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reverted samples with new command argument parser. will be continued after OpenCV release.

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This commit is contained in:
itsyplen
2011-06-09 12:01:47 +00:00
parent 8f4f982e5c
commit 3876cf22e3
16 changed files with 601 additions and 559 deletions
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57
samples/c/adaptiveskindetector.cpp
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@@ -35,17 +35,27 @@
//M*/
#include "opencv2/core/core.hpp"
#include "opencv2/contrib/contrib.hpp"
#include "opencv2/highgui/highgui.hpp"
#include <iostream>
#include <cstdio>
#include <cstring>
#include <ctime>
#include "opencv2/contrib/contrib.hpp"
#include "opencv2/highgui/highgui.hpp"
using namespace std;
using namespace cv;
void help(char **argv)
{
std::cout << "\nThis program demonstrates the contributed flesh detector CvAdaptiveSkinDetector which can be found in contrib.cpp\n"
<< "Usage: " << std::endl <<
argv[0] << " fileMask firstFrame lastFrame" << std::endl << std::endl <<
"Example: " << std::endl <<
argv[0] << " C:\\VideoSequences\\sample1\\right_view\\temp_%05d.jpg 0 1000" << std::endl <<
" iterates through temp_00000.jpg to temp_01000.jpg" << std::endl << std::endl <<
"If no parameter specified, this application will try to capture from the default Webcam." << std::endl <<
"Please note: Background should not contain large surfaces with skin tone." <<
"\n\n ESC will stop\n"
"Using OpenCV version %s\n" << CV_VERSION << "\n"
<< std::endl;
}
class ASDFrameHolder
{
@@ -149,6 +159,7 @@ void ASDFrameHolder::setImage(IplImage *sourceImage)
//-------------------- ASDFrameSequencer -----------------------//
ASDFrameSequencer::~ASDFrameSequencer()
{
close();
@@ -204,6 +215,7 @@ bool ASDCVFrameSequencer::isOpen()
//-------------------- ASDFrameSequencerWebCam -----------------------//
bool ASDFrameSequencerWebCam::open(int cameraIndex)
{
close();
@@ -323,39 +335,19 @@ void displayBuffer(IplImage *rgbDestImage, IplImage *buffer, int rValue, int gVa
}
};
void help()
int main(int argc, char** argv )
{
printf("\nThis program demonstrates the contributed flesh detector CvAdaptiveSkinDetector \n"
"which can be found in contrib.cpp \n"
"Usage: \n"
"./adaptiveskindetector [--fileMask]=<path to file, which are used in mask \n"
" [--firstFrame]=<first frame number \n"
" [--lastFrame]=<last frame number> \n"
"if at least one parameter doesn't specified, it will try to use default webcam \n"
"Expample: \n"
" --fileMask = /home/user_home_directory/work/opencv/samples/c/temp_%%05d.jpg --firstFrame=0 --lastFrame=1000 \n");
}
int main(int argc, const char** argv )
{
help();
CommandLineParser parser(argc, argv);
string fileMask = parser.get<string>("fileMask");
int firstFrame = parser.get<int>("firstFrame", 0);
int lastFrame = parser.get<int>("lastFrame", 0);
IplImage *img, *filterMask = NULL;
CvAdaptiveSkinDetector filter(1, CvAdaptiveSkinDetector::MORPHING_METHOD_ERODE_DILATE);
ASDFrameSequencer *sequencer;
CvFont base_font;
char caption[2048], s[256], windowName[256];
long int clockTotal = 0, numFrames = 0;
std::clock_t clock;
std::clock_t clock;
if (argc < 4)
{
help(argv);
sequencer = new ASDFrameSequencerWebCam();
(dynamic_cast<ASDFrameSequencerWebCam*>(sequencer))->open(-1);
@@ -366,9 +358,8 @@ int main(int argc, const char** argv )
}
else
{
// A sequence of images captured from video source, is stored here
sequencer = new ASDFrameSequencerImageFile();
(dynamic_cast<ASDFrameSequencerImageFile*>(sequencer))->open(fileMask.c_str(), firstFrame, lastFrame );
(dynamic_cast<ASDFrameSequencerImageFile*>(sequencer))->open(argv[1], std::atoi(argv[2]), std::atoi(argv[3]) ); // A sequence of images captured from video source, is stored here
}
std::sprintf(windowName, "%s", "Adaptive Skin Detection Algorithm for Video Sequences");
@@ -376,6 +367,10 @@ int main(int argc, const char** argv )
cvNamedWindow(windowName, CV_WINDOW_AUTOSIZE);
cvInitFont( &base_font, CV_FONT_VECTOR0, 0.5, 0.5);
// Usage:
// c:\>CvASDSample "C:\VideoSequences\sample1\right_view\temp_%05d.jpg" 0 1000
std::cout << "Press ESC to stop." << std::endl << std::endl;
while ((img = sequencer->getNextImage()) != 0)
{
numFrames++;

