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package com.zhonglai.luhui.smart.feeder.service;
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import com.zhonglai.luhui.smart.feeder.config.OpenCVConfig;
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import com.zhonglai.luhui.smart.feeder.util.OpenCVUtils;
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import org.opencv.core.Core;
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import org.opencv.core.Mat;
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import org.opencv.videoio.VideoCapture;
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import org.opencv.imgproc.Imgproc;
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import org.opencv.core.MatOfPoint;
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import org.opencv.core.Scalar;
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import org.opencv.core.CvType;
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import org.opencv.core.Rect;
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import javax.swing.*;
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import java.awt.image.BufferedImage;
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import java.util.ArrayList;
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import java.util.List;
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public class OpenCVService {
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public static void main(String[] args) {
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OpenCVConfig.loadOpenCv(args);
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readVideoCaptureForVideo("C:/Users/123/Pictures/图片识别/6月30日.mp4");
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}
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public static void readVideoCaptureForVideo(String videoPath)
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{
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// 创建VideoCapture对象
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VideoCapture videoCapture = new VideoCapture();
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boolean isopen = videoCapture.open(videoPath);
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System.out.println(isopen);
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// 检查视频是否成功打开
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if (!videoCapture.isOpened()) {
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System.out.println("无法打开视频文件");
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return;
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}
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// 背景帧
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Mat backgroundFrame = new Mat();
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// 初始阈值范围
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double minAreaThreshold = Double.MAX_VALUE;
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double maxAreaThreshold = 0;
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// 逐帧处理视频
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Mat frame = new Mat();
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while (videoCapture.read(frame)) {
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// 背景差分
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Mat diffFrame = new Mat();
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Core.absdiff(frame, backgroundFrame, diffFrame);
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// 灰度转换
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Mat grayFrame = new Mat();
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Imgproc.cvtColor(diffFrame, grayFrame, Imgproc.COLOR_BGR2GRAY);
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// 阈值处理
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Mat thresholdFrame = new Mat();
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Imgproc.threshold(grayFrame, thresholdFrame, 30, 255, Imgproc.THRESH_BINARY);
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// 边缘检测
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Mat edges = new Mat();
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Imgproc.Canny(thresholdFrame, edges, 100, 200);
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// 轮廓检测
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List<MatOfPoint> contours = new ArrayList<>();
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Mat hierarchy = new Mat();
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Imgproc.findContours(edges, contours, hierarchy, Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE);
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// 更新阈值范围
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for (MatOfPoint contour : contours) {
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double area = Imgproc.contourArea(contour);
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if (area > maxAreaThreshold) {
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maxAreaThreshold = area;
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}
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if (area < minAreaThreshold) {
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minAreaThreshold = area;
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}
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}
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// 根据阈值范围选择适当的阈值
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double thresholdValue = (maxAreaThreshold + minAreaThreshold) / 2.0;
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// 绘制轮廓
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Mat contourImage = new Mat(frame.size(), CvType.CV_8UC3, new Scalar(0, 0, 0));
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Imgproc.drawContours(contourImage, contours, -1, new Scalar(0, 255, 0), 2);
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// 提取鱼群区域
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for (MatOfPoint contour : contours) {
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double area = Imgproc.contourArea(contour);
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if (area > thresholdValue) {
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// 对于满足面积阈值的轮廓，可以进一步处理或分析
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// 例如，计算鱼群数量、中心位置等信息
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// ...
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// 在原图上绘制鱼群区域
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Rect boundingRect = Imgproc.boundingRect(contour);
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Imgproc.rectangle(frame, boundingRect.tl(), boundingRect.br(), new Scalar(0, 255, 0), 2);
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}
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}
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// 重置阈值范围
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minAreaThreshold = Double.MAX_VALUE;
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maxAreaThreshold = 0;
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// 在图像上显示结果
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displayImage(frame);
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}
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}
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// 显示图像
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private static void displayImage(Mat image) {
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// 将Mat图像转换为BufferedImage
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BufferedImage bufferedImage = OpenCVUtils.matToBufferedImage(image);
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// 在标签上显示图像
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new ImageIcon(bufferedImage);
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// 更新窗口
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}
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} |
...
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...
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