opencv/samples/c/bgfg_codebook.cpp
2013-04-08 15:47:29 +04:00

242 lines
8.1 KiB
C++

// Background average sample code done with averages and done with codebooks
// (adapted from the OpenCV book sample)
//
// NOTE: To get the keyboard to work, you *have* to have one of the video windows be active
// and NOT the consule window.
//
// Gary Bradski Oct 3, 2008.
//
/* *************** License:**************************
Oct. 3, 2008
Right to use this code in any way you want without warrenty, support or any guarentee of it working.
BOOK: It would be nice if you cited it:
Learning OpenCV: Computer Vision with the OpenCV Library
by Gary Bradski and Adrian Kaehler
Published by O'Reilly Media, October 3, 2008
AVAILABLE AT:
http://www.amazon.com/Learning-OpenCV-Computer-Vision-Library/dp/0596516134
Or: http://oreilly.com/catalog/9780596516130/
ISBN-10: 0596516134 or: ISBN-13: 978-0596516130
************************************************** */
#include "opencv2/core.hpp"
#include "opencv2/core/utility.hpp"
#include "opencv2/video/background_segm.hpp"
#include "opencv2/imgproc/imgproc_c.h"
#include "opencv2/highgui/highgui_c.h"
#include "opencv2/legacy.hpp"
#include <stdio.h>
#include <stdlib.h>
#include <ctype.h>
using namespace std;
using namespace cv;
//VARIABLES for CODEBOOK METHOD:
CvBGCodeBookModel* model = 0;
const int NCHANNELS = 3;
bool ch[NCHANNELS]={true,true,true}; // This sets what channels should be adjusted for background bounds
static void help()
{
printf("\nLearn background and find foreground using simple average and average difference learning method:\n"
"Originally from the book: Learning OpenCV by O'Reilly press\n"
"\nUSAGE:\n"
" bgfg_codebook [--nframes(-nf)=300] [--movie_filename(-mf)=tree.avi] [--camera(-c), use camera or not]\n"
"***Keep the focus on the video windows, NOT the consol***\n\n"
"INTERACTIVE PARAMETERS:\n"
"\tESC,q,Q - quit the program\n"
"\th - print this help\n"
"\tp - pause toggle\n"
"\ts - single step\n"
"\tr - run mode (single step off)\n"
"=== AVG PARAMS ===\n"
"\t- - bump high threshold UP by 0.25\n"
"\t= - bump high threshold DOWN by 0.25\n"
"\t[ - bump low threshold UP by 0.25\n"
"\t] - bump low threshold DOWN by 0.25\n"
"=== CODEBOOK PARAMS ===\n"
"\ty,u,v- only adjust channel 0(y) or 1(u) or 2(v) respectively\n"
"\ta - adjust all 3 channels at once\n"
"\tb - adjust both 2 and 3 at once\n"
"\ti,o - bump upper threshold up,down by 1\n"
"\tk,l - bump lower threshold up,down by 1\n"
"\tSPACE - reset the model\n"
);
}
//
//USAGE: ch9_background startFrameCollection# endFrameCollection# [movie filename, else from camera]
//If from AVI, then optionally add HighAvg, LowAvg, HighCB_Y LowCB_Y HighCB_U LowCB_U HighCB_V LowCB_V
//
const char *keys =
{
"{nf nframes |300 |frames number}"
"{c camera |false |use the camera or not}"
"{mf movie_file|tree.avi |used movie video file}"
};
int main(int argc, const char** argv)
{
help();
CommandLineParser parser(argc, argv, keys);
int nframesToLearnBG = parser.get<int>("nf");
bool useCamera = parser.has("c");
string filename = parser.get<string>("mf");
IplImage* rawImage = 0, *yuvImage = 0; //yuvImage is for codebook method
IplImage *ImaskCodeBook = 0,*ImaskCodeBookCC = 0;
CvCapture* capture = 0;
int c, n, nframes = 0;
model = cvCreateBGCodeBookModel();
//Set color thresholds to default values
model->modMin[0] = 3;
