java opencv识别图片中有多少根筷子代码

以下是使用Java OpenCV库识别图片中有多少根筷子的示例代码：

import org.opencv.core.Core;
import org.opencv.core.Mat;
import org.opencv.core.MatOfKeyPoint;
import org.opencv.core.Scalar;
import org.opencv.features2d.FeatureDetector;
import org.opencv.features2d.Features2d;
import org.opencv.highgui.HighGui;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;

public class ChopsticksDetector {
    public static void main(String[] args) {
        // Load the image
        Mat img = Imgcodecs.imread("chopsticks.jpg");

        // Convert the image to grayscale
        Mat gray = new Mat();
        Imgproc.cvtColor(img, gray, Imgproc.COLOR_BGR2GRAY);

        // Detect the keypoints using the SIFT detector
        FeatureDetector detector = FeatureDetector.create(FeatureDetector.SIFT);
        MatOfKeyPoint keypoints = new MatOfKeyPoint();
        detector.detect(gray, keypoints);

        // Draw the keypoints on the image
        Mat outputImg = new Mat();
        Scalar keypointColor = new Scalar(0, 255, 0); // Green keypoints
        Features2d.drawKeypoints(img, keypoints, outputImg, keypointColor);

        // Count the number of chopsticks
        int numChopsticks = keypoints.toList().size() / 2;

        // Show the output image and print the number of chopsticks
        HighGui.imshow("Chopsticks", outputImg);
        System.out.println("Number of chopsticks: " + numChopsticks);
        HighGui.waitKey();
    }
}

需要注意的是，这个示例代码使用的是 SIFT 特征检测器，这是一种比较老的算法，可能不能很好地适应新的图片。如果需要更好的性能，可以考虑使用 SURF 或者 ORB 特征检测器，或者使用深度学习的方法进行检测。