问题描述
最近，我正在尝试实现基于YOLO的图像对象检测工具。首先，我使用了代码here。听起来一切正常，除了该程序未通过以下代码行（第72行）并且不会进入循环。 ：
if (cap.read(frame))
换句话说，如果在该行上放置了一个断点，程序将不会继续进行下一步。任何想法如何解决此问题？
package yoloexample;
import org.opencv.core.*;
import org.opencv.dnn.*;
import org.opencv.utils.*;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;
import org.opencv.objdetect.CascadeClassifier;
import org.opencv.videoio.VideoCapture;
import java.awt.image.BufferedImage;
import java.awt.image.DataBufferByte;
import java.awt.image.WritableRaster;
import java.io.ByteArrayInputStream;
import java.io.FileNotFoundException;
import java.io.IOException;
import java.io.InputStream;
import java.util.ArrayList;
import java.util.List;
import javax.imageio.ImageIO;
import javax.swing.ImageIcon;
import javax.swing.JFrame;
import javax.swing.JLabel;
public class Yoloexample {
private static List<String> getoutputNames(Net net) {
List<String> names = new ArrayList<>();
List<Integer> outLayers = net.getUnconnectedOutLayers().toList();
List<String> layersNames = net.getLayerNames();
outLayers.forEach((item) -> names.add(layersNames.get(item - 1)));//unfold and create R-CNN layers from the loaded YOLO model//
System.out.println(names);
return names;
}
/**
* @param args the command line arguments
*/
public static void main(String[] args) {
// Todo code application logic here
System.load("\\opencv\\opencv\\build\\java\\x64\\opencv_java420.dll"); // Load the openCV 4.0 dll //
String modelWeights = "g:\\yolov3.weights"; //Download and load only wights for YOLO,this is obtained from official YOLO site//
String modelConfiguration = "g:\\yolov3.cfg";//Download and load cfg file for YOLO,can be obtained from official site//
String filePath = "test.mp4"; //My video file to be analysed//
VideoCapture cap = new VideoCapture(filePath);// Load video using the videocapture method//
Mat frame = new Mat(); // define a matrix to extract and store pixel info from video//
//cap.read(frame);
JFrame jframe = new JFrame("Video"); // the lines below create a frame to display the resultant video with object detection and localization//
JLabel vidpanel = new JLabel();
jframe.setContentPane(vidpanel);
jframe.setSize(600,600);
jframe.setVisible(true);// we instantiate the frame here//
Net net = Dnn.readNetFromDarknet(modelConfiguration,modelWeights); //OpenCV DNN supports models trained from varIoUs frameworks like Caffe and TensorFlow. It also supports varIoUs networks architectures based on YOLO//
//Thread.sleep(5000);
//Mat image = Imgcodecs.imread("D:\\yolo-object-detection\\yolo-object-detection\\images\\soccer.jpg");
Size sz = new Size(288,288);
List<Mat> result = new ArrayList<>();
List<String> outBlobNames = getoutputNames(net);
while (true) {
if (cap.read(frame)) {
Mat blob = Dnn.blobFromImage(frame,0.00392,sz,new Scalar(0),true,false); // We Feed one frame of video into the network at a time,we have to convert the image to a blob. A blob is a pre-processed image that serves as the input.//
net.setInput(blob);
net.forward(result,outBlobNames); //Feed forward the model to get output //
// outBlobNames.forEach(System.out::println);
// result.forEach(System.out::println);
float confThreshold = 0.6f; //Insert thresholding beyond which the model will detect objects//
List<Integer> clsIds = new ArrayList<>();
List<Float> confs = new ArrayList<>();
List<Rect> rects = new ArrayList<>();
for (int i = 0; i < result.size(); ++i) {
// each row is a candidate detection,the 1st 4 numbers are
// [center_x,center_y,width,height],followed by (N-4) class probabilities
Mat level = result.get(i);
for (int j = 0; j < level.rows(); ++j) {
Mat row = level.row(j);
Mat scores = row.colRange(5,level.cols());
Core.MinMaxLocResult mm = Core.minMaxLoc(scores);
float confidence = (float) mm.maxVal;
Point classIdPoint = mm.maxLoc;
if (confidence > confThreshold) {
int centerX = (int) (row.get(0,0)[0] * frame.cols()); //scaling for drawing the bounding Boxes//
int centerY = (int) (row.get(0,1)[0] * frame.rows());
int width = (int) (row.get(0,2)[0] * frame.cols());
int height = (int) (row.get(0,3)[0] * frame.rows());
int left = centerX - width / 2;
int top = centerY - height / 2;
clsIds.add((int) classIdPoint.x);
confs.add((float) confidence);
rects.add(new Rect(left,top,height));
}
}
}
float nmsThresh = 0.5f;
MatOfFloat confidences = new MatOfFloat(Converters.vector_float_to_Mat(confs));
Rect[] BoxesArray = rects.toArray(new Rect[0]);
MatOfRect Boxes = new MatOfRect(BoxesArray);
MatOfInt indices = new MatOfInt();
Dnn.NMSBoxes(Boxes,confidences,confThreshold,nmsThresh,indices); //We draw the bounding Boxes for objects here//
int[] ind = indices.toArray();
int j = 0;
for (int i = 0; i < ind.length; ++i) {
int idx = ind[i];
Rect Box = BoxesArray[idx];
Imgproc.rectangle(frame,Box.tl(),Box.br(),new Scalar(0,255),2);
//i=j;
System.out.println(idx);
}
// Imgcodecs.imwrite("D://out.png",image);
//System.out.println("Image Loaded");
ImageIcon image = new ImageIcon(Mat2bufferedImage(frame)); //setting the results into a frame and initializing it //
vidpanel.setIcon(image);
vidpanel.repaint();
System.out.println(j);
System.out.println("Done");
}
}
}
private static BufferedImage Mat2bufferedImage(Mat image) { // The class described here takes in matrix and renders the video to the frame //
MatOfByte bytemat = new MatOfByte();
Imgcodecs.imencode(".jpg",image,bytemat);
byte[] bytes = bytemat.toArray();
InputStream in = new ByteArrayInputStream(bytes);
BufferedImage img = null;
try {
img = ImageIO.read(in);
} catch (IOException e) {
// Todo Auto-generated catch block
e.printstacktrace();
}
return img;
}
}
解决方法
暂无找到可以解决该程序问题的有效方法，小编努力寻找整理中！
如果你已经找到好的解决方法，欢迎将解决方案带上本链接一起发送给小编。
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