103
samples/c/bgfg_codebook.cpp
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@@ -25,14 +25,10 @@
#include <stdlib.h>
#include <ctype.h>
#include "opencv2/core/core.hpp"
#include "opencv2/video/background_segm.hpp"
#include <opencv2/imgproc/imgproc_c.h>
#include "opencv2/imgproc/imgproc_c.h"
#include "opencv2/highgui/highgui.hpp"
using namespace std;
using namespace cv;
//VARIABLES for CODEBOOK METHOD:
CvBGCodeBookModel* model = 0;
const int NCHANNELS = 3;
@@ -42,28 +38,26 @@ void help(void)
{
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]=<frames number, 300 as default> \n"
" [--input]=<movie filename or camera index, zero camera index as default>\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"
"\nUSAGE:\nbgfg_codebook [--nframes=300] [movie filename, else from camera]\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"
);
}
@@ -71,20 +65,15 @@ void help(void)
//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
//
int main(int argc, const char** argv)
int main(int argc, char** argv)
{
help();
CommandLineParser parser(argc, argv);
string inputName = parser.get<string>("input", "0");
int nframesToLearnBG = parser.get<int>("nframes", 300);
const char* filename = 0;
IplImage* rawImage = 0, *yuvImage = 0; //yuvImage is for codebook method
IplImage *ImaskCodeBook = 0,*ImaskCodeBookCC = 0;
CvCapture* capture = 0;
int c, n, nframes = 0;
int c, n, nframes = 0;
int nframesToLearnBG = 300;
model = cvCreateBGCodeBookModel();
@@ -98,30 +87,38 @@ int main(int argc, const char** argv)
bool pause = false;
bool singlestep = false;
if( inputName.empty() || (isdigit(inputName.c_str()[0]) && inputName.c_str()[1] == '\0') )
for( n = 1; n < argc; n++ )
{
printf("Capture from camera\n");
capture = cvCaptureFromCAM( inputName.empty() ? 0 : inputName.c_str()[0] - '0' );
int c = inputName.empty() ? 0 : inputName.c_str()[0] - '0' ;
if( !capture)
static const char* nframesOpt = "--nframes=";
if( strncmp(argv[n], nframesOpt, strlen(nframesOpt))==0 )
{
printf ("Capture from CAM %d", c);
printf (" didn't work\n");
}
}
else
{
printf("Capture from file %s\n",inputName.c_str());
capture = cvCreateFileCapture(inputName.c_str());
if( !capture)
if( sscanf(argv[n] + strlen(nframesOpt), "%d", &nframesToLearnBG) == 0 )
{
printf ("Capture from file %s", inputName.c_str());
printf (" didn't work\n");
help();
return -1;
}
}
else
filename = argv[n];
}
if( !filename )
{
printf("Capture from camera\n");
capture = cvCaptureFromCAM( 0 );
}
else
{
printf("Capture from file %s\n",filename);
capture = cvCreateFileCapture( filename );
}
if( !capture )
{
printf( "Can not initialize video capturing\n\n" );
help();
return -1;
}
//MAIN PROCESSING LOOP:
for(;;)

