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package com.yuxue.easypr.core;
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import java.util.Vector;
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import static org.bytedeco.javacpp.opencv_core.*;
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import static org.bytedeco.javacpp.opencv_imgproc.*;
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import com.yuxue.constant.Constant;
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import org.bytedeco.javacpp.opencv_imgcodecs;
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import org.bytedeco.javacpp.opencv_core.CvPoint2D32f;
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import org.bytedeco.javacpp.opencv_core.Mat;
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import org.bytedeco.javacpp.opencv_core.MatVector;
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import org.bytedeco.javacpp.opencv_core.Point;
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import org.bytedeco.javacpp.opencv_core.Point2f;
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import org.bytedeco.javacpp.opencv_core.RotatedRect;
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import org.bytedeco.javacpp.opencv_core.Scalar;
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import org.bytedeco.javacpp.opencv_core.Size;
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/**
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* 车牌定位
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* @author yuxue
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* @date 2020-04-24 15:33
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*/
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public class PlateLocate {
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// PlateLocate所用常量
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public static final int DEFAULT_GAUSSIANBLUR_SIZE = 5;
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public static final int SOBEL_SCALE = 1;
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public static final int SOBEL_DELTA = 0;
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public static final int SOBEL_DDEPTH = CV_16S;
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public static final int SOBEL_X_WEIGHT = 1;
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public static final int SOBEL_Y_WEIGHT = 0;
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public static final int DEFAULT_MORPH_SIZE_WIDTH = 17;
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public static final int DEFAULT_MORPH_SIZE_HEIGHT = 3;
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// showResultMat所用常量
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public static final int WIDTH = 136;
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public static final int HEIGHT = 36;
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public static final int TYPE = CV_8UC3;
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// verifySize所用常量
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public static final int DEFAULT_VERIFY_MIN = 3;
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public static final int DEFAULT_VERIFY_MAX = 20;
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final float DEFAULT_ERROR = 0.6f;
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final float DEFAULT_ASPECT = 3.75f;
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// 角度判断所用常量
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public static final int DEFAULT_ANGLE = 30;
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// 高斯模糊所用变量
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protected int gaussianBlurSize = DEFAULT_GAUSSIANBLUR_SIZE;
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// 连接操作所用变量
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protected int morphSizeWidth = DEFAULT_MORPH_SIZE_WIDTH;
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protected int morphSizeHeight = DEFAULT_MORPH_SIZE_HEIGHT;
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// verifySize所用变量
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protected float error = DEFAULT_ERROR;
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protected float aspect = DEFAULT_ASPECT;
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protected int verifyMin = DEFAULT_VERIFY_MIN;
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protected int verifyMax = DEFAULT_VERIFY_MAX;
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// 角度判断所用变量
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protected int angle = DEFAULT_ANGLE;
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// 是否开启调试模式，0关闭，非0开启
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protected boolean debug = true;
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// 开启调试模式之后，切图文件保存路径
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protected String tempPath = Constant.DEFAULT_TEMP_DIR + System.currentTimeMillis() + "/";
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/**
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* 生活模式与工业模式切换
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* @param islifemode
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* 如果为真，则设置各项参数为定位生活场景照片（如百度图片）的参数，否则恢复默认值。
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*
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*/
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public void setLifemode(boolean islifemode) {
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if (islifemode) {
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setGaussianBlurSize(5);
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setMorphSizeWidth(9);
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setMorphSizeHeight(3);
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setVerifyError(0.9f);
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setVerifyAspect(4);
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setVerifyMin(1);
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setVerifyMax(30);
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} else {
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setGaussianBlurSize(DEFAULT_GAUSSIANBLUR_SIZE);
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setMorphSizeWidth(DEFAULT_MORPH_SIZE_WIDTH);
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setMorphSizeHeight(DEFAULT_MORPH_SIZE_HEIGHT);
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setVerifyError(DEFAULT_ERROR);
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setVerifyAspect(DEFAULT_ASPECT);
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setVerifyMin(DEFAULT_VERIFY_MIN);
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setVerifyMax(DEFAULT_VERIFY_MAX);
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}
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}
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/**
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* 定位车牌图像
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* @param src 原始图像
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* @return 一个Mat的向量，存储所有抓取到的图像
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*/
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public Vector<Mat> plateLocate(Mat src) {
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Vector<Mat> resultVec = new Vector<Mat>();
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Mat src_blur = new Mat();
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Mat src_gray = new Mat();
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Mat grad = new Mat();
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int scale = SOBEL_SCALE;
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int delta = SOBEL_DELTA;
