前段時間看的OpenCV，其實有很多的例子程序，參考代碼值得我們學習，對圖像特征提取三大法寶：HOG特征，LBP特征，Haar特征有一定了解後。
對本文中的例子程序剛開始沒有調通，今晚上調通了，試了試效果還可以，還需要深入理解。值得大家動手試試，還是很有成就感的，雖然是現成的例子.......
環境：OpenCV3.1+VS2013+WIN10
/*!
* \file Capture.cpp
*
* \author ranjiewen
* \date 十一月 2016
*http://www.linuxidc.com/Linux/2016-11/137099.htm
解析opencv自帶人臉識別源碼（……/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 << "\nThis program demonstrates the cascade recognizer. Now you can use Haar or LBP features.\n"
"This classifier can recognize many kinds of rigid objects, once the appropriate classifier is trained.\n"
"It's most known use is for faces.\n"
"Usage:\n"
"./facedetect [--cascade=<cascade_path> this is the primary trained classifier such as frontal face]\n"
" [--nested-cascade[=nested_cascade_path this an optional secondary classifier such as eyes]]\n"
" [--scale=<image scale greater or equal to 1, try 1.3 for example>]\n"
" [--try-flip]\n"
" [filename|camera_index]\n\n"
"see facedetect.cmd for one call:\n"
"./facedetect --cascade=\"../../data/haarcascades/haarcascade_frontalface_alt.xml\" --nested-cascade=\"../../data/haarcascades/haarcascade_eye_tree_eyeglasses.xml\" --scale=1.3\n\n"
"During execution:\n\tHit any key to quit.\n"
"\tUsing OpenCV version " << CV_VERSION << "\n" << 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中做人臉檢測的時候的一個級聯分類器，現在有兩種選擇：一是使用老版本的CvHaarClassifierCascade函數，一是使用新版本的CascadeClassifier類。老版本的分類器只支持類Haar特征，而新版本的分類器既可以使用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|}" //默認路徑實在安裝路徑下sample，修改了路徑，以便加載load成功
"{nested-cascade|D:/opencv/sources/data/haarcascades/haarcascade_eye_tree_eyeglasses.xml|}" //修改路徑
"{scale|1|}{try-flip||}{@filename||}" //文件為空時，設置攝像頭，實時檢測人臉
);
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;
}
// 加載模型
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;
}
// 讀取攝像頭
// isdigit檢測字符是否為阿拉伯數字
if (inputName.empty() || (isdigit(inputName[0]) && inputName.size() == 1))
{
int c = inputName.empty() ? 0 : inputName[0] - '0';
// 此處若系統在虛擬機上，需在虛擬機中設置接管攝像頭：虛擬機(M)-> 可移動設備 -> 攝像頭名稱 -> 連接(斷開與主機連接)
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] = '\0';
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\n", 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: [email protected]
* \問題描述：http://www.linuxidc.com/Linux/2016-11/137103.htm
* \問題分析：
可以存avi,但是不能打開，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) //如果不能打開攝像頭給出警告
// {
// cout << "Can not open the camera." << endl;
// return -1;
// }
// else
// {
// frame = cvQueryFrame(capture); //首先取得攝像頭中的一幀
// video = cvCreateVideoWriter("camera.avi", CV_FOURCC('X', 'V', 'I', 'D'), 25,
// cvSize(frame->width, frame->height)); //創建CvVideoWriter對象並分配空間
// //保存的文件名為camera.avi，編碼要在運行程序時選擇，大小就是攝像頭視頻的大小，幀頻率是32
// if (video) //如果能創建CvVideoWriter對象則表明成功
// {
// cout << "VideoWriter has created." << endl;
// }
//
// cvNamedWindow("Camera Video", 1); //新建一個窗口
// int i = 0;
// while (i <= 300) // 讓它循環200次自動停止錄取
// {
// frame = cvQueryFrame(capture); //從CvCapture中獲得一幀
// if (!frame)
// {
// cout << "Can not get frame from the capture." << endl;
// break;
// }
// n = cvWriteFrame(video, frame); //判斷是否寫入成功，如果返回的是1，表示寫入成功
// cout << n << endl;
// cvShowImage("Camera Video", frame); //顯示視頻內容的圖片
// i++;
// if (cvWaitKey(2) > 0)
// break; //有其他鍵盤響應，則退出
// }
//
// cvReleaseVideoWriter(&video);
// cvReleaseCapture(&capture);
// cvDestroyWindow("Camera Video");
// }
// return 0;
//}
這是調用攝像頭動態檢測人臉的程序，實驗結果：
控制台輸出：
***** VIDEOINPUT LIBRARY - 0.1995 - TFW07 *****
SETUP: Setting up device 0
SETUP: Integrated Camera
SETUP: Couldn't find preview pin using SmartTee
SETUP: Default Format is set to 640x480
SETUP: trying specified format RGB24 @ 640x480
SETUP: trying format RGB24 @ 640x480
SETUP: trying format RGB32 @ 640x480
SETUP: trying format RGB555 @ 640x480
SETUP: trying format RGB565 @ 640x480
SETUP: trying format YUY2 @ 640x480
SETUP: Capture callback set
SETUP: Device is setup and ready to capture.
Video capturing has been started ...
capturing...
Start to detect...
detection time = 486.754 ms
capturing...
Start to detect...
detection time = 444.236 ms
capturing...
Start to detect...
detection time = 441.649 ms
capturing...
Start to detect...
detection time = 447.361 ms
capturing...
Start to detect...
detection time = 427.589 ms
capturing...
Start to detect...
detection time = 453.187 ms
capturing...
Start to detect...
d
OpenCV官方教程中文版（For Python） PDF http://www.linuxidc.com/Linux/2015-08/121400.htm
Ubuntu Linux下安裝OpenCV2.4.1所需包 http://www.linuxidc.com/Linux/2012-08/68184.htm
Ubuntu 16.04上用CMake圖形界面交叉編譯樹莓派的OpenCV3.0 http://www.linuxidc.com/Linux/2016-10/135914.htm
Ubuntu 12.04下安裝OpenCV 2.4.5總結 http://www.linuxidc.com/Linux/2013-06/86704.htm
Ubuntu 10.04中安裝OpenCv2.1九步曲 http://www.linuxidc.com/Linux/2010-09/28678.htm
基於QT和OpenCV的人臉識別系統 http://www.linuxidc.com/Linux/2011-11/47806.htm
[翻譯]Ubuntu 14.04, 13.10 下安裝 OpenCV 2.4.9 http://www.linuxidc.com/Linux/2014-12/110045.htm
OpenCV的詳細介紹：請點這裡
OpenCV的下載地址：請點這裡