79
samples/c/facedetect.cpp
View File

@@ -1,4 +1,3 @@
#include "opencv2/core/core.hpp"
#include "opencv2/objdetect/objdetect.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
@@ -11,13 +10,13 @@ using namespace cv;
void help()
{
cout << "\nThis program demonstrates the cascade classifier. Now you can use Haar or LBP features.\n"
cout << "\nThis program demonstrates the cascade recognizer. Now you can use Haar or LBP features.\n"
"This classifier can recognize many ~rigid objects, 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"
" [--input=filename|camera_index]\n\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.xml\" --scale=1.3 \n"
"Hit any key to quit.\n"
@@ -28,41 +27,70 @@ void detectAndDraw( Mat& img,
CascadeClassifier& cascade, CascadeClassifier& nestedCascade,
double scale);
String cascadeName = "../../data/haarcascades/haarcascade_frontalface_alt.xml";
String nestedCascadeName = "../../data/haarcascades/haarcascade_eye_tree_eyeglasses.xml";
int main( int argc, const char** argv )
{
help();
CommandLineParser parser(argc, argv);
string cascadeName = parser.get<string>("cascade", "../../data/haarcascades/haarcascade_frontalface_alt.xml");
string nestedCascadeName = parser.get<string>("nested-cascade", "../../data/haarcascades/haarcascade_eye_tree_eyeglasses.xml");
double scale = parser.get<double>("scale", 1.0);
string inputName = parser.get<string>("input", "0"); //read from camera by default
if (!cascadeName.empty())
cout << " from which we have cascadeName= " << cascadeName << endl;
if (!nestedCascadeName.empty())
cout << " from which we have nestedCascadeName= " << nestedCascadeName << endl;
CvCapture* capture = 0;
Mat frame, frameCopy, image;
const String scaleOpt = "--scale=";
size_t scaleOptLen = scaleOpt.length();
const String cascadeOpt = "--cascade=";
size_t cascadeOptLen = cascadeOpt.length();
const String nestedCascadeOpt = "--nested-cascade";
size_t nestedCascadeOptLen = nestedCascadeOpt.length();
String inputName;
help();
CascadeClassifier cascade, nestedCascade;
double scale = 1;
for( int i = 1; i < argc; i++ )
{
cout << "Processing " << i << " " << argv[i] << endl;
if( cascadeOpt.compare( 0, cascadeOptLen, argv[i], cascadeOptLen ) == 0 )
{
cascadeName.assign( argv[i] + cascadeOptLen );
cout << " from which we have cascadeName= " << cascadeName << endl;
}
else if( nestedCascadeOpt.compare( 0, nestedCascadeOptLen, argv[i], nestedCascadeOptLen ) == 0 )
{
if( argv[i][nestedCascadeOpt.length()] == '=' )
nestedCascadeName.assign( argv[i] + nestedCascadeOpt.length() + 1 );
if( !nestedCascade.load( nestedCascadeName ) )
cerr << "WARNING: Could not load classifier cascade for nested objects" << endl;
}
else if( scaleOpt.compare( 0, scaleOptLen, argv[i], scaleOptLen ) == 0 )
{
if( !sscanf( argv[i] + scaleOpt.length(), "%lf", &scale ) || scale < 1 )
scale = 1;
cout << " from which we read scale = " << scale << endl;
}
else if( argv[i][0] == '-' )
{
cerr << "WARNING: Unknown option %s" << argv[i] << endl;
}
else
inputName.assign( argv[i] );
}
if( !cascade.load( cascadeName ) )
{
cerr << "ERROR: Could not load classifier cascade" << endl;
cerr << "Usage: facedetect [--cascade=<cascade_path>]\n"
" [--nested-cascade[=nested_cascade_path]]\n"
" [--scale[=<image scale>\n"
" [filename|camera_index]\n" << endl ;
return -1;
}
if( !nestedCascade.load( nestedCascadeName ) )
cerr << "WARNING: Could not load classifier cascade for nested objects" << endl;
if( inputName.empty() || (isdigit(inputName.c_str()[0]) && inputName.c_str()[1] == '\0') )
{
capture = cvCaptureFromCAM( inputName.empty() ? 0 : inputName.c_str()[0] - '0' );
int c = inputName.empty() ? 0 : inputName.c_str()[0] - '0' ;
if( !capture) cout << "Capture from CAM " << c << " didn't work" << endl;
if(!capture) cout << "Capture from CAM " << c << " didn't work" << endl;
}
else if( inputName.size() )
{
@@ -70,9 +98,14 @@ int main( int argc, const char** argv )
if( image.empty() )
{
capture = cvCaptureFromAVI( inputName.c_str() );
if( !capture ) cout << "Capture from AVI didn't work" << endl;
if(!capture) cout << "Capture from AVI didn't work" << endl;
}
}
else
{
image = imread( "lena.jpg", 1 );
if(image.empty()) cout << "Couldn't read lena.jpg" << endl;
}
cvNamedWindow( "result", 1 );