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int ddepth = SOBEL_DDEPTH;
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// 高斯模糊。Size中的数字影响车牌定位的效果。
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GaussianBlur(src, src_blur, new Size(gaussianBlurSize, gaussianBlurSize), 0, 0, BORDER_DEFAULT);
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if (debug) {
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opencv_imgcodecs.imwrite(tempPath + "debug_GaussianBlur.jpg", src_blur);
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}
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// Convert it to gray 将图像进行灰度化
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cvtColor(src_blur, src_gray, CV_RGB2GRAY);
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if (debug) {
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opencv_imgcodecs.imwrite(tempPath + "debug_gray.jpg", src_gray);
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}
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// 对图像进行Sobel 运算，得到的是图像的一阶水平方向导数。
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// Generate grad_x and grad_y
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Mat grad_x = new Mat();
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Mat grad_y = new Mat();
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Mat abs_grad_x = new Mat();
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Mat abs_grad_y = new Mat();
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Sobel(src_gray, grad_x, ddepth, 1, 0, 3, scale, delta, BORDER_DEFAULT);
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convertScaleAbs(grad_x, abs_grad_x);
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Sobel(src_gray, grad_y, ddepth, 0, 1, 3, scale, delta, BORDER_DEFAULT);
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convertScaleAbs(grad_y, abs_grad_y);
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// Total Gradient (approximate)
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addWeighted(abs_grad_x, SOBEL_X_WEIGHT, abs_grad_y, SOBEL_Y_WEIGHT, 0, grad);
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if (debug) {
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opencv_imgcodecs.imwrite(tempPath + "debug_Sobel.jpg", grad);
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}
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// 对图像进行二值化。将灰度图像（每个像素点有256 个取值可能）转化为二值图像（每个像素点仅有1 和0 两个取值可能）。
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Mat img_threshold = new Mat();
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threshold(grad, img_threshold, 0, 255, CV_THRESH_OTSU + CV_THRESH_BINARY);
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if (debug) {
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opencv_imgcodecs.imwrite(tempPath + "debug_threshold.jpg", img_threshold);
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}
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// 使用闭操作。对图像进行闭操作以后，可以看到车牌区域被连接成一个矩形装的区域。
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Mat element = getStructuringElement(MORPH_RECT, new Size(morphSizeWidth, morphSizeHeight));
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morphologyEx(img_threshold, img_threshold, MORPH_CLOSE, element);
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if (debug) {
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opencv_imgcodecs.imwrite(tempPath + "debug_morphology.jpg", img_threshold);
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}
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// Find 轮廓 of possibles plates 求轮廓。求出图中所有的轮廓。这个算法会把全图的轮廓都计算出来，因此要进行筛选。
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MatVector contours = new MatVector();
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findContours(img_threshold, contours, // a vector of contours
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CV_RETR_EXTERNAL, // 提取外部轮廓
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CV_CHAIN_APPROX_NONE); // all pixels of each contours
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Mat result = new Mat();
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if (debug) {
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src.copyTo(result);
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// 将轮廓描绘到图上输出
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drawContours(result, contours, -1, new Scalar(0, 0, 255, 255));
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opencv_imgcodecs.imwrite(tempPath + "debug_Contours.jpg", result);
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}
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// Start to iterate to each contour founded
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// 筛选。对轮廓求最小外接矩形，然后验证，不满足条件的淘汰。
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Vector<RotatedRect> rects = new Vector<RotatedRect>();
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for (int i = 0; i < contours.size(); ++i) {
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RotatedRect mr = minAreaRect(contours.get(i));
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if (verifySizes(mr))
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rects.add(mr);
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}
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int k = 1;
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for (int i = 0; i < rects.size(); i++) {
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RotatedRect minRect = rects.get(i);
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/*if (debug) {
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Point2f rect_points = new Point2f(4);
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minRect.points(rect_points);
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for (int j = 0; j < 4; j++) {
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Point pt1 = new Point(new CvPoint2D32f(rect_points.position(j)));
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Point pt2 = new Point(new CvPoint2D32f(rect_points.position((j + 1) % 4)));
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line(result, pt1, pt2, new Scalar(0, 255, 255, 255), 1, 8, 0);
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}
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}*/
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// rotated rectangle drawing
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// 旋转这部分代码确实可以将某些倾斜的车牌调整正，但是它也会误将更多正的车牌搞成倾斜！所以综合考虑，还是不使用这段代码。
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// 2014-08-14,由于新到的一批图片中发现有很多车牌是倾斜的，因此决定再次尝试这段代码。
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float r = minRect.size().width() / minRect.size().height();
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float angle = minRect.angle();
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Size rect_size = new Size((int) minRect.size().width(), (int) minRect.size().height());
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if (r < 1) {
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angle = 90 + angle;
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rect_size = new Size(rect_size.height(), rect_size.width());
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}
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// 如果抓取的方块旋转超过m_angle角度，则不是车牌，放弃处理
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if (angle - this.angle < 0 && angle + this.angle > 0) {
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Mat img_rotated = new Mat();
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Mat rotmat = getRotationMatrix2D(minRect.center(), angle, 1);
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warpAffine(src, img_rotated, rotmat, src.size()); // CV_INTER_CUBIC
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Mat resultMat = showResultMat(img_rotated, rect_size, minRect.center(), k++);
