format
This commit is contained in:
jackyu1127
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//
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// Created by 庾金科 on 20/09/2017.
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//
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#include <../include/PlateDetection.h>
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void drawRect(cv::Mat image,cv::Rect rect)
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{
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cv::Point p1(rect.x,rect.y);
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cv::Point p2(rect.x+rect.width,rect.y+rect.height);
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cv::rectangle(image,p1,p2,cv::Scalar(0,255,0),1);
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}
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int main()
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{
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cv::Mat image = cv::imread("res/test1.jpg");
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pr::PlateDetection plateDetection("model/cascade.xml");
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std::vector<pr::PlateInfo> plates;
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plateDetection.plateDetectionRough(image,plates);
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for(pr::PlateInfo platex:plates)
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{
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drawRect(image,platex.getPlateRect());
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cv::imwrite("res/cache/test.png",platex.getPlateImage());
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cv::imshow("image",platex.getPlateImage());
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cv::waitKey(0);
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}
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cv::imshow("image",image);
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cv::waitKey(0);
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return 0 ;
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}
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//
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// Created by Jack Yu on 02/10/2017.
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//
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#include <../include/FastDeskew.h>
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void drawRect(cv::Mat image,cv::Rect rect)
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{
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cv::Point p1(rect.x,rect.y);
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cv::Point p2(rect.x+rect.width,rect.y+rect.height);
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cv::rectangle(image,p1,p2,cv::Scalar(0,255,0),1);
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}
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void TEST_DESKEW(){
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cv::Mat image = cv::imread("res/3.png",cv::IMREAD_GRAYSCALE);
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// cv::resize(image,image,cv::Size(136*2,36*2));
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cv::Mat deskewed = pr::fastdeskew(image,12);
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// cv::imwrite("./res/4.png",deskewed);
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// cv::Mat deskewed2 = pr::fastdeskew(deskewed,12);
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//
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cv::imshow("image",deskewed);
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cv::waitKey(0);
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}
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int main()
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{
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TEST_DESKEW();
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return 0 ;
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}
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@@ -0,0 +1,25 @@
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//
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// Created by Jack Yu on 24/09/2017.
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//
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#include "FineMapping.h"
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int main()
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{
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cv::Mat image = cv::imread("res/cache/test.png");
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cv::Mat image_finemapping = pr::FineMapping::FineMappingVertical(image);
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pr::FineMapping finemapper = pr::FineMapping("model/HorizonalFinemapping.prototxt","model/HorizonalFinemapping.caffemodel");
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image_finemapping = finemapper.FineMappingHorizon(image_finemapping,0,-3);
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cv::imwrite("res/cache/finemappingres.png",image_finemapping);
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cv::imshow("image",image_finemapping);
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cv::waitKey(0);
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return 0 ;
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}
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@@ -0,0 +1,199 @@
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//
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// Created by Jack Yu on 23/10/2017.
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//
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#include "../include/Pipeline.h"
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using namespace std;
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template<class T>
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static unsigned int levenshtein_distance(const T &s1, const T &s2) {
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const size_t len1 = s1.size(), len2 = s2.size();
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std::vector<unsigned int> col(len2 + 1), prevCol(len2 + 1);
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for (unsigned int i = 0; i < prevCol.size(); i++) prevCol[i] = i;
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for (unsigned int i = 0; i < len1; i++) {
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col[0] = i + 1;
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for (unsigned int j = 0; j < len2; j++)
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col[j + 1] = min(
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min(prevCol[1 + j] + 1, col[j] + 1),
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prevCol[j] + (s1[i] == s2[j] ? 0 : 1));
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col.swap(prevCol);
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}
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return prevCol[len2];
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}
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void TEST_ACC(){
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pr::PipelinePR prc("model/cascade.xml",
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"model/HorizonalFinemapping.prototxt","model/HorizonalFinemapping.caffemodel",
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"model/Segmentation.prototxt","model/Segmentation.caffemodel",
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"model/CharacterRecognization.prototxt","model/CharacterRecognization.caffemodel",
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"model/SegmenationFree-Inception.prototxt","model/SegmenationFree-Inception.caffemodel"
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);
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ifstream file;
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string imagename;
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int n = 0,correct = 0,j = 0,sum = 0;
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char filename[] = "/Users/yujinke/Downloads/general_test/1.txt";
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string pathh = "/Users/yujinke/Downloads/general_test/";
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file.open(filename, ios::in);
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while (!file.eof())
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{
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file >> imagename;
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string imgpath = pathh + imagename;
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std::cout << "------------------------------------------------" << endl;
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cout << "图片名：" << imagename << endl;
