1)EasyPR开源项目地址：https://github.com/liuruoze/EasyPR
2)Ubuntu环境：
root@Slave1:~# uname -a
Linux Slave1 3.16.0-77-generic #99~14.04.1-Ubuntu SMP Tue Jun 28 19:17:10 UTC 2016 x86_64 x86_64 x86_64 GNU/Linux
GCC/G++安装：#gcc --versiongcc
(Ubuntu 4.8.4-2ubuntu1~14.04.3) 4.8.4
#apt-get install g++
#g++ --version
g++ (Ubuntu 4.8.4-2ubuntu1~14.04.3) 4.8.4
CMake安装：Ubunut默认cmake version 2.8.12.2
EasyPR要求cmake版本3.1.0+，需要升级
#add-apt-repository ppa:george-edison55/cmake-3.x
#apt-get update
#apt-get install cmake
#cmake --version
cmake version 3.2.2
3)Opencv安装：
http://opencv.org/downloads.html 下载opencv-3.1.0.zip放在/home目录下
#unzip opencv-3.1.0.zip
解压到/home目录下
#cd opencv-3.1.0
#mkdir release
#cd release
#cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local ..
#make
#make install
测试：
#mkdir /tmp/opencvdemo
#cd /tmp/opencvdemo
#vi DisplayImage.cpp
编辑：
#include <stdio.h>
#include <opencv2/opencv.hpp>
using namespace cv;
int main(int argc, char** argv )
{
if ( argc != 2 )
{
printf("usage: DisplayImage.out <Image_Path>\n");
return -1;
}
Mat image;
image = imread( argv[1], 1 );
if ( !image.data )
{
printf("No image data \n");
return -1;
}
namedWindow("Display Image", WINDOW_AUTOSIZE );
imshow("Display Image", image);
waitKey(0);
return 0;
}
#vi CMakeLists.txt
编辑：
cmake_minimum_required(VERSION 2.8)
project( DisplayImage )
find_package( OpenCV REQUIRED )
add_executable( DisplayImage DisplayImage.cpp )
target_link_libraries( DisplayImage ${OpenCV_LIBS} )
#cmake .
#make
#./DisplayImage uk722.jpg //要显示图片需要安装GTK+ 2.x版本
4)EasyPR安装：
https://github.com/liuruoze/EasyPR 下载EasyPR-master.zip
#unzip EasyPR-master.zip
解压到/home目录下
#cd EasyPR-master
#vi CMakeLists.txt
set(CMAKE_PREFIX_PATH ${CMAKE_PREFIX_PATH} "/usr/local/share/OpenCV")
修改为opencv的CMake配置文件路径
#cmake CMakeLists.txt
#make -j 12
生成demo_linux_amd64可执行程序，用于测试。
5)测试：
#cd EasyPR-master
#./demo_linux_amd64 ?
有5个命令
ann ann operation
judge determine whether an image block is the license plate
locate locate plates in an image
recognize plate recognition
svm svm operations
#./demo_linux_amd64 recognize -p resources/image/plate_recognize.jpg --svm resources/model/svm.xml --ann resources/model/ann.xml
可以训练自己的样本来提升识别。
参考：
