前几篇文章中有提到对openCV环境配置，这里再重新梳理导入和使用openCV进行简单的人脸检测（包括使用级联分类器）

一首先导入openCVLibrary320

二设置gradle的sdk版本号与当前项目一致

    compileSdkVersion 26
    buildToolsVersion "26.0.2"

    defaultConfig {
        minSdkVersion 14
        targetSdkVersion 26
    }

三新建 jniLibs 目录

在 app/src/main 目录下与 java 目录同级，新建 jniLibs 目录

把 OpenCV-android-sdk-3.2/sdk/native/libs 目录下的所有文件夹内容拷贝到 jniLibs 目录

四加载so包

    private static String strLibraryName = "opencv_java3"; // 不需要添加前缀 libopencv_java3

static {
try {
            Log.e("loadLibrary", strLibraryName);
            System.loadLibrary(strLibraryName);
//System.loadLibrary(Core.NATIVE_LIBRARY_NAME); // couldn't find "libopencv_java320.so"
        } catch (UnsatisfiedLinkError e) {
            Log.e("loadLibrary", "Native code library failed to load.\n" + e);
        } catch (Exception e) {
            Log.e("loadLibrary", "Exception: " + e);
        }
    }

五添加xml级联分类器

在导入的openCVLibrary320模块中，找到 src/main/res 目录，新建raw文件夹。

在 OpenCV-android-sdk-3.2/sdk/etc 目录下，存放的则是训练好的分类器。把 haarcascades 目录和 lbpcascades 目录内的所有xml文件拷贝到 raw目录中。

六配置权限

    <uses-permission android:name="android.permission.WRITE_EXTERNAL_STORAGE" />
<uses-permission android:name="android.permission.READ_EXTERNAL_STORAGE" />
<uses-permission android:name="android.permission.MOUNT_UNMOUNT_FILESYSTEMS" />

<uses-permission android:name="android.permission.CAMERA" />
<uses-permission android:name="android.permission.FLASHLIGHT" />

完成以上步骤，就可以使用opencv了。

使用openCV

首先创建检测器

    mCascadeClassifier = createDetector(context, R.raw.haarcascade_frontalface_alt);


/**
     * 创建检测器
     *
     * @param context 上下文
     * @param id      级联分类器ID
     * @return 检测器
*/
private CascadeClassifier createDetector(Context context, int id) {
        CascadeClassifier javaDetector;
        InputStream is = null;
        FileOutputStream os = null;
try {
            is = context.getResources().openRawResource(id);
            File cascadeDir = context.getDir("cascade", Context.MODE_PRIVATE);
            File cascadeFile = new File(cascadeDir, id + ".xml");
            os = new FileOutputStream(cascadeFile);

byte[] buffer = new byte[4096];
int bytesRead;
while ((bytesRead = is.read(buffer)) != -1) {
                os.write(buffer, 0, bytesRead);
            }

            javaDetector = new CascadeClassifier(cascadeFile.getAbsolutePath());
if (javaDetector.empty()) {
                javaDetector = null;
            }

boolean delete = cascadeDir.delete();
return javaDetector;
        } catch (IOException e) {
            e.printStackTrace();
return null;
        } finally {
try {
if (null != is) {
                    is.close();
                }
if (null != os) {
                    os.close();
                }
            } catch (IOException e) {
                e.printStackTrace();
            }
        }
    }

检测人脸方法：

    /**
     * 目标检测 图片
     *
     * @param gray   灰度图像
     * @param object 识别结果的容器
     * @return
*/
public Rect[] detectObjectImage(Mat gray, MatOfRect object) {
        mCascadeClassifier.detectMultiScale(gray,object);
return object.toArray();
    }

detectFace 整个函数：

    private void detectFace() {
try {
// bitmapToMat
            Mat toMat = new Mat();
            Utils.bitmapToMat(bitmap, toMat);
            Mat copyMat = new Mat();
            toMat.copyTo(copyMat); // 复制

// togray
            Mat gray = new Mat();
            Imgproc.cvtColor(toMat, gray, Imgproc.COLOR_RGBA2GRAY);

            MatOfRect mRect = new MatOfRect();
            Rect[] object = mFaceDetector.detectObjectImage(gray, mRect);