41
samples/c/find_obj.cpp
View File

@@ -4,30 +4,26 @@
* Author: Liu Liu
* liuliu.1987+opencv@gmail.com
*/
#include "opencv2/core/core.hpp"
#include "opencv2/objdetect/objdetect.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/calib3d/calib3d.hpp"
#include <opencv2/imgproc/imgproc_c.h>
#include "opencv2/imgproc/imgproc_c.h"
#include <iostream>
#include <vector>
using namespace std;
using namespace cv;
void help()
{
printf( "\n This program demonstrated the use of the SURF Detector and Descriptor using\n"
"either FLANN (fast approx nearst neighbor classification) or brute force matching\n"
"on planar objects.\n"
"Usage: \n"
"./find_obj [--object_filename]=<object_filename, box.png as default> \n"
" [--scene_filename]=<scene_filename box_in_scene.png as default>] \n"
"Example: \n"
"./find_obj --object_filename=box.png --scene_filename=box_in_scene.png \n\n"
);
printf(
"This program demonstrated the use of the SURF Detector and Descriptor using\n"
"either FLANN (fast approx nearst neighbor classification) or brute force matching\n"
"on planar objects.\n"
"Call:\n"
"./find_obj [<object_filename default box.png> <scene_filename default box_in_scene.png>]\n\n"
);
}
// define whether to use approximate nearest-neighbor search
@@ -213,16 +209,13 @@ locatePlanarObject( const CvSeq* objectKeypoints, const CvSeq* objectDescriptors
return 1;
}
int main(int argc, const char** argv)
int main(int argc, char** argv)
{
help();
CommandLineParser parser(argc, argv);
string objectFileName = parser.get<string>("object_filename", "box.png");
string sceneFileName = parser.get<string>("scene_filename", "box_in_scene.png");
const char* object_filename = argc == 3 ? argv[1] : "box.png";
const char* scene_filename = argc == 3 ? argv[2] : "box_in_scene.png";
CvMemStorage* storage = cvCreateMemStorage(0);
help();
cvNamedWindow("Object", 1);
cvNamedWindow("Object Correspond", 1);
@@ -239,11 +232,13 @@ int main(int argc, const char** argv)
{{255,255,255}}
};
IplImage* object = cvLoadImage( objectFileName.c_str(), CV_LOAD_IMAGE_GRAYSCALE );
IplImage* image = cvLoadImage( sceneFileName.c_str(), CV_LOAD_IMAGE_GRAYSCALE );
IplImage* object = cvLoadImage( object_filename, CV_LOAD_IMAGE_GRAYSCALE );
IplImage* image = cvLoadImage( scene_filename, CV_LOAD_IMAGE_GRAYSCALE );
if( !object || !image )
{
fprintf( stderr, "Can not load %s and/or %s\n", objectFileName.c_str(), sceneFileName.c_str() );
fprintf( stderr, "Can not load %s and/or %s\n"
"Usage: find_obj [<object_filename> <scene_filename>]\n",
object_filename, scene_filename );
exit(-1);
}
IplImage* object_color = cvCreateImage(cvGetSize(object), 8, 3);

