目录
效果展示
相关文章及项目
这里的程序是以我的这篇文章为基础的：Android NDK开发：Opencv实现人脸识别
这里我参考了这个项目：https://github.com/hpc203/FaceMaskDetection-dnn，用的这个项目里面的C语言部分的代码和dnn模型数据，移植到了Android上
实现步骤
1.创建人脸框类
这里创建一个用于存储人脸框和是否佩戴口罩的类用于绘制
public class FaceMaskBean {
private int isMask = 0;//是否戴口罩了，0没戴，1戴了
private Rect faceRect;//人脸框
public FaceMaskBean(int isMask, Rect faceRect) {
this.isMask = isMask;
this.faceRect = faceRect;
}
public int getIsMask() {
return isMask;
}
public void setIsMask(int isMask) {
this.isMask = isMask;
}
public Rect getFaceRect() {
return faceRect;
}
public void setFaceRect(Rect faceRect) {
this.faceRect = faceRect;
}
}
2.修改JNI返回类型
与Android NDK开发：Opencv实现人脸识别中的代码相比，修改NativeUtil中ndkCheckFace函数的返回类型为FaceMaskBean类型的数组
object NativeUtil {
init {
System.loadLibrary("NDKInterface")
System.loadLibrary("opencv_java4")
}
/**
* 加载模型
*/
external fun ndkInit(protoTxtFilePath:String,modelFilePath:String)
/**
* 人脸检测
*/
external fun ndkCheckFace(yuvData:ByteArray,rotation:Int,width:Int,height:Int):Array<FaceMaskBean>
}
3.移植戴口罩识别代码
这里我把文章开头提到的项目中的代码做了如下修改
FaceMask.h
#ifndef OPENCVCHECKFACE_FACEMASK_H
#define OPENCVCHECKFACE_FACEMASK_H
#include <iostream>
#include <opencv2/dnn.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/highgui.hpp>
#include <math.h>
#include <jni.h>
using namespace cv;
using namespace dnn;
using namespace std;
class FaceMask {
public:
FaceMask(const float conf_thresh = 0.5, const float iou_thresh = 0.4);
jobjectArray detect(Mat &srcimg,JNIEnv* &env);
private:
const int feature_map_sizes[5][2] = {{33, 33}, {17, 17}, {9, 9}, {5, 5}, {3, 3}};
const float anchor_sizes[5][2] = {{0.04, 0.056}, {0.08, 0.11}, {0.16, 0.22}, {0.32, 0.45}, {0.64, 0.72}};
const float anchor_ratios[3] = {1, 0.62, 0.42};
const float variances[4] = {0.1, 0.1, 0.2, 0.2};
float conf_thresh;
float iou_thresh;
const Size target_shape = Size(260, 260);
const int num_prior = 5972;
float* prior_data;
Net net;
void generate_priors();
void decode(Mat loc, Mat conf, vector<Rect>& boxes, vector<float>& confidences, vector<int>& classIds, const int srcimg_h, const int srcimg_w);
};
#endif //OPENCVCHECKFACE_FACEMASK_H
FaceMask.cpp，其中模型数据我为了方便直接手动拷贝到了SD卡中，然后直接用路径加载的
#include "FaceMask.h"
FaceMask::FaceMask(const float conf_thresh, const float iou_thresh)
{
this->conf_thresh = conf_thresh;
this->iou_thresh = iou_thresh;
this->net = readNet("/storage/emulated/0/Android/data/com.itfitness.opencvcheckface/files/Download/face_mask_detection.caffemodel"
, "/storage/emulated/0/Android/data/com.itfitness.opencvcheckface/files/Download/face_mask_detection.prototxt");
this->generate_priors();
}
void FaceMask::generate_priors()
{
this->prior_data = new float[this->num_prior *4];
float* pdata = prior_data;
int i = 0, j = 0, h = 0, w = 0;
float height = 0, width = 0, ratio = 0;
for (i = 0; i < 5; i++)
{
const int feature_map_height = this->feature_map_sizes[i][0];
const int feature_map_width = this->feature_map_sizes[i][1];
for (h = 0; h < feature_map_height; h++)
{
for (w = 0; w < feature_map_width; w++)
{
ratio = sqrt(this->anchor_ratios[0]);
for(j=0;j<2;j++)
{
width = this->anchor_sizes[i][j] * ratio;
height = this->anchor_sizes[i][j] / ratio;
// pdata[0] = (w + 0.5) / feature_map_width - 0.5 * width; ///xmin
// pdata[1] = (h + 0.5) / feature_map_height - 0.5 * height; ////ymin
// pdata[2] = (w + 0.5) / feature_map_width + 0.5 * width; ///xmax
// pdata[3] = (h + 0.5) / feature_map_height + 0.5 * height; ////ymax
pdata[0] = (w + 0.5) / feature_map_width; ///center_x
pdata[1] = (h + 0.5) / feature_map_height; ////center_y
pdata[2] = width; ///width
pdata[3] = height; ////height
pdata += 4;
}
for(j=0;j<2;j++)
{
ratio = sqrt(this->anchor_ratios[j+1]);
width = this->anchor_sizes[i][0] * ratio;
height = this->anchor_sizes[i][0] / ratio;
// pdata[0] = (w + 0.5) / feature_map_width - 0.5 * width; ///xmin
// pdata[1] = (h + 0.5) / feature_map_height - 0.5 * height; ////ymin
// pdata[2] = (w + 0.5) / feature_map_width + 0.5 * width; ///xmax
// pdata[3] = (h + 0.5) / feature_map_height + 0.5 * height; ////ymax
pdata[0] = (w + 0.5) / feature_map_width; ///center_x
pdata[1] = (h + 0.5) / feature_map_height; ////center_y