            Log.e("objectLength", object.length + "");


int maxRectArea = 0 * 0;
            Rect maxRect = null;

int facenum = 0;
// Draw a bounding box around each face.
for (Rect rect : object) {
                Imgproc.rectangle(
                        toMat,
new Point(rect.x, rect.y),
new Point(rect.x + rect.width, rect.y + rect.height),
new Scalar(255, 0, 0), 3);
++facenum;
// 找出最大的面积
int tmp = rect.width * rect.height;
if (tmp >= maxRectArea) {
                    maxRectArea = tmp;
                    maxRect = rect;
                }
            }

            rectBitmap = null;
if (facenum != 0) {
// 剪切最大的头像
                Log.e("剪切的长宽", String.format("高:%s,宽:%s", maxRect.width, maxRect.height));
                Rect rect = new Rect(maxRect.x, maxRect.y, maxRect.width, maxRect.height);
                Mat rectMat = new Mat(copyMat, rect);  // 从原始图像拿
                rectBitmap = Bitmap.createBitmap(rectMat.cols(), rectMat.rows(), Bitmap.Config.ARGB_8888);
                Utils.matToBitmap(rectMat, rectBitmap);
            }

            textView.setText(String.format("检测到%1$d个人脸", facenum));
            Utils.matToBitmap(toMat, bitmap);


        } catch (Exception e) {
            e.printStackTrace();
        }

    }

附所有代码：

package com.myproject.facedetection.ui;

import android.content.Intent;
import android.graphics.Bitmap;
import android.graphics.BitmapFactory;
import android.net.Uri;
import android.os.Environment;
import android.provider.MediaStore;
import android.support.v7.app.AppCompatActivity;
import android.os.Bundle;
import android.util.Log;
import android.view.Gravity;
import android.view.View;
import android.widget.TextView;
import android.widget.Toast;

import com.myproject.facedetection.R;
import com.myproject.facedetection.entity.CustomImageButton;
import com.opencvlib.ObjectDetector;

import org.opencv.android.Utils;
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.imgproc.Imgproc;

import java.io.File;

public class FaceDetectionOpenCVActivity extends AppCompatActivity {
private ObjectDetector mFaceDetector;

private static String CAMERAIMAGENAME = "image.jpg";
private CustomImageButton imageButton;
private CustomImageButton imageButton2;
private TextView textView;
private Bitmap bitmap;
private Bitmap rectBitmap;
private Bitmap resizeBitmap;
private Toast toast;


    @Override
protected void onCreate(Bundle savedInstanceState) {
super.onCreate(savedInstanceState);
        setContentView(R.layout.activity_face_detection_opencv);
        textView = (TextView) findViewById(R.id.tv_face);
        imageButton = (CustomImageButton) findViewById(R.id.iv_face);
        imageButton.setGravity(Gravity.CENTER_HORIZONTAL | Gravity.CENTER_VERTICAL);
        imageButton2 = (CustomImageButton) findViewById(R.id.iv_face2);
        imageButton2.setGravity(Gravity.CENTER_HORIZONTAL | Gravity.CENTER_VERTICAL);

        mFaceDetector = new ObjectDetector(this, R.raw.haarcascade_frontalface_alt, 6, 0.2F, 0.2F, new Scalar(255, 0, 0, 255));
    }


/**
     * 点击添加照片事件
     *
     * @param v
*/
public void onClick(View v) {

int bt_id = v.getId();
switch (bt_id) {
case R.id.addPic:
// 添加照片
// 打开本地相册
                Intent intent1 = new Intent(Intent.ACTION_PICK, android.provider.MediaStore.Images.Media.EXTERNAL_CONTENT_URI);
                startActivityForResult(intent1, 101);
break;

case R.id.takePhoto:
// 拍照
// 打开本地相机
                Intent intent2 = new Intent(android.provider.MediaStore.ACTION_IMAGE_CAPTURE);
                Uri imageUri = Uri.fromFile(new File(Environment.getExternalStorageDirectory(), CAMERAIMAGENAME));
                intent2.putExtra(MediaStore.EXTRA_OUTPUT, imageUri);
                startActivityForResult(intent2, 102);

break;

case R.id.back:
this.finish();
break;

default:
break;
        }

    }


    @Override
protected void onActivityResult(int requestCode, int resultCode, Intent data) {
super.onActivityResult(requestCode, resultCode, data);
// 加判断 不选择照片或者不拍照时不闪退
//Log.e("data", String.valueOf(data));
//if (data == null)
//return;

        bitmap = null;
switch (requestCode) {
// 选择图片库的图片
case 101:
if (resultCode == RESULT_OK) {
try {
                        Uri uri = data.getData();
                        bitmap = MediaStore.Images.Media.getBitmap(this.getContentResolver(), uri);

