/*!
* file Capture.cpp
*
* author ranjiewen
* date 十一月 2016
*
* http://www.cnblogs.com/tanfy/p/5552270.html
解析opencv自带人脸识别源码(……/opencv-3.1.0/samples/cpp/facedetect.cpp)
*/
#include "opencv2/objdetect.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"
#include <iostream>
using namespace std;
using namespace cv;
static void help()
{
cout << "
This program demonstrates the cascade recognizer. Now you can use Haar or LBP features.
"
"This classifier can recognize many kinds of rigid objects, once the appropriate classifier is trained.
"
"It's most known use is for faces.
"
"Usage:
"
"./facedetect [--cascade=<cascade_path> this is the primary trained classifier such as frontal face]
"
" [--nested-cascade[=nested_cascade_path this an optional secondary classifier such as eyes]]
"
" [--scale=<image scale greater or equal to 1, try 1.3 for example>]
"
" [--try-flip]
"
" [filename|camera_index]
"
"see facedetect.cmd for one call:
"
"./facedetect --cascade="../../data/haarcascades/haarcascade_frontalface_alt.xml" --nested-cascade="../../data/haarcascades/haarcascade_eye_tree_eyeglasses.xml" --scale=1.3
"
"During execution:
Hit any key to quit.
"
" Using OpenCV version " << CV_VERSION << "
" << endl;
}
void detectAndDraw(Mat& img, CascadeClassifier& cascade,
CascadeClassifier& nestedCascade,
double scale, bool tryflip);
string cascadeName;
string nestedCascadeName;
int main(int argc, const char** argv)
{
VideoCapture capture;
Mat frame, image;
string inputName;
bool tryflip;
// CascadeClassifier是Opencv中做人脸检测的时候的一个级联分类器,现在有两种选择:一是使用老版本的CvHaarClassifierCascade函数,一是使用新版本的CascadeClassifier类。老版本的分类器只支持类Haar特征,而新版本的分类器既可以使用Haar,也可以使用LBP特征。
CascadeClassifier cascade, nestedCascade;
double scale;
cv::CommandLineParser parser(argc, argv,
"{help h||}"
"{cascade|D:/opencv/sources/data/haarcascades/haarcascade_frontalface_alt.xml|}" //默认路径实在安装路径下sample,修改了路径,以便加载load成功
"{nested-cascade|D:/opencv/sources/data/haarcascades/haarcascade_eye_tree_eyeglasses.xml|}" //修改路径
"{scale|1|}{try-flip||}{@filename||}" //文件为空时,设置摄像头,实时检测人脸
);
if (parser.has("help"))
{
help();
return 0;
}
cascadeName = parser.get<string>("cascade");
nestedCascadeName = parser.get<string>("nested-cascade");
scale = parser.get<double>("scale");
if (scale < 1)
scale = 1;
tryflip = parser.has("try-flip");
inputName = parser.get<string>("@filename");
std::cout << inputName << std::endl; // test
if (!parser.check())
{
parser.printErrors();
return 0;
}
// 加载模型
if (!nestedCascade.load(nestedCascadeName))
cerr << "WARNING: Could not load classifier cascade for nested objects" << endl;
if (!cascade.load(cascadeName))
{
cerr << "ERROR: Could not load classifier cascade" << endl;
help();
return -1;
}
// 读取摄像头
// isdigit检测字符是否为阿拉伯数字
if (inputName.empty() || (isdigit(inputName[0]) && inputName.size() == 1))
{
int c = inputName.empty() ? 0 : inputName[0] - '0';
// 此处若系统在虚拟机上,需在虚拟机中设置接管摄像头:虚拟机(M)-> 可移动设备 -> 摄像头名称 -> 连接(断开与主机连接)
if (!capture.open(c))
cout << "Capture from camera #" << c << " didn't work" << endl;
else {
capture.set(CV_CAP_PROP_FRAME_WIDTH, 640);
capture.set(CV_CAP_PROP_FRAME_HEIGHT, 480);
}
}
else if (inputName.size())
{
image = imread(inputName, 1);
if (image.empty())
{
if (!capture.open(inputName))
cout << "Could not read " << inputName << endl;
}
}
else
{
image = imread("../data/lena.jpg", 1);
if (image.empty()) cout << "Couldn't read ../data/lena.jpg" << endl;
}
if (capture.isOpened())
{
cout << "Video capturing has been started ..." << endl;
for (;;)
{
std::cout << "capturing..." << std::endl; // test
capture >> frame;
if (frame.empty())
break;
Mat frame1 = frame.clone();
std::cout << "Start to detect..." << std::endl; // test
detectAndDraw(frame1, cascade, nestedCascade, scale, tryflip);
int c = waitKey(10);
if (c == 27 || c == 'q' || c == 'Q')
break;
}
}
else
{
cout << "Detecting face(s) in " << inputName << endl;
if (!image.empty())
{
detectAndDraw(image, cascade, nestedCascade, scale, tryflip);
waitKey(0);
}
else if (!inputName.empty())
{
/* assume it is a text file containing the
list of the image filenames to be processed - one per line */
FILE* f = fopen(inputName.c_str(), "rt");
if (f)
{
char buf[1000 + 1];
while (fgets(buf, 1000, f))
{
int len = (int)strlen(buf), c;
while (len > 0 && isspace(buf[len - 1]))
len--;