pdata[2] = width; ///width
pdata[3] = height; ////height
pdata += 4;
}
}
}
}
}
void FaceMask::decode(Mat loc, Mat conf, vector<Rect>& boxes, vector<float>& confidences, vector<int>& classIds, const int srcimg_h, const int srcimg_w)
{
if(loc.dims==3)
{
loc = loc.reshape(0, this->num_prior);
}
if(conf.dims==3)
{
conf = conf.reshape(0, this->num_prior);
}
float predict_xmin = 0, predict_ymin = 0, predict_w = 0, predict_h = 0;
int srcimg_xmin = 0, srcimg_ymin = 0;
int i = 0;
for(i=0;i<this->num_prior;i++)
{
Mat scores = conf.row(i).colRange(0, 2);
Point classIdPoint;
double score;
// Get the value and location of the maximum score
minMaxLoc(scores, 0, &score, 0, &classIdPoint);
if (score>this->conf_thresh)
{
const int row_ind = i * 4;
const float* pbox = (float*)loc.data + row_ind;
predict_w = exp(pbox[2] * this->variances[2]) * this->prior_data[row_ind + 2];
predict_h = exp(pbox[3] * this->variances[3]) * this->prior_data[row_ind + 3];
predict_xmin = pbox[0] * this->variances[0] * this->prior_data[row_ind + 2] + this->prior_data[row_ind] - 0.5 * predict_w;
predict_ymin = pbox[1] * this->variances[1] * this->prior_data[row_ind + 3] + this->prior_data[row_ind + 1] - 0.5 * predict_h;
classIds.push_back(classIdPoint.x);
confidences.push_back(score);
srcimg_xmin = (int)max(predict_xmin * srcimg_w, 0.f);
srcimg_ymin = (int)max(predict_ymin * srcimg_h, 0.f);
boxes.push_back(Rect(srcimg_xmin, srcimg_ymin, (int)(predict_w * srcimg_w), (int)(predict_h * srcimg_h)));
}
}
}
jobjectArray FaceMask::detect(Mat &srcimg,JNIEnv* &env)
{
int height = srcimg.rows;
int width = srcimg.cols;
Mat blob = blobFromImage(srcimg, 1/255.0, this->target_shape);
this->net.setInput(blob);
vector<Mat> outs;
this->net.forward(outs, this->net.getUnconnectedOutLayersNames());
////post process
vector<int> classIds;
vector<float> confidences;
vector<Rect> boxes;
this->decode(outs[0], outs[1], boxes, confidences, classIds, height, width);
vector<int> indices;
NMSBoxes(boxes, confidences, this->conf_thresh, this->iou_thresh, indices);
jclass faceMaskBeanCls = env->FindClass("com/itfitness/opencvcheckface/FaceMaskBean");
jmethodID faceMaskBean_construct = env->GetMethodID(faceMaskBeanCls, "<init>","(ILandroid/graphics/Rect;)V"); //Rect的构造函数
jclass rectCls = env->FindClass("android/graphics/Rect");
jmethodID rect_construct = env->GetMethodID(rectCls, "<init>", "(IIII)V"); //Rect的构造函数
jobjectArray faceRectArray = env->NewObjectArray(indices.size(),faceMaskBeanCls,nullptr);
for (size_t i = 0; i < indices.size(); ++i)
{
int idx = indices[i];
Rect box = boxes[idx];
if(classIds[idx]==1)
{
// rectangle(srcimg, Point(box.x, box.y), Point(box.x + box.width, box.y + box.height), Scalar(0, 0, 255), 2);
// putText(srcimg, "No mask", Point(box.x, box.y -10), FONT_HERSHEY_SIMPLEX, 0.75, Scalar(0, 0, 255), 1);
jobject rect = env->NewObject(rectCls,rect_construct,box.x,box.y,box.x + box.width,box.y + box.height);
jobject faceMaskBean = env->NewObject(faceMaskBeanCls,faceMaskBean_construct,0,rect);
env->SetObjectArrayElement(faceRectArray,i,faceMaskBean);
}
else
{
// rectangle(srcimg, Point(box.x, box.y), Point(box.x + box.width, box.y + box.height), Scalar(0, 255, 0), 2);
// putText(srcimg, "wear mask", Point(box.x, box.y -10), FONT_HERSHEY_SIMPLEX, 0.75, Scalar(0, 255, 0), 1);
jobject rect = env->NewObject(rectCls,rect_construct,box.x,box.y,box.x + box.width,box.y + box.height);
jobject faceMaskBean = env->NewObject(faceMaskBeanCls,faceMaskBean_construct,1,rect);
env->SetObjectArrayElement(faceRectArray,i,faceMaskBean);
}
}
return faceRectArray;
}
NDK的ndkCheckFace函数也进行了修改，如下所示：
extern "C"
JNIEXPORT jobjectArray JNICALL
Java_com_itfitness_opencvcheckface_NativeUtil_ndkCheckFace(JNIEnv *env, jobject thiz,
jbyteArray yuv_data, jint rotation,jint width,jint height) {
jbyte *yuvBuffer = (jbyte *) env->GetByteArrayElements(yuv_data, JNI_FALSE);
Mat imageSrc(height + height / 2, width, CV_8UC1, (unsigned char *) yuvBuffer);
Mat bgrCVFrame;
cvtColor(imageSrc, bgrCVFrame, cv::COLOR_YUV2BGR_NV21);
rotateMat(bgrCVFrame,rotation);
return modelMask.detect(bgrCVFrame,env);
}