model->modMin[1] = model->modMin[2] = 3;
model->modMax[0] = 10;
model->modMax[1] = model->modMax[2] = 10;
model->cbBounds[0] = model->cbBounds[1] = model->cbBounds[2] = 10;
bool pause = false;
bool singlestep = false;
if( useCamera )
{
printf("Capture from camera\n");
capture = cvCaptureFromCAM( 0 );
}
else
{
printf("Capture from file %s\n",filename.c_str());
capture = cvCreateFileCapture( filename.c_str() );
}
if( !capture )
{
printf( "Can not initialize video capturing\n\n" );
help();
return -1;
}
//MAIN PROCESSING LOOP:
for(;;)
{
if( !pause )
{
rawImage = cvQueryFrame( capture );
++nframes;
if(!rawImage)
break;
}
if( singlestep )
pause = true;
//First time:
if( nframes == 1 && rawImage )
{
// CODEBOOK METHOD ALLOCATION
yuvImage = cvCloneImage(rawImage);
ImaskCodeBook = cvCreateImage( cvGetSize(rawImage), IPL_DEPTH_8U, 1 );
ImaskCodeBookCC = cvCreateImage( cvGetSize(rawImage), IPL_DEPTH_8U, 1 );
cvSet(ImaskCodeBook,cvScalar(255));
cvNamedWindow( "Raw", 1 );
cvNamedWindow( "ForegroundCodeBook",1);
cvNamedWindow( "CodeBook_ConnectComp",1);
}
// If we've got an rawImage and are good to go:
if( rawImage )
{
cvCvtColor( rawImage, yuvImage, CV_BGR2YCrCb );//YUV For codebook method
//This is where we build our background model
if( !pause && nframes-1 < nframesToLearnBG )
cvBGCodeBookUpdate( model, yuvImage );
if( nframes-1 == nframesToLearnBG )
cvBGCodeBookClearStale( model, model->t/2 );
//Find the foreground if any
if( nframes-1 >= nframesToLearnBG )
{
// Find foreground by codebook method
cvBGCodeBookDiff( model, yuvImage, ImaskCodeBook );
// This part just to visualize bounding boxes and centers if desired
cvCopy(ImaskCodeBook,ImaskCodeBookCC);
cvSegmentFGMask( ImaskCodeBookCC );
}
//Display
cvShowImage( "Raw", rawImage );
cvShowImage( "ForegroundCodeBook",ImaskCodeBook);
cvShowImage( "CodeBook_ConnectComp",ImaskCodeBookCC);
}
// User input:
c = cvWaitKey(10)&0xFF;
c = tolower(c);
// End processing on ESC, q or Q
if(c == 27 || c == 'q')
break;
//Else check for user input
switch( c )
{
case 'h':
help();
break;
case 'p':
pause = !pause;
break;
case 's':
singlestep = !singlestep;
pause = false;
break;
case 'r':
pause = false;
singlestep = false;
break;
case ' ':
cvBGCodeBookClearStale( model, 0 );
nframes = 0;
break;
//CODEBOOK PARAMS
case 'y': case '0':
case 'u': case '1':
case 'v': case '2':
case 'a': case '3':
case 'b':
ch[0] = c == 'y' || c == '0' || c == 'a' || c == '3';
ch[1] = c == 'u' || c == '1' || c == 'a' || c == '3' || c == 'b';
ch[2] = c == 'v' || c == '2' || c == 'a' || c == '3' || c == 'b';
printf("CodeBook YUV Channels active: %d, %d, %d\n", ch[0], ch[1], ch[2] );
break;
case 'i': //modify max classification bounds (max bound goes higher)
case 'o': //modify max classification bounds (max bound goes lower)
case 'k': //modify min classification bounds (min bound goes lower)
case 'l': //modify min classification bounds (min bound goes higher)
{
uchar* ptr = c == 'i' || c == 'o' ? model->modMax : model->modMin;
for(n=0; n<NCHANNELS; n++)
{
if( ch[n] )
{
int v = ptr[n] + (c == 'i' || c == 'l' ? 1 : -1);
ptr[n] = cv::saturate_cast<uchar>(v);
}
printf("%d,", ptr[n]);
}
printf(" CodeBook %s Side\n", c == 'i' || c == 'o' ? "High" : "Low" );
}
break;
}
}
cvReleaseCapture( &capture );
cvDestroyWindow( "Raw" );
cvDestroyWindow( "ForegroundCodeBook");
cvDestroyWindow( "CodeBook_ConnectComp");
return 0;
}