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108 lines
3.0 KiB
108 lines
3.0 KiB
package com.yuxue.easypr.core;
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import org.bytedeco.javacpp.opencv_core;
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import org.bytedeco.javacpp.opencv_imgproc;
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import java.util.Vector;
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import org.bytedeco.javacpp.opencv_core.Mat;
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import org.bytedeco.javacpp.opencv_core.Rect;
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import org.bytedeco.javacpp.opencv_core.Size;
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import org.bytedeco.javacpp.opencv_ml.SVM;
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import com.yuxue.constant.Constant;
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/**
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* 车牌判断
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* @author yuxue
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* @date 2020-04-26 15:21
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*/
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public class PlateJudge {
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private SVM svm = SVM.create();
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public PlateJudge() {
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loadSVM(Constant.DEFAULT_SVM_PATH);
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}
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public void loadSVM(String path) {
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svm.clear();
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// svm=SVM.loadSVM(path, "svm");
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svm=SVM.load(path);
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}
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/**
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* EasyPR的getFeatures回调函数, 用于从车牌的image生成svm的训练特征features
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*/
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private SVMCallback features = new Features();
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/**
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* 对单幅图像进行SVM判断
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* @param inMat
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* @return
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*/
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public int plateJudge(final Mat inMat) {
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int ret = 1;
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// 使用com.yuxue.train.SVMTrain 生成的训练库文件
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Mat features = this.features.getHistogramFeatures(inMat);
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/*Mat samples = features.reshape(1, 1);
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samples.convertTo(samples, opencv_core.CV_32F);*/
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Mat p = features.reshape(1, 1);
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p.convertTo(p, opencv_core.CV_32FC1);
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ret = (int) svm.predict(features);
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return ret;
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// 使用com.yuxue.train.PlateRecoTrain 生成的训练库文件
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// 在使用的过程中，传入的样本切图要跟训练的时候处理切图的方法一致
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/*Mat grayImage = new Mat();
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opencv_imgproc.cvtColor(inMat, grayImage, opencv_imgproc.CV_RGB2GRAY);
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Mat dst = new Mat();
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opencv_imgproc.Canny(grayImage, dst, 130, 250);
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Mat samples = dst.reshape(1, 1);
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samples.convertTo(samples, opencv_core.CV_32F);*/
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// 正样本为0 负样本为1
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/*if(svm.predict(samples) <= 0) {
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ret = 1;
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}*/
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/*ret = (int)svm.predict(samples);
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System.err.println(ret);
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return ret ;*/
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}
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/**
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* 对多幅图像进行SVM判断
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* @param inVec
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* @param resultVec
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* @return
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*/
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public int plateJudge(Vector<Mat> inVec, Vector<Mat> resultVec) {
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for (int j = 0; j < inVec.size(); j++) {
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Mat inMat = inVec.get(j);
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if (1 == plateJudge(inMat)) {
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resultVec.add(inMat);
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} else { // 再取中间部分判断一次
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int w = inMat.cols();
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int h = inMat.rows();
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Mat tmpDes = inMat.clone();
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Mat tmpMat = new Mat(inMat, new Rect((int) (w * 0.05), (int) (h * 0.1), (int) (w * 0.9), (int) (h * 0.8)));
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opencv_imgproc.resize(tmpMat, tmpDes, new Size(inMat.size()));
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if (plateJudge(tmpDes) == 1) {
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resultVec.add(inMat);
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}
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}
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}
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return 0;
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}
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}
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