怎样使用OpenCV进行人脸识别

Posted 2023-04-30

参考技术A 1.环境搭建：见上一篇博客 整个项目的结构图： 2.编写DetectFaceDemo.java,代码如下： [java] view plaincopyprint? package com.njupt.zhb.test; import org.opencv.core.Core; import org.opencv.core.Mat; import org.opencv.core.MatOfRect; import org.opencv.core.Point; import org.opencv.core.Rect; import org.opencv.core.Scalar; import org.opencv.highgui.Highgui; import org.opencv.objdetect.CascadeClassifier; // // Detects faces in an image, draws boxes around them, and writes the results // to "faceDetection.png". // public class DetectFaceDemo public void run() System.out.println("\nRunning DetectFaceDemo"); System.out.println(getClass().getResource("lbpcascade_frontalface.xml").getPath()); // Create a face detector from the cascade file in the resources // directory. //CascadeClassifier faceDetector = new CascadeClassifier(getClass().getResource("lbpcascade_frontalface.xml").getPath()); //Mat image = Highgui.imread(getClass().getResource("lena.png").getPath()); //注意：源程序的路径会多打印一个‘/’，因此总是出现如下错误 /* * Detected 0 faces Writing faceDetection.png libpng warning: Image * width is zero in IHDR libpng warning: Image height is zero in IHDR * libpng error: Invalid IHDR data */ //因此，我们将第一个字符去掉 String xmlfilePath=getClass().getResource("lbpcascade_frontalface.xml").getPath().substring(1); CascadeClassifier faceDetector = new CascadeClassifier(xmlfilePath); Mat image = Highgui.imread(getClass().getResource("we.jpg").getPath().substring(1)); // Detect faces in the image. // MatOfRect is a special container class for Rect. MatOfRect faceDetections = new MatOfRect(); faceDetector.detectMultiScale(image, faceDetections); System.out.println(String.format("Detected %s faces", faceDetections.toArray().length)); // Draw a bounding box around each face. for (Rect rect : faceDetections.toArray()) Core.rectangle(image, new Point(rect.x, rect.y), new Point(rect.x + rect.width, rect.y + rect.height), new Scalar(0, 255, 0)); // Save the visualized detection. String filename = "faceDetection.png"; System.out.println(String.format("Writing %s", filename)); Highgui.imwrite(filename, image); package com.njupt.zhb.test; import org.opencv.core.Core; import org.opencv.core.Mat; import org.opencv.core.MatOfRect; import org.opencv.core.Point; import org.opencv.core.Rect; import org.opencv.core.Scalar; import org.opencv.highgui.Highgui; import org.opencv.objdetect.CascadeClassifier; // // Detects faces in an image, draws boxes around them, and writes the results // to "faceDetection.png". // public class DetectFaceDemo public void run() System.out.println("\nRunning DetectFaceDemo"); System.out.println(getClass().getResource("lbpcascade_frontalface.xml").getPath()); // Create a face detector from the cascade file in the resources // directory. //CascadeClassifier faceDetector = new CascadeClassifier(getClass().getResource("lbpcascade_frontalface.xml").getPath()); //Mat image = Highgui.imread(getClass().getResource("lena.png").getPath()); //注意：源程序的路径会多打印一个‘/’，因此总是出现如下错误 /* * Detected 0 faces Writing faceDetection.png libpng warning: Image * width is zero in IHDR libpng warning: Image height is zero in IHDR * libpng error: Invalid IHDR data */ //因此，我们将第一个字符去掉 String xmlfilePath=getClass().getResource("lbpcascade_frontalface.xml").getPath().substring(1); CascadeClassifier faceDetector = new CascadeClassifier(xmlfilePath); Mat image = Highgui.imread(getClass().getResource("we.jpg").getPath().substring(1)); // Detect faces in the image. // MatOfRect is a special container class for Rect. MatOfRect faceDetections = new MatOfRect(); faceDetector.detectMultiScale(image, faceDetections); System.out.println(String.format("Detected %s faces", faceDetections.toArray().length)); // Draw a bounding box around each face. for (Rect rect : faceDetections.toArray()) Core.rectangle(image, new Point(rect.x, rect.y), new Point(rect.x + rect.width, rect.y + rect.height), new Scalar(0, 255, 0)); // Save the visualized detection. String filename = "faceDetection.png"; System.out.println(String.format("Writing %s", filename)); Highgui.imwrite(filename, image); 3.编写测试类： [java] view plaincopyprint? package com.njupt.zhb.test; public class TestMain public static void main(String[] args) System.out.println("Hello, OpenCV"); // Load the native library. System.loadLibrary("opencv_java246"); new DetectFaceDemo().run(); //运行结果: //Hello, OpenCV // //Running DetectFaceDemo ///E:/eclipse_Jee/workspace/JavaOpenCV246/bin/com/njupt/zhb/test/lbpcascade_frontalface.xml //Detected 8 faces //Writing faceDetection.png package com.njupt.zhb.test; public class TestMain public static void main(String[] args) System.out.println("Hello, OpenCV"); // Load the native library. System.loadLibrary("opencv_java246"); new DetectFaceDemo().run(); //运行结果: //Hello, OpenCV // //Running DetectFaceDemo ///E:/eclipse_Jee/workspace/JavaOpenCV246/bin/com/njupt/zhb/test/lbpcascade_frontalface.xml //Detected 8 faces //Writing faceDetection.png

