text: ﻿//
  // Created by Jack Yu on 23/10/2017.
  //
  
  #include "../include/Pipeline.h"
  #include<fstream>
  #include<vector>
  
  
  
  using namespace std;
  
  
  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/SegmenationFree-Inception.prototxt", "../lpr/model/SegmenationFree-Inception.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/SegmenationFree-Inception.prototxt", "../lpr/model/SegmenationFree-Inception.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;
  
  }
  
  
  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);
  
  }
  
  
  int main()
  {
  	//    TEST_ACC();
  
  	//    TEST_CAM();
  	TEST_PIPELINE();
  	return 0;
  }
  