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resultVec.add(resultMat);
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}
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}
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return resultVec;
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}
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/**
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* 对minAreaRect获得的最小外接矩形，用纵横比进行判断
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*
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* @param mr
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* @return
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*/
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private boolean verifySizes(RotatedRect mr) {
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float error = this.error;
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// China car plate size: 440mm*140mm，aspect 3.142857
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float aspect = this.aspect;
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int min = 44 * 14 * verifyMin; // minimum area
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int max = 44 * 14 * verifyMax; // maximum area
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// Get only patchs that match to a respect ratio.
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float rmin = aspect - aspect * error;
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float rmax = aspect + aspect * error;
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int area = (int) (mr.size().height() * mr.size().width());
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float r = mr.size().width() / mr.size().height();
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if (r < 1)
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r = mr.size().height() / mr.size().width();
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return area >= min && area <= max && r >= rmin && r <= rmax;
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}
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/**
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* 显示最终生成的车牌图像，便于判断是否成功进行了旋转。
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* @param src
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* @param rect_size
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* @param center
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* @param index
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* @return
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*/
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private Mat showResultMat(Mat src, Size rect_size, Point2f center, int index) {
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Mat img_crop = new Mat();
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getRectSubPix(src, rect_size, center, img_crop);
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if (debug) {
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opencv_imgcodecs.imwrite(tempPath + "debug_crop_" + index + ".jpg", img_crop);
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}
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Mat resultResized = new Mat();
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resultResized.create(HEIGHT, WIDTH, TYPE);
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resize(img_crop, resultResized, resultResized.size(), 0, 0, INTER_CUBIC);
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if (debug) {
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opencv_imgcodecs.imwrite(tempPath + "debug_resize_" + index + ".jpg", resultResized);
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}
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return resultResized;
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}
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public String getTempPath() {
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return tempPath;
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}
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public void setTempPath(String tempPath) {
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this.tempPath = tempPath;
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}
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public void setGaussianBlurSize(int gaussianBlurSize) {
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this.gaussianBlurSize = gaussianBlurSize;
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}
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public final int getGaussianBlurSize() {
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return this.gaussianBlurSize;
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}
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public void setMorphSizeWidth(int morphSizeWidth) {
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this.morphSizeWidth = morphSizeWidth;
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}
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public final int getMorphSizeWidth() {
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return this.morphSizeWidth;
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}
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public void setMorphSizeHeight(int morphSizeHeight) {
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this.morphSizeHeight = morphSizeHeight;
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}
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public final int getMorphSizeHeight() {
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return this.morphSizeHeight;
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}
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public void setVerifyError(float error) {
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this.error = error;
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}
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public final float getVerifyError() {
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return this.error;
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}
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public void setVerifyAspect(float aspect) {
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this.aspect = aspect;
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}
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public final float getVerifyAspect() {
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return this.aspect;
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}
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public void setVerifyMin(int verifyMin) {
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this.verifyMin = verifyMin;
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}
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public void setVerifyMax(int verifyMax) {
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this.verifyMax = verifyMax;
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}
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public void setJudgeAngle(int angle) {
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this.angle = angle;
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}
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public void setDebug(boolean debug) {
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this.debug = debug;
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}
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public boolean getDebug() {
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return debug;
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}
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}
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