在opencv的面罩 [英] Face mask in opencv
问题描述
输入：面部图片
希望的输出如果输入不同的面部，它应该生成一个适当的面罩（面部区域白色和背景白色） >
尝试与苹果图片...工作精细
#include< opencv2 / highgui / highgui.hpp>
#include< opencv2 / core / core.hpp>
#include< opencv2 / imgproc / imgproc.hpp>
using namespace cv;
using namespace std;
int main（）{
Mat right = imread（front.jpg）;
Mat img1;
cvtColor（right，img1，CV_RGB2GRAY）;
threshold（img1，img1,160,255，cv :: THRESH_BINARY）;
Canny（img1，img1，128，350）;
vector<向量< Point> >轮廓;
findContours（img1，contoururs，CV_RETR_EXTERNAL，CV_CHAIN_APPROX_NONE）;
Mat mask = Mat :: zeros（img1.rows，img1.cols，CV_8UC1）;
drawContours（mask，contoururs，-1，Scalar（255），CV_FILLED）;
normalize（mask.clone（），mask，0.0，255.0，CV_MINMAX，CV_8UC1）;
imshow（original，right）;
imshow（thresh，img1）;
imshow（mask，mask）;
waitKey（0）;
return 0;
}
这是我使用的图片
>
请忽略以下前3条评论
这里假设您的背景是任何颜色，没有其他对象。
b以下代码将执行
>通过形态操作加强边缘。
在边缘中找到最大轮廓（始终是前景的边界） ul>
有时你的轮廓可能不会在底部关闭（底部没有边缘），所以填充轮廓不工作，所以为了使它关闭代码首先找到边界rect为最大轮廓（前景），然后绘制底部的矩形到边缘图像，然后找到最大的轮廓，将给你正确的掩码图像。
Rect R;
Mat findLargestContour（Mat thr）{
vector<向量< Point> >轮廓; //用于存储轮廓的向量
向量< Vec4i>层次;
int largest_contour_index = 0;
int largest_area = 0;
Mat dst（thr.rows，thr.cols，CV_8UC1，Scalar :: all（0））; // create destination image
findContours（thr，contour，hierarchy，CV_RETR_EXTERNAL，CV_CHAIN_APPROX_SIMPLE）;
for（int i = 0; i
double a = contourArea（contoururs [i]，false）; //找到轮廓的区域
if（a> largest_area）{
highest_area = a;
largest_contour_index = i; //存储最大轮廓的索引
}
}
drawContours（dst，contours，largest_contour_index，Scalar（255,255,255），CV_FILLED，8，
R = boundingRect（contoururs [largest_contour_index]）;
return dst;
}
int main（）
{
Mat right = imread（1.jpg）;
// blur（right，right，Size（3,3））;
Mat gray;
cvtColor（right，gray，CV_RGB2GRAY）;
int borderW = 10;
// Mat ROI = gray（Rect（borderW，borderW，img1.cols-2 * borderW，img1.rows-2 * borderW））;
Canny（灰色，灰色，30，255）;
size kernalSize（5,5）;
Mat element = getStructuringElement（MORPH_RECT，kernalSize，Point（1,1））;
morphologyEx（gray，gray，MORPH_CLOSE，element）;
imshow（canny，gray）;
Mat largestCon = findLargestContour（gray.clone（））;
line（largestCon，Point（Rx，R.y + R.height），Point（R.x + R.width，R.y + R.height），Scalar（255），2,8,0 ）;
Mat mask = findLargestContour（largestCon.clone（））;
Mat A;
right.copyTo（A，mask）;
imshow（original，right）;
imshow（dst，A）;
imshow（mask，mask）;
waitKey（0）;
return 0;
}
查看一些示例面具
Input: face image
Problem: thresholded image before applying Canny to find contours but does not return face mask
Desired output if different face is input,it should generate a proper face mask(face area white and background white)
Tried with apple picture..works fine
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/core/core.hpp>
#include <opencv2/imgproc/imgproc.hpp>
using namespace cv;
using namespace std;
int main(){
Mat right=imread("front.jpg");
Mat img1;
cvtColor(right, img1, CV_RGB2GRAY);
threshold(img1,img1,160,255,cv::THRESH_BINARY);
Canny(img1, img1, 128, 350);
vector< vector<Point> > contours;
findContours(img1, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);
Mat mask = Mat::zeros(img1.rows, img1.cols, CV_8UC1);
drawContours(mask, contours, -1, Scalar(255), CV_FILLED);
normalize(mask.clone(), mask, 0.0, 255.0, CV_MINMAX, CV_8UC1);
imshow("original", right);
imshow("thresh",img1);
imshow("mask", mask);
waitKey(0);
return 0;
}
Here is the image that I used
Please ignore the first 3 comments below
Using this below code the mask creation working perfectly for the sample image you provided in the above commants.
Here assumes, your background is of any colour with no other object.
The below code will do
Find edge
Strengthen the edge by morphology operation.
Find biggest contour in edge( always the boundary of your foreground ) and draw it by filling.
Sometimes your contour may not be closed at the bottom(no edges at bottom) so the filling contour wont work, so for make it closed the code first find the bounding rect for biggest contour(foreground) and then draw bottom of rect to the edge image, then find largest contour again will give you the proper mask image.
Rect R;
Mat findLargestContour(Mat thr){
vector< vector <Point> > contours; // Vector for storing contour
vector< Vec4i > hierarchy;
int largest_contour_index=0;
int largest_area=0;
Mat dst(thr.rows,thr.cols,CV_8UC1,Scalar::all(0)); //create destination image
findContours( thr, contours, hierarchy,CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE );
for( int i = 0; i< contours.size(); i++ ) // iterate through each contour.
{
double a=contourArea( contours[i],false); // Find the area of contour
if(a>largest_area){
largest_area=a;
largest_contour_index=i; //Store the index of largest contour
}
}
drawContours( dst,contours, largest_contour_index, Scalar(255,255,255),CV_FILLED, 8, hierarchy );
R= boundingRect( contours[largest_contour_index]);
return dst;
}
int main( )
{
Mat right=imread("1.jpg");
// blur(right,right,Size(3,3));
Mat gray;
cvtColor(right, gray, CV_RGB2GRAY);
int borderW=10;
//Mat ROI=gray(Rect(borderW,borderW,img1.cols-2*borderW,img1.rows-2*borderW));
Canny(gray, gray, 30, 255);
Size kernalSize (5,5);
Mat element = getStructuringElement (MORPH_RECT, kernalSize, Point(1,1) );
morphologyEx(gray, gray, MORPH_CLOSE, element );
imshow("canny", gray);
Mat largestCon=findLargestContour(gray.clone());
line(largestCon, Point(R.x,R.y+R.height), Point(R.x+R.width,R.y+R.height), Scalar(255),2,8,0);
Mat mask=findLargestContour(largestCon.clone());
Mat A;
right.copyTo(A,mask);
imshow("original", right);
imshow("dst", A);
imshow("mask", mask);
waitKey(0);
return 0;
}
See some sample mask
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