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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 com.zhonglai.luhui.smart.feeder.draw.FishRegionPanel;
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import org.opencv.core.*;
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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.Arrays;
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import java.util.Collections;
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import java.util.List;
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public class OpenCVService {
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/**
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* 反光阈值（reflectionThreshold）被设置为100。这意味着所有灰度值低于100的像素都会被设置为0（黑色），灰度值大于或等于100的像素都会被设置为255（白色）。如果你的图像中的对象或区域的灰度值接近或低于这个阈值，它们可能会被排除在二值图像之外。尝试调整这个阈值可能有助于改善结果
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*/
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public static int reflectionThreshold = 100; // 反光阈值
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public static int kernelSize = 3; // 去噪调整内核大小,用来消除小的物体或噪声
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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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readVideoCaptureForVideo("C:/Users/123/Pictures/1.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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@@ -32,86 +34,168 @@ public class OpenCVService { |
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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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brightnessIdentifyFishRegion(videoCapture);
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// 释放资源
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videoCapture.release();
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}
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/**
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* 亮度查找水面，透明度过滤鱼群
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*/
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private static void brightnessIdentifyFishRegion(VideoCapture videoCapture)
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{
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// 读取第一帧并获取视频大小
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Mat previousFrame = new Mat();
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if (!videoCapture.read(previousFrame)) {
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System.out.println("无法读取视频帧");
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return;
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}
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// 获取水域轮廓
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MatOfPoint largestContour = getDefaultMatOfPoint(previousFrame);
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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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//画板
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FishRegionPanel fishRegionPanel = new FishRegionPanel();
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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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//抠图
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Mat shuiyu = matting(frame,largestContour);
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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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// 2. 转换为灰度图像
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Mat gray = new Mat();
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Imgproc.cvtColor(shuiyu, gray, Imgproc.COLOR_BGR2GRAY);
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// 3. 进行阈值分割以得到二值图像
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Mat binaryImage = new Mat();
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Imgproc.threshold(gray, binaryImage, 100, 255, Imgproc.THRESH_BINARY);
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List<MatOfPoint> contours = new ArrayList<>(); // 用于存储找到的轮廓
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Mat hierarchy = new Mat(); // 轮廓的层次结构
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// 在水域二值图像中找所有轮廓
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Imgproc.findContours(binaryImage, contours, hierarchy, Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE);
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//计算大小
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double area = getArea(contours);
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//标注识别对象
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Imgproc.drawContours(frame, contours, -1, new Scalar(0, 0, 255), 2);
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Imgproc.drawContours(frame, Arrays.asList(new MatOfPoint[]{largestContour}), 0, new Scalar(0, 255, 0), 2);
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// 显示图像
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// 在图像上显示结果
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displayImage(frame);
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fishRegionPanel.displayImage(binaryImage);
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fishRegionPanel.dispSrcImage(frame);
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// 绘制鱼群变化曲线
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fishRegionPanel.addFishCount(new Double(area).intValue());
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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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/**
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* 获取标准水域轮廓
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* @param previousFrame
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* @return
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*/
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private static MatOfPoint getDefaultMatOfPoint(Mat previousFrame)
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{
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Mat firstBinaryImage = waterBybinary(previousFrame);
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// 绘制白色区域的轮廓
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List<MatOfPoint> contours = new ArrayList<>();
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Mat hierarchy = new Mat();
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Imgproc.findContours(firstBinaryImage, contours, hierarchy, Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE);
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// 找到最大区域
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double maxArea = 0;
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int maxAreaIndex = -1;
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for (int i = 0; i < contours.size(); i++) {
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double area = Imgproc.contourArea(contours.get(i));
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if (area > maxArea) {
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maxArea = area;
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maxAreaIndex = i;
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}
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}
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// 获取最大区域的轮廓
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MatOfPoint largestContour = contours.get(maxAreaIndex);
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return largestContour;
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}
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private static double getArea(List<MatOfPoint> contours) {
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// 找到最大区域
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double maxArea = 0;
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int maxAreaIndex = -1;
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for (int i = 0; i < contours.size(); i++) {
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double area = Imgproc.contourArea(contours.get(i));
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if (area > maxArea) {
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maxArea = area;
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maxAreaIndex = i;
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}
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}
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if(-1 != maxAreaIndex)
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{
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contours.remove(maxAreaIndex);
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}
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// 返回总面积
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return maxArea;
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}
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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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private static Mat matting(Mat frame,MatOfPoint largestContour)
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{
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// 创建一个与原始图像相同大小的新Mat，用于提取图像区域
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Mat extractedRegion = Mat.zeros(frame.size(), frame.type());
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// 将指定的轮廓绘制到新的Mat上
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Imgproc.drawContours(extractedRegion, Collections.singletonList(largestContour), 0, new Scalar(255, 255, 255), -1);
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// 使用按位与操作提取对应的图像区域
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Mat extractedImage = new Mat();
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Core.bitwise_and(frame, extractedRegion, extractedImage);
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return extractedImage;
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}
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/**
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* 根据反光查找水面
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* @param frame
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* @return
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*/
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private static Mat waterBybinary(Mat frame) {
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// 将加载的图像转换为灰度图像，以便进行亮度或反光的分析
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Mat grayImage = new Mat();
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Imgproc.cvtColor(frame, grayImage, Imgproc.COLOR_BGR2GRAY);
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// 检测反光
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Mat binaryImage = new Mat();
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double maxValue = 255;
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Imgproc.threshold(grayImage, binaryImage, reflectionThreshold, maxValue, Imgproc.THRESH_BINARY);
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// 进行形态学操作，去除噪点
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Mat kernel = Imgproc.getStructuringElement(Imgproc.MORPH_RECT, new Size(kernelSize, kernelSize));
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Imgproc.morphologyEx(binaryImage, binaryImage, Imgproc.MORPH_OPEN, kernel);
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return binaryImage;
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}
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private static List<MatOfPoint> fishByWater(Mat frame)
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{
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// 2. 转换为灰度图像
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Mat gray = new Mat();
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Imgproc.cvtColor(frame, gray, Imgproc.COLOR_BGR2GRAY);
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// 3. 进行阈值分割以得到二值图像
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Mat binary = new Mat();
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Imgproc.threshold(gray, binary, 100, 255, Imgproc.THRESH_BINARY);
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// 4. 查找轮廓
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List<MatOfPoint> contours = new ArrayList<>();
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Mat hierarchy = new Mat();
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Imgproc.findContours(binary, contours, hierarchy, Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE);
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return contours;
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}
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} |
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