mirror of
https://gitcode.com/gh_mirrors/es/esp32-opencv.git
synced 2025-08-06 18:24:38 +08:00
initial commit
This commit is contained in:
Joachim
255
samples/cpp/facedetect.cpp
Normal file
255
samples/cpp/facedetect.cpp
Normal file
@ -0,0 +1,255 @@
|
||||
#include "opencv2/objdetect.hpp"
|
||||
#include "opencv2/highgui.hpp"
|
||||
#include "opencv2/imgproc.hpp"
|
||||
#include "opencv2/videoio.hpp"
|
||||
#include <iostream>
|
||||
|
||||
using namespace std;
|
||||
using namespace cv;
|
||||
|
||||
static void help()
|
||||
{
|
||||
cout << "\nThis program demonstrates the use of cv::CascadeClassifier class to detect objects (Face + eyes). 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 cascade, nestedCascade;
|
||||
double scale;
|
||||
|
||||
cv::CommandLineParser parser(argc, argv,
|
||||
"{help h||}"
|
||||
"{cascade|data/haarcascades/haarcascade_frontalface_alt.xml|}"
|
||||
"{nested-cascade|data/haarcascades/haarcascade_eye_tree_eyeglasses.xml|}"
|
||||
"{scale|1|}{try-flip||}{@filename||}"
|
||||
);
|
||||
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");
|
||||
if (!parser.check())
|
||||
{
|
||||
parser.printErrors();
|
||||
return 0;
|
||||
}
|
||||
if (!nestedCascade.load(samples::findFileOrKeep(nestedCascadeName)))
|
||||
cerr << "WARNING: Could not load classifier cascade for nested objects" << endl;
|
||||
if (!cascade.load(samples::findFile(cascadeName)))
|
||||
{
|
||||
cerr << "ERROR: Could not load classifier cascade" << endl;
|
||||
help();
|
||||
return -1;
|
||||
}
|
||||
if( inputName.empty() || (isdigit(inputName[0]) && inputName.size() == 1) )
|
||||
{
|
||||
int camera = inputName.empty() ? 0 : inputName[0] - '0';
|
||||
if(!capture.open(camera))
|
||||
{
|
||||
cout << "Capture from camera #" << camera << " didn't work" << endl;
|
||||
return 1;
|
||||
}
|
||||
}
|
||||
else if (!inputName.empty())
|
||||
{
|
||||
image = imread(samples::findFileOrKeep(inputName), IMREAD_COLOR);
|
||||
if (image.empty())
|
||||
{
|
||||
if (!capture.open(samples::findFileOrKeep(inputName)))
|
||||
{
|
||||
cout << "Could not read " << inputName << endl;
|
||||
return 1;
|
||||
}
|
||||
}
|
||||
}
|
||||
else
|
||||
{
|
||||
image = imread(samples::findFile("lena.jpg"), IMREAD_COLOR);
|
||||
if (image.empty())
|
||||
{
|
||||
cout << "Couldn't read lena.jpg" << endl;
|
||||
return 1;
|
||||
}
|
||||
}
|
||||
|
||||
if( capture.isOpened() )
|
||||
{
|
||||
cout << "Video capturing has been started ..." << endl;
|
||||
|
||||
for(;;)
|
||||
{
|
||||
capture >> frame;
|
||||
if( frame.empty() )
|
||||
break;
|
||||
|
||||
Mat frame1 = frame.clone();
|
||||
detectAndDraw( frame1, cascade, nestedCascade, scale, tryflip );
|
||||
|
||||
char c = (char)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);
|
||||
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 );
|
||||
char c = (char)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_EXACT );
|
||||
equalizeHist( smallImg, smallImg );
|
||||
|
||||
t = (double)getTickCount();
|
||||
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)getTickCount() - t;
|
||||
printf( "detection time = %g ms\n", t*1000/getTickFrequency());
|
||||
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, Point(cvRound(r.x*scale), cvRound(r.y*scale)),
|
||||
Point(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 );
|
||||
}
|
||||
Reference in New Issue
Block a user