
cv::minMaxLoc(probBlob, NULL, classProb, NULL, &classNumber); cv::minMaxLoc(probBlob, NULL, classProb, NULL, &classNumber);
*classId = classNumber.x; *classId = classNumber.x;
} }
Prj-Win/lpr/tests/test_segmentation.cpp
+1 -1
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@@ -1,5 +1,5 @@
// //
// Created by 庾金科 on 16/10/2017. // Created by Jack Yu on 16/10/2017.
// //
Prj-Win/lpr/tests/test_segmentationFree.cpp
+54
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@@ -0,0 +1,54 @@
//
// Created by Jack Yu on 29/11/2017.
//
#include "../include/SegmentationFreeRecognizer.h"
#include "../include/Pipeline.h"
#include "../include/PlateInfo.h"
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;
}
int main()
{
cv::Mat image = cv::imread("res/cache/chars_segment.jpg");
// cv::transpose(image,image);
// cv::resize(image,image,cv::Size(160,40));
cv::imshow("xxx",image);
cv::waitKey(0);
pr::SegmentationFreeRecognizer recognizr("model/SegmenationFree-Inception.prototxt","model/ISegmenationFree-Inception.caffemodel");
std::pair<std::string,float> res = recognizr.SegmentationFreeForSinglePlate(image,pr::CH_PLATE_CODE);
std::cout<<res.first<<" "
<<res.second<<std::endl;
// decodeResults(plate,pr::CH_PLATE_CODE);
cv::imshow("image",image);
cv::waitKey(0);
return 0;
}