Opencv实现去除背景留下前景
最近要用DN跑UCF101数据集，看了王东曙教授的论文 Developmental Network: An Internal Emergent Object Feature Learning
里面用抑制了背景的人脸图像给DN去做识别，有93.51%的识别率。然后就想着用抑制了背景的UCF101数据集给DN做动作识别
会怎么样。
抑制了背景的人脸如下图：
实验结果如下图：
然后就想用DN跑UCF101试试效果。下面进入正题：
opencv函数太多了，不过常用的还是应该记住。
1、 line() 函数
void line(Mat& img, Point pt1, Point pt2, const Scalar& color, int thickness=1, int lineType=8, int shift=0)
/**参数含义：
img: on which you are going to draw.
pt1: start point of the line
pt2: end point of the line
color: the color of the line you are going to draw
thickness: the width of the line
lineType: the type of the line .(smooth or Anti-sawtooth)
shift:decimal number of the cordinate */
2、cvSetMouseCallback()
void cvSetMouseCallback(const char* window_name, CvMouseCallback on_mouse, void* param=NULL ); window_name: 回调函数需要注册到的窗口的name，也就是产生事件的window
on_mouse: 指定窗口里每次鼠标事件发生的时候，被调用的函数指针（注：这个变量是一个函数指针（地址））
3、实验效果
#include
#include
#include
#include
#include
#include
using namespace std;
using namespace cv;
CvPoint prev_pt = { -1, -1 };
Mat img;
Mat img_mask;
Mat dst;
void on_mouse(int event, int x, int y, int flags, void*)
{
if (!img.data)
return;
if (event == CV_EVENT_LBUTTONUP || !(flags & CV_EVENT_FLAG_LBUTTON)) //判断事件为松开鼠标左键或者不是左拖拽
{
prev_pt = cvPoint(-1, -1);
}
else if (event == CV_EVENT_LBUTTONDOWN) //判断为按下左键
{
prev_pt = cvPoint(x, y);
}
else if (event == CV_EVENT_MOUSEMOVE && (flags & CV_EVENT_FLAG_LBUTTON)) //判断移动鼠标并且左拖拽
{
CvPoint pt = cvPoint(x, y);
if (prev_pt.x < 0)
{
prev_pt = pt;
}
line(img_mask, prev_pt, pt, Scalar(0), 2, 8, 0); //模板上划线
line(img, prev_pt, pt, Scalar::all(255), 2, 8, 0); //原图上划线
prev_pt = pt;
imshow("image", img);
}
if (event == CV_EVENT_RBUTTONUP) //如果鼠标右键点击图片
{
floodFill(img_mask, Point(x, y), Scalar(0));//填充抠图模板
/*imshow("img_mask", img_mask);*/
img.copyTo(dst, img_mask);
imshow("dst", dst);
imwrite("E:/Cpp_Test/get_foreground/ConsoleApplication2/image_mask.png", img_mask);
}
}
int main(int argc, char * argv[])
{
Mat image = imread("E:/Cpp_Test/get_foreground/ConsoleApplication2/gray.png");
image.copyTo(img);
//将模板设置成白色
img_mask.create(img.rows, img.cols, CV_8U);
img_mask.setTo(Scalar(255));
//显示原图
imshow("image", img);
////显示模板原图
//imshow("watershed transform", img_mask);
//鼠标回调函数
cvSetMouseCallback("image", on_mouse, 0);
waitKey(0);
imwrite("E:/Cpp_Test/get_foreground/ConsoleApplication2/image.png",img);
return 0;
}
