//
// 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/SegmenationFree-Inception.prototxt", "../lpr/model/SegmenationFree-Inception.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;
}