buf[len] = ' ';
cout << "file " << buf << endl;
image = imread(buf, 1);
if (!image.empty())
{
detectAndDraw(image, cascade, nestedCascade, scale, tryflip);
c = waitKey(0);
if (c == 27 || c == 'q' || c == 'Q')
break;
}
else
{
cerr << "Aw snap, couldn't read image " << buf << endl;
}
}
fclose(f);
}
}
}
return 0;
}
void detectAndDraw(Mat& img, CascadeClassifier& cascade,
CascadeClassifier& nestedCascade,
double scale, bool tryflip)
{
double t = 0;
vector<Rect> faces, faces2;
const static Scalar colors[] =
{
Scalar(255, 0, 0),
Scalar(255, 128, 0),
Scalar(255, 255, 0),
Scalar(0, 255, 0),
Scalar(0, 128, 255),
Scalar(0, 255, 255),
Scalar(0, 0, 255),
Scalar(255, 0, 255)
};
Mat gray, smallImg;
cvtColor(img, gray, COLOR_BGR2GRAY);
double fx = 1 / scale;
resize(gray, smallImg, Size(), fx, fx, INTER_LINEAR);
equalizeHist(smallImg, smallImg);
t = (double)cvGetTickCount();
cascade.detectMultiScale(smallImg, faces,
1.1, 2, 0
//|CASCADE_FIND_BIGGEST_OBJECT
//|CASCADE_DO_ROUGH_SEARCH
| CASCADE_SCALE_IMAGE,
Size(30, 30));
if (tryflip)
{
flip(smallImg, smallImg, 1);
cascade.detectMultiScale(smallImg, faces2,
1.1, 2, 0
//|CASCADE_FIND_BIGGEST_OBJECT
//|CASCADE_DO_ROUGH_SEARCH
| CASCADE_SCALE_IMAGE,
Size(30, 30));
for (vector<Rect>::const_iterator r = faces2.begin(); r != faces2.end(); r++)
{
faces.push_back(Rect(smallImg.cols - r->x - r->width, r->y, r->width, r->height));
}
}
t = (double)cvGetTickCount() - t;
printf("detection time = %g ms
", t / ((double)cvGetTickFrequency()*1000.));
for (size_t i = 0; i < faces.size(); i++)
{
Rect r = faces[i];
Mat smallImgROI;
vector<Rect> nestedObjects;
Point center;
Scalar color = colors[i % 8];
int radius;
double aspect_ratio = (double)r.width / r.height;
if (0.75 < aspect_ratio && aspect_ratio < 1.3)
{
center.x = cvRound((r.x + r.width*0.5)*scale);
center.y = cvRound((r.y + r.height*0.5)*scale);
radius = cvRound((r.width + r.height)*0.25*scale);
circle(img, center, radius, color, 3, 8, 0);
}
else
rectangle(img, cvPoint(cvRound(r.x*scale), cvRound(r.y*scale)),
cvPoint(cvRound((r.x + r.width - 1)*scale), cvRound((r.y + r.height - 1)*scale)),
color, 3, 8, 0);
if (nestedCascade.empty())
continue;
smallImgROI = smallImg(r);
nestedCascade.detectMultiScale(smallImgROI, nestedObjects,
1.1, 2, 0
//|CASCADE_FIND_BIGGEST_OBJECT
//|CASCADE_DO_ROUGH_SEARCH
//|CASCADE_DO_CANNY_PRUNING
| CASCADE_SCALE_IMAGE,
Size(30, 30));
for (size_t j = 0; j < nestedObjects.size(); j++)
{
Rect nr = nestedObjects[j];
center.x = cvRound((r.x + nr.x + nr.width*0.5)*scale);
center.y = cvRound((r.y + nr.y + nr.height*0.5)*scale);
radius = cvRound((nr.width + nr.height)*0.25*scale);
circle(img, center, radius, color, 3, 8, 0);
}
}
imshow("result", img);
}
/*****************************************************
* file Capture.cpp
* date 2016/11/10 0:22
* author ranjiewen
* contact: ranjiewen@outlook.com
* 问题描述:
http://www.cnblogs.com/lingshaohu/archive/2011/12/16/2290017.html
* 问题分析:
可以存avi,但是不能打开,待改善
*****************************************************/
//#include <iostream>
//#include <opencv2/opencv.hpp>
//using namespace cv;;
//using namespace std;
//int main()
//{
// CvCapture* capture = cvCaptureFromCAM(-1);
// CvVideoWriter* video = NULL;
// IplImage* frame = NULL;
// int n;
// if (!capture) //如果不能打开摄像头给出警告
// {
// cout << "Can not open the camera." << endl;
// return -1;
// }
// else
// {
// frame = cvQueryFrame(capture); //首先取得摄像头中的一帧
// video = cvCreateVideoWriter("camera.avi", CV_FOURCC('X', 'V', 'I', 'D'), 25,
// cvSize(frame->width, frame->height)); //创建CvVideoWriter对象并分配空间
// //保存的文件名为camera.avi,编码要在运行程序时选择,大小就是摄像头视频的大小,帧频率是32
// if (video) //如果能创建CvVideoWriter对象则表明成功
// {
// cout << "VideoWriter has created." << endl;
// }
//
// cvNamedWindow("Camera Video", 1); //新建一个窗口
// int i = 0;
// while (i <= 300) // 让它循环200次自动停止录取
// {
// frame = cvQueryFrame(capture); //从CvCapture中获得一帧
// if (!frame)
// {
// cout << "Can not get frame from the capture." << endl;
// break;
// }
// n = cvWriteFrame(video, frame); //判断是否写入成功,如果返回的是1,表示写入成功
// cout << n << endl;
// cvShowImage("Camera Video", frame); //显示视频内容的图片
// i++;
// if (cvWaitKey(2) > 0)
// break; //有其他键盘响应,则退出
// }
//
// cvReleaseVideoWriter(&video);
// cvReleaseCapture(&capture);
// cvDestroyWindow("Camera Video");
// }
// return 0;
//}