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cv::Mat image = cv::imread(imgpath);
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// cv::imshow("image", image);
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// cv::waitKey(0);
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std::vector<pr::PlateInfo> res = prc.RunPiplineAsImage(image,pr::SEGMENTATION_FREE_METHOD);
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float conf = 0;
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vector<float> con ;
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vector<string> name;
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for (auto st : res) {
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if (st.confidence > 0.1) {
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//std::cout << st.getPlateName() << " " << st.confidence << std::endl;
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con.push_back(st.confidence);
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name.push_back(st.getPlateName());
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//conf += st.confidence;
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}
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else
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cout << "no string" << endl;
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}
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// std::cout << conf << std::endl;
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int num = con.size();
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float max = 0;
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string platestr, chpr, ch;
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int diff = 0,dif = 0;
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for (int i = 0; i < num; i++) {
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if (con.at(i) > max)
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{
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max = con.at(i);
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platestr = name.at(i);
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}
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}
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// cout << "max:"<<max << endl;
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cout << "string:" << platestr << endl;
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chpr = platestr.substr(0, 2);
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ch = imagename.substr(0, 2);
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diff = levenshtein_distance(imagename, platestr);
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dif = diff - 4;
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cout << "差距:" <<dif << endl;
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sum += dif;
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if (ch != chpr) n++;
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if (diff == 0) correct++;
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j++;
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}
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float cha = 1 - float(n) / float(j);
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std::cout << "------------------------------------------------" << endl;
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cout << "车牌总数：" << j << endl;
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cout << "汉字识别准确率："<<cha << endl;
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float chaccuracy = 1 - float(sum - n * 2) /float(j * 8);
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cout << "字符识别准确率：" << chaccuracy << endl;
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}
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void TEST_PIPELINE(){
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pr::PipelinePR prc("model/cascade.xml",
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"model/HorizonalFinemapping.prototxt","model/HorizonalFinemapping.caffemodel",
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"model/Segmentation.prototxt","model/Segmentation.caffemodel",
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"model/CharacterRecognization.prototxt","model/CharacterRecognization.caffemodel",
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"model/SegmenationFree-Inception.prototxt","model/SegmenationFree-Inception.caffemodel"
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);
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cv::Mat image = cv::imread("/Users/yujinke/ClionProjects/cpp_ocr_demo/test.png");
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std::vector<pr::PlateInfo> res = prc.RunPiplineAsImage(image,pr::SEGMENTATION_FREE_METHOD);
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for(auto st:res) {
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if(st.confidence>0.75) {
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std::cout << st.getPlateName() << " " << st.confidence << std::endl;
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cv::Rect region = st.getPlateRect();
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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);
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}
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}
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cv::imshow("image",image);
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cv::waitKey(0);
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}
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void TEST_CAM()
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{
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cv::VideoCapture capture("test1.mp4");
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cv::Mat frame;
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pr::PipelinePR prc("model/cascade.xml",
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"model/HorizonalFinemapping.prototxt","model/HorizonalFinemapping.caffemodel",
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"model/Segmentation.prototxt","model/Segmentation.caffemodel",
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"model/CharacterRecognization.prototxt","model/CharacterRecognization.caffemodel",
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"model/SegmentationFree.prototxt","model/SegmentationFree.caffemodel"
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);
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while(1) {
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//读取下一帧
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if (!capture.read(frame)) {
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std::cout << "读取视频失败" << std::endl;
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exit(1);
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}
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//
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// cv::transpose(frame,frame);
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// cv::flip(frame,frame,2);
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// cv::resize(frame,frame,cv::Size(frame.cols/2,frame.rows/2));
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std::vector<pr::PlateInfo> res = prc.RunPiplineAsImage(frame,pr::SEGMENTATION_FREE_METHOD);
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for(auto st:res) {
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if(st.confidence>0.75) {
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std::cout << st.getPlateName() << " " << st.confidence << std::endl;
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cv::Rect region = st.getPlateRect();
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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);
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}
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}
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cv::imshow("image",frame);
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cv::waitKey(1);
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}
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}
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int main()
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{
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TEST_ACC();
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// TEST_CAM();
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// TEST_PIPELINE();
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return 0 ;
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}
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@@ -0,0 +1,54 @@
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//
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// Created by Jack Yu on 23/10/2017.