使用 Android 进行 OpenCV 人脸识别

【中文标题】使用 Android 进行 OpenCV 人脸识别

【英文标题】：OpenCV face recognition with Android

【发布时间】：2021-03-01 15:00:54

【问题描述】：

我对 android 很陌生，因为我有一个维护项目。我完成了项目的其他部分，如身份验证、令牌设置等......其中面部识别用于识别人。

以前它工作正常并拍摄图像，用它训练并识别出这个人。（显然不是我做的:)）。现在它抛出错误

添加人员 ActivityCvException [org.opencv.core.CvException: 简历::异常： /build/master_pack-android/opencv/modules/core/src/matrix.cpp:1047： 错误：（-13）矩阵不连续，因此它的行数可以 不能在函数 cv::Mat 中改变 cv::Mat::reshape(int, int) const

代码示例如下

public void training() 
    Thread thread;
    try
    PreferenceManager.setDefaultValues(getApplicationContext(), R.xml.preferences, false);
    catch (Exception e)
        AddPersonActivity.this.runOnUiThread(new Runnable() 
            public void run() 
                WriteLog("Add Person Activity" +e.fillInStackTrace());
                errorAlert("Add Person Activity" +e.fillInStackTrace());
                VolleyHelper.progressDialog.dismiss();
            
        );

    
    WriteLog("training 1 ");

    final Handler handler = new Handler(Looper.getMainLooper());
    thread = new Thread(new Runnable() 
        public void run() 
            if (!Thread.currentThread().isInterrupted()) 
                try 
                    WriteLog("training 2 ");
                PreProcessorFactory ppF = new PreProcessorFactory(AddPersonActivity.this);
                PreferencesHelper preferencesHelper = new PreferencesHelper(AddPersonActivity.this);
                String algorithm = preferencesHelper.getClassificationMethod();

                FileHelper fileHelper = new FileHelper();
                fileHelper.createDataFolderIfNotExsiting();
                final File[] persons = fileHelper.getTrainingList();
                if (persons.length > 0) 
                    Recognition rec = RecognitionFactory.getRecognitionAlgorithm(getApplicationContext(), Recognition.TRAINING, algorithm);
                    for (File person : persons) 
                        if (person.isDirectory()) 
                            File[] files = person.listFiles();
                            int counter = 1;
                            for (File file : files) 
                                if (FileHelper.isFileAnImage(file)) 
                                    Mat imgRgb = Imgcodecs.imread(file.getAbsolutePath());
                                    Imgproc.cvtColor(imgRgb, imgRgb, Imgproc.COLOR_BGRA2RGBA);
                                    Mat processedImage = new Mat();
                                    imgRgb.copyTo(processedImage);
                                    List<Mat> images = ppF.getProcessedImage(processedImage, PreProcessorFactory.PreprocessingMode.RECOGNITION);
                                    if (images == null || images.size() > 1) 
                                        continue;
                                     else 
                                        processedImage = images.get(0);
                                    
                                    if (processedImage.empty()) 
                                        continue;
                                    
                                    String[] tokens = file.getParent().split("/");
                                    final String name = tokens[tokens.length - 1];

                                    for (int i = 0; i < files.length; i++) 
                                        File myfile = new File(person +

                                                "\\" + files[i].getName());
                                        String long_file_name = files[i].getName();
                                        System.out.println(long_file_name);
                                        System.out.print(long_file_name);

                                        myfile.renameTo(new File(person +
                                                "\\" + long_file_name + "_101" + ".png"));
                                    

                                    WriteLog("training 3 ");

                                    MatName m = new MatName("processedImage", processedImage);
                                    fileHelper.saveMatToImage(m, FileHelper.DATA_PATH);


                                    rec.addImage(processedImage, name, false);

                                    counter++;
                                
                            
                        
                    

                    try 

                        if (rec.train()) 
                            if (zipFileAtPath("/storage/emulated/0/Pictures/facerecognition/training/" + lcode, "/storage/emulated/0/Pictures/facerecognition/data/SVM/" + lcode + ".zip")) 
                                WriteLog("training 4 ");
                                if (zipFileAtPath("/storage/emulated/0/Pictures/facerecognition/data/SVM", "/storage/emulated/0/Pictures/facerecognition/" + "SVM_" + lcode + ".zip")) 
                                    WriteLog("training 5 ");
                                    fileupload(getintent.getStringExtra("lcode"));
                                 else 
                                    Toast.makeText(getApplicationContext(), "No Face Recognised", Toast.LENGTH_SHORT).show();
                                
                             else 
                                Toast.makeText(getApplicationContext(), "No Face Recognised", Toast.LENGTH_SHORT).show();
                            
                         else 
                            Toast.makeText(getApplicationContext(), "Try Again", Toast.LENGTH_SHORT).show();
                            
                        
                     catch (Exception e) 
                        WriteLog("Add Person Activity" +e.fillInStackTrace());
                        errorAlert("Add Person Activity" +e.fillInStackTrace());

                    


                    handler.post(new Runnable() 
                        @Override
                        public void run() 

                        
                    );
                 else 
                    Thread.currentThread().interrupt();
                

             catch (Exception e) 
                    AddPersonActivity.this.runOnUiThread(new Runnable() 
                        public void run() 
                            VolleyHelper.progressDialog.dismiss();
                            WriteLog("Add Person Activity" +e.fillInStackTrace());
                            errorAlert("Add Person Activity" +e.fillInStackTrace());
                        
                    );


            

            
        
    );
    thread.start();

【参考方案1】：

输入图像需要作为连续的字节块存储在内存中。我遇到了类似的情况，特别是因为 Android（至少我尝试过的版本）似乎并没有连续存储图像。 1）检查图像是否连续使用：inputImage.isContinuous()。它返回一个bool。应该是true。 2) 如果图像不连续，您可以通过inputImage.clone() 创建图像的clone 来创建图像的副本。在幕后，我们正在使用create 方法创建输入的深层副本，这应该保证新矩阵是连续的。

 //check image before continuing:
 if ( !inputImage.isContinuous() ) 
    //if the image is not continuous, create a deep copy:
    inputImage = inputImage.clone();