                    } catch (Exception e) {
                        e.printStackTrace();
                    }
                }
break;

// 表示调用本地照相机拍照
case 102:
if (resultCode == RESULT_OK) {
//Bundle bundle = data.getExtras();
//bm = (Bitmap) bundle.get("data");
                    bitmap = BitmapFactory.decodeFile(Environment.getExternalStorageDirectory() + "/" + CAMERAIMAGENAME);

                }
break;
default:
break;
        }

        Log.e("bitmap", String.valueOf(bitmap));

if (bitmap == null) {
            toast = Toast.makeText(FaceDetectionOpenCVActivity.this, "未选择图像", Toast.LENGTH_SHORT);
            toast.show();
return;
        }


// 识别图片 并画框
        detectFace();


// 将照片剪裁 bitmap将被释放重新赋值
int ibWidth = imageButton.getWidth();
int ibHeight = imageButton.getHeight();
        resizeBitmap = imageButton.resizeBitmap(bitmap, ibWidth, ibHeight);

        imageButton.setBitmap(resizeBitmap);
        imageButton2.setBitmap(rectBitmap);


    }

private void detectFace() {
try {
// bitmapToMat
            Mat toMat = new Mat();
            Utils.bitmapToMat(bitmap, toMat);
            Mat copyMat = new Mat();
            toMat.copyTo(copyMat); // 复制

// togray
            Mat gray = new Mat();
            Imgproc.cvtColor(toMat, gray, Imgproc.COLOR_RGBA2GRAY);

            MatOfRect mRect = new MatOfRect();
            Rect[] object = mFaceDetector.detectObjectImage(gray, mRect);

            Log.e("objectLength", object.length + "");


int maxRectArea = 0 * 0;
            Rect maxRect = null;

int facenum = 0;
// Draw a bounding box around each face.
for (Rect rect : object) {
                Imgproc.rectangle(
                        toMat,
new Point(rect.x, rect.y),
new Point(rect.x + rect.width, rect.y + rect.height),
new Scalar(255, 0, 0), 3);
++facenum;
// 找出最大的面积
int tmp = rect.width * rect.height;
if (tmp >= maxRectArea) {
                    maxRectArea = tmp;
                    maxRect = rect;
                }
            }

            rectBitmap = null;
if (facenum != 0) {
// 剪切最大的头像
                Log.e("剪切的长宽", String.format("高:%s,宽:%s", maxRect.width, maxRect.height));
                Rect rect = new Rect(maxRect.x, maxRect.y, maxRect.width, maxRect.height);
                Mat rectMat = new Mat(copyMat, rect);  // 从原始图像拿
                rectBitmap = Bitmap.createBitmap(rectMat.cols(), rectMat.rows(), Bitmap.Config.ARGB_8888);
                Utils.matToBitmap(rectMat, rectBitmap);
            }

            textView.setText(String.format("检测到%1$d个人脸", facenum));
            Utils.matToBitmap(toMat, bitmap);


        } catch (Exception e) {
            e.printStackTrace();
        }

    }

}

FaceDetectionOpenCVActivity Android+openCV人脸检测2(静态图片)

package com.opencvlib;

import android.content.Context;

import org.opencv.core.Mat;
import org.opencv.core.MatOfRect;
import org.opencv.core.Rect;
import org.opencv.core.Scalar;
import org.opencv.core.Size;
import org.opencv.objdetect.CascadeClassifier;
import org.opencv.objdetect.Objdetect;

import java.io.File;
import java.io.FileOutputStream;
import java.io.IOException;
import java.io.InputStream;