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//
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#include "../include/CNNRecognizer.h"
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std::vector<std::string> chars{"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"};
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#include <opencv2/dnn.hpp>
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using namespace cv::dnn;
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void getMaxClass(cv::Mat &probBlob, int *classId, double *classProb)
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{
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// cv::Mat probMat = probBlob.matRefConst().reshape(1, 1); //reshape the blob to 1x1000 matrix
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cv::Point classNumber;
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cv::minMaxLoc(probBlob, NULL, classProb, NULL, &classNumber);
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*classId = classNumber.x;
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}
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void TEST_RECOGNIZATION(){
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// pr::CNNRecognizer instance("model/CharacterRecognization.prototxt","model/CharacterRecognization.caffemodel");
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Net net = cv::dnn::readNetFromCaffe("model/CharacterRecognization.prototxt","model/CharacterRecognization.caffemodel");
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cv::Mat image = cv::imread("res/char1.png",cv::IMREAD_GRAYSCALE);
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cv::resize(image,image,cv::Size(14,30));
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cv::equalizeHist(image,image);
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cv::Mat inputBlob = cv::dnn::blobFromImage(image, 1/255.0, cv::Size(14,30), false);
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net.setInput(inputBlob,"data");
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cv::Mat res = net.forward();
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std::cout<<res<<std::endl;
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float *p = (float*)res.data;
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int maxid= 0;
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double prob = 0;
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getMaxClass(res,&maxid,&prob);
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std::cout<<chars[maxid]<<std::endl;
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};
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int main()
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{TEST_RECOGNIZATION();
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}
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@@ -0,0 +1,43 @@
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//
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// Created by Jack Yu on 16/10/2017.
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//
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#include "../include/PlateSegmentation.h"
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#include "../include/CNNRecognizer.h"
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#include "../include/Recognizer.h"
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std::vector<std::string> chars{"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"};
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void TEST_SLIDINGWINDOWS_EVAL(){
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cv::Mat demo = cv::imread("res/cache/finemappingres.png");
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cv::resize(demo,demo,cv::Size(136,36));
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cv::Mat respones;
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pr::PlateSegmentation plateSegmentation("model/Segmentation.prototxt","model/Segmentation.caffemodel");
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pr::PlateInfo plate;
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plate.setPlateImage(demo);
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std::vector<cv::Rect> rects;
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plateSegmentation.segmentPlatePipline(plate,1,rects);
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plateSegmentation.ExtractRegions(plate,rects);
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pr::GeneralRecognizer *recognizer = new pr::CNNRecognizer("model/CharacterRecognization.prototxt","model/CharacterRecognization.caffemodel");
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recognizer->SegmentBasedSequenceRecognition(plate);
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std::cout<<plate.decodePlateNormal(chars)<<std::endl;
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delete(recognizer);
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}
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int main(){
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TEST_SLIDINGWINDOWS_EVAL();
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return 0;
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}
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@@ -0,0 +1,54 @@
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//
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// Created by Jack Yu on 29/11/2017.
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//
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#include "../include/SegmentationFreeRecognizer.h"
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#include "../include/Pipeline.h"
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#include "../include/PlateInfo.h"
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std::string decodeResults(cv::Mat code_table,std::vector<std::string> mapping_table)
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{
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cv::MatSize mtsize = code_table.size;
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int sequencelength = mtsize[2];
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int labellength = mtsize[1];
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cv::transpose(code_table.reshape(1,1).reshape(1,labellength),code_table);
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std::string name = "";
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std::vector<int> seq(sequencelength);
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for(int i = 0 ; i < sequencelength; i++) {
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float *fstart = ((float *) (code_table.data) + i * labellength );
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int id = std::max_element(fstart,fstart+labellength) - fstart;
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seq[i] =id;
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}
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for(int i = 0 ; i< sequencelength ; i++)
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{
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if(seq[i]!=labellength-1 && (i==0 || seq[i]!=seq[i-1]))
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name+=mapping_table[seq[i]];
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}
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std::cout<<name;
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return name;
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}
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int main()
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{
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cv::Mat image = cv::imread("res/cache/chars_segment.jpg");
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// cv::transpose(image,image);
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// cv::resize(image,image,cv::Size(160,40));
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cv::imshow("xxx",image);
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cv::waitKey(0);
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pr::SegmentationFreeRecognizer recognizr("model/SegmenationFree-Inception.prototxt","model/ISegmenationFree-Inception.caffemodel");
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std::pair<std::string,float> res = recognizr.SegmentationFreeForSinglePlate(image,pr::CH_PLATE_CODE);
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std::cout<<res.first<<" "
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<<res.second<<std::endl;
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// decodeResults(plate,pr::CH_PLATE_CODE);
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cv::imshow("image",image);
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cv::waitKey(0);
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return 0;
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}
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