JavaCV以图搜图代码

以下是使用JavaCV实现以图搜图的代码示例：

import org.bytedeco.javacpp.opencv_core.*;
import org.bytedeco.javacpp.opencv_features2d.*;
import org.bytedeco.javacpp.opencv_xfeatures2d.*;
import org.bytedeco.javacpp.indexer.FloatRawIndexer;
import org.bytedeco.javacpp.indexer.UByteRawIndexer;

import java.io.File;
import java.util.ArrayList;
import java.util.List;

import static org.bytedeco.javacpp.opencv_core.CV_32F;
import static org.bytedeco.javacpp.opencv_core.CV_8U;
import static org.bytedeco.javacpp.opencv_core.NORM_L2;
import static org.bytedeco.javacpp.opencv_features2d.Features2d.drawKeypoints;
import static org.bytedeco.javacpp.opencv_imgcodecs.imread;
import static org.bytedeco.javacpp.opencv_imgcodecs.imwrite;
import static org.bytedeco.javacpp.opencv_xfeatures2d.SIFT.create;

public class ImageSearch {
    public static void main(String[] args) {
        // 加载原图并提取SIFT特征
        Mat img1 = imread("path/to/image1.jpg");
        Mat img1Gray = new Mat();
        cvtColor(img1, img1Gray, COLOR_BGR2GRAY);
        MatOfKeyPoint keypoints1 = new MatOfKeyPoint();
        Mat descriptors1 = new Mat();
        create().detectAndCompute(img1Gray, new Mat(), keypoints1, descriptors1);

        // 加载待搜索图像并提取SIFT特征
        Mat img2 = imread("path/to/image2.jpg");
        Mat img2Gray = new Mat();
        cvtColor(img2, img2Gray, COLOR_BGR2GRAY);
        MatOfKeyPoint keypoints2 = new MatOfKeyPoint();
        Mat descriptors2 = new Mat();
        create().detectAndCompute(img2Gray, new Mat(), keypoints2, descriptors2);

        // 匹配SIFT特征
        MatOfDMatch matches = new MatOfDMatch();
        DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.FLANNBASED);
        matcher.match(descriptors1, descriptors2, matches);

        // 筛选距离最近的匹配点
        float minDistance = Float.MAX_VALUE;
        DMatch[] matchArray = matches.toArray();
        for (int i = 0; i < matchArray.length; i++) {
            float distance = matchArray[i].distance();
            if (distance < minDistance) {
                minDistance = distance;
            }
        }
        List<DMatch> goodMatches = new ArrayList<>();
        for (int i = 0; i < matchArray.length; i++) {
            if (matchArray[i].distance() <= 2 * minDistance) {
                goodMatches.add(matchArray[i]);
            }
        }

        // 绘制匹配结果
        Mat result = new Mat();
        drawMatches(img1, keypoints1, img2, keypoints2, new MatOfDMatch(goodMatches.toArray(new DMatch[0])), result);
        imwrite("path/to/result.jpg", result);
    }
}

以上代码中，我们使用JavaCV提供的SIFT算法对原图像和待搜索图像提取SIFT特征，然后使用FLANN匹配器进行匹配，筛选出距离最近的匹配点，并绘制匹配结果。注意，由于JavaCV并不支持直接绘制匹配点，因此我们需要使用OpenCV的C++接口中提供的drawMatches函数，将其转换为Mat类型后再进行绘制。