/**
 * Created by think-hxr on 17-10-12.
*/

public class ObjectDetector {
private CascadeClassifier mCascadeClassifier;
private int mMinNeighbors;
private float mRelativeObjectWidth;
private float mRelativeObjectHeight;
private Scalar mRectColor;

/**
     * 构造方法
     *
     * @param context              上下文
     * @param id                   级联分类器ID
     * @param minNeighbors         连续几帧确认目标
     * @param relativeObjectWidth  最小宽度屏占比
     * @param relativeObjectHeight 最小高度屏占比
     * @param rectColor            画笔颜色
*/
public ObjectDetector(Context context, int id, int minNeighbors, float relativeObjectWidth, float relativeObjectHeight, Scalar rectColor) {
        context = context.getApplicationContext();
        mCascadeClassifier = createDetector(context, id);
        mMinNeighbors = minNeighbors;
        mRelativeObjectWidth = relativeObjectWidth;
        mRelativeObjectHeight = relativeObjectHeight;
        mRectColor = rectColor;
    }

/**
     * 创建检测器
     *
     * @param context 上下文
     * @param id      级联分类器ID
     * @return 检测器
*/
private CascadeClassifier createDetector(Context context, int id) {
        CascadeClassifier javaDetector;
        InputStream is = null;
        FileOutputStream os = null;
try {
            is = context.getResources().openRawResource(id);
            File cascadeDir = context.getDir("cascade", Context.MODE_PRIVATE);
            File cascadeFile = new File(cascadeDir, id + ".xml");
            os = new FileOutputStream(cascadeFile);

byte[] buffer = new byte[4096];
int bytesRead;
while ((bytesRead = is.read(buffer)) != -1) {
                os.write(buffer, 0, bytesRead);
            }

            javaDetector = new CascadeClassifier(cascadeFile.getAbsolutePath());
if (javaDetector.empty()) {
                javaDetector = null;
            }

boolean delete = cascadeDir.delete();
return javaDetector;
        } catch (IOException e) {
            e.printStackTrace();
return null;
        } finally {
try {
if (null != is) {
                    is.close();
                }
if (null != os) {
                    os.close();
                }
            } catch (IOException e) {
                e.printStackTrace();
            }
        }
    }

/**
     * 目标检测 视频
     *
     * @param gray   灰度图像
     * @param object 识别结果的容器
     * @return 检测到的目标位置集合
*/
public Rect[] detectObject(Mat gray, MatOfRect object) {
// 使用Java人脸检测
        mCascadeClassifier.detectMultiScale(
                gray, // 要检查的灰度图像
                object, // 检测到的人脸
                1.1, // 表示在前后两次相继的扫描中，搜索窗口的比例系数。默认为1.1即每次搜索窗口依次扩大10%;
                mMinNeighbors, // 默认是3 控制误检测，表示默认几次重叠检测到人脸，才认为人脸存在
                Objdetect.CASCADE_SCALE_IMAGE,
                getSize(gray, mRelativeObjectWidth, mRelativeObjectHeight), // 目标最小可能的大小
                gray.size()); // 目标最大可能的大小

return object.toArray();
    }

/**
     * 目标检测 图片
     *
     * @param gray   灰度图像
     * @param object 识别结果的容器
     * @return
*/
public Rect[] detectObjectImage(Mat gray, MatOfRect object) {
        mCascadeClassifier.detectMultiScale(gray,object);
return object.toArray();
    }


/**
     * 根据屏占比获取大小
     *
     * @param gray                 gray
     * @param relativeObjectWidth  最小宽度屏占比
     * @param relativeObjectHeight 最小高度屏占比
     * @return 大小
*/
private Size getSize(Mat gray, float relativeObjectWidth, float relativeObjectHeight) {
        Size size = gray.size();
int cameraWidth = gray.cols();
int cameraHeight = gray.rows();
int width = Math.round(cameraWidth * relativeObjectWidth);
int height = Math.round(cameraHeight * relativeObjectHeight);
        size.width = 0 >= width ? 0 : (cameraWidth < width ? cameraWidth : width); // width [0, cameraWidth]
        size.height = 0 >= height ? 0 : (cameraHeight < height ? cameraHeight : height); // height [0, cameraHeight]
return size;
    }

/**
     * 获取画笔颜色
     *
     * @return 颜色
*/
public Scalar getRectColor() {
return mRectColor;
    }
}

ObjectDetector Android+openCV人脸检测2(静态图片)

<?xml version="1.0" encoding="utf-8"?>
<android.support.constraint.ConstraintLayout xmlns:android="http://schemas.android.com/apk/res/android"
    xmlns:app="http://schemas.android.com/apk/res-auto"
    xmlns:tools="http://schemas.android.com/tools"
    android:layout_width="match_parent"
    android:layout_height="match_parent"
    tools:context="com.myproject.facedetection.ui.FaceDetectionOpenCVActivity">

<com.myproject.facedetection.entity.CustomImageButton
android:id="@+id/iv_face"
        android:layout_width="0dp"
        android:layout_height="460dp"
        android:layout_marginLeft="10dp"
        android:layout_marginRight="10dp"
        app:layout_constraintLeft_toLeftOf="parent"
        app:layout_constraintRight_toRightOf="parent"
        tools:layout_editor_absoluteY="10dp" />


<com.myproject.facedetection.entity.CustomImageButton
android:id="@+id/iv_face2"
        android:layout_width="100dp"
        android:layout_height="100dp"
        android:layout_marginRight="10dp"
        app:layout_constraintRight_toRightOf="parent"
        tools:layout_editor_absoluteY="10dp" />


<TextView
android:id="@+id/tv_face"
        android:layout_width="wrap_content"
        android:layout_height="wrap_content"
        android:layout_marginBottom="16dp"
        android:text="未检测到人脸"
        android:textColor="@color/colorAccent"
        app:layout_constraintBottom_toTopOf="@+id/ll1"
        app:layout_constraintLeft_toLeftOf="parent"
        app:layout_constraintRight_toRightOf="parent" />

<LinearLayout
android:id="@+id/ll1"
        android:layout_width="0dp"
        android:layout_height="wrap_content"
        android:orientation="horizontal"
        app:layout_constraintBottom_toBottomOf="parent"
        app:layout_constraintLeft_toLeftOf="parent"
        app:layout_constraintRight_toRightOf="parent">

<Button
android:id="@+id/takePhoto"
            android:layout_width="wrap_content"
            android:layout_height="wrap_content"
            android:layout_marginBottom="5dp"
            android:layout_weight="1"
            android:onClick="onClick"
            android:text="拍照(CV)"
            android:textSize="16sp"
            app:layout_constraintLeft_toLeftOf="parent"
            app:layout_constraintRight_toRightOf="parent" />

<Button
android:id="@+id/addPic"
            android:layout_width="wrap_content"
            android:layout_height="wrap_content"
            android:layout_marginBottom="5dp"
            android:layout_weight="1"
            android:onClick="onClick"
            android:text="选择图片(CV)"
            android:textSize="16sp"
            app:layout_constraintLeft_toLeftOf="parent"
            app:layout_constraintRight_toRightOf="parent" />

<Button
android:id="@+id/back"
            android:layout_width="wrap_content"
            android:layout_height="wrap_content"
            android:layout_marginBottom="0dp"
            android:layout_weight="1"
            android:onClick="onClick"
            android:text="返回(CV)"
            android:textSize="16sp"
            app:layout_constraintLeft_toLeftOf="parent"
            app:layout_constraintRight_toRightOf="parent" />
</LinearLayout>


</android.support.constraint.ConstraintLayout>

activity_face_detection_opencv.xml

秒客网

Android+openCV人脸检测2(静态图片)

一首先导入openCVLibrary320

二设置gradle的sdk版本号与当前项目一致

三新建 jniLibs 目录

四加载so包

五添加xml级联分类器

六配置权限

使用openCV

相关文章

Android+openCV人脸检测2(静态图片)

一 首先导入openCVLibrary320

二 设置gradle的sdk版本号与当前项目一致

三 新建 jniLibs 目录

四 加载so包

五 添加xml级联分类器

六 配置权限

使用openCV

相关文章

一首先导入openCVLibrary320

二设置gradle的sdk版本号与当前项目一致

三新建 jniLibs 目录

四加载so包

五添加xml级联分类器

六配置权限