38
samples/c/find_obj_calonder.cpp
View File

@@ -11,17 +11,14 @@ using namespace cv;
void help()
{
printf("\n This program shows the use of the Calonder point descriptor classifier \n"
"SURF is used to detect interest points, Calonder is used to describe/match these points \n"
"Usage: \n"
"./find_obj_calonder --classifier_file=<classifier file, there is no default classifier file. You should create it at first and when you can use it for test> \n"
" --test_image=<image file for test, lena.jpg as default> \n"
" [--train_container]=<txt file with train images filenames> \n"
"Example: \n"
" --classifier_file=test_classifier --test_image=lena.jpg --train_container=one_way_train_images.txt \n"
" the test_classifier is created here using --train_container and tested witn --test_image at the end \n"
" --classifier_file=test_classifier --test_image=lena.jpg \n"
" the test classifier is tested here using lena.jpg \n");
cout << "This program shows the use of the Calonder point descriptor classifier"
"SURF is used to detect interest points, Calonder is used to describe/match these points\n"
"Format:" << endl <<
" classifier_file(to write) test_image file_with_train_images_filenames(txt)" <<
" or" << endl <<
" classifier_file(to read) test_image"
"Using OpenCV version %s\n" << CV_VERSION << "\n"
<< endl;
}
/*
* Generates random perspective transform of image
@@ -147,27 +144,18 @@ void testCalonderClassifier( const string& classifierFilename, const string& img
waitKey();
}
int main( int argc, const char **argv )
int main( int argc, char **argv )
{
help();
CommandLineParser parser(argc, argv);
string classifierFileName = parser.get<string>("classifier_file");
string testImageFileName = parser.get<string>("test_image", "lena.jpg");
string trainContainerFileName = parser.get<string>("train_container");
if( classifierFileName.empty())
if( argc != 4 && argc != 3 )
{
printf("\n Can't find classifier file, please select file for --classifier_file parameter \n");
help();
return -1;
}
if( !trainContainerFileName.empty())
trainCalonderClassifier( classifierFileName.c_str(), trainContainerFileName.c_str() );
if( argc == 4 )
trainCalonderClassifier( argv[1], argv[3] );
testCalonderClassifier( classifierFileName.c_str(), testImageFileName.c_str() );
testCalonderClassifier( argv[1], argv[2] );
return 0;
}

32
samples/c/find_obj_ferns.cpp
View File

@@ -9,37 +9,30 @@
#include <vector>
using namespace cv;
void help()
{
printf( "This program shows the use of the \"fern\" plannar PlanarObjectDetector point\n"
"descriptor classifier"
"Usage: \n"
"./find_obj_ferns [--object_filename]=<object_filename, box.png as default> \n"
" [--scene_filename]=<scene_filename box_in_scene.png as default>] \n"
"Example: \n"
"./find_obj_ferns --object_filename=box.png --scene_filename=box_in_scene.png \n");
"descriptor classifier"
"Usage:\n"
"./find_obj_ferns [<object_filename default: box.png> <scene_filename default:box_in_scene.png>]\n"
"\n");
}
int main(int argc, const char** argv)
int main(int argc, char** argv)
{
const char* object_filename = argc > 1 ? argv[1] : "box.png";
const char* scene_filename = argc > 2 ? argv[2] : "box_in_scene.png";
int i;
help();
CommandLineParser parser(argc, argv);
string objectFileName = parser.get<string>("object_filename", "box.png");
string sceneFileName = parser.get<string>("scene_filename", "box_in_scene.png");
cvNamedWindow("Object", 1);
cvNamedWindow("Image", 1);
cvNamedWindow("Object Correspondence", 1);
Mat object = imread( objectFileName.c_str(), CV_LOAD_IMAGE_GRAYSCALE );
Mat object = imread( object_filename, CV_LOAD_IMAGE_GRAYSCALE );
Mat image;
double imgscale = 1;
Mat _image = imread( sceneFileName.c_str(), CV_LOAD_IMAGE_GRAYSCALE );
Mat _image = imread( scene_filename, CV_LOAD_IMAGE_GRAYSCALE );
resize(_image, image, Size(), 1./imgscale, 1./imgscale, INTER_CUBIC);
@@ -47,7 +40,7 @@ int main(int argc, const char** argv)
{
fprintf( stderr, "Can not load %s and/or %s\n"
"Usage: find_obj_ferns [<object_filename> <scene_filename>]\n",
objectFileName.c_str(), sceneFileName.c_str() );
object_filename, scene_filename );
exit(-1);
}
@@ -67,7 +60,7 @@ int main(int argc, const char** argv)
vector<KeyPoint> objKeypoints, imgKeypoints;
PatchGenerator gen(0,256,5,true,0.8,1.2,-CV_PI/2,CV_PI/2,-CV_PI/2,CV_PI/2);
string model_filename = format("%s_model.xml.gz", objectFileName.c_str());
string model_filename = format("%s_model.xml.gz", object_filename);
printf("Trying to load %s ...\n", model_filename.c_str());
FileStorage fs(model_filename, FileStorage::READ);
if( fs.isOpened() )
@@ -113,7 +106,6 @@ int main(int argc, const char** argv)
t = (double)getTickCount() - t;
printf("%gms\n", t*1000/getTickFrequency());
int i = 0;
if( found )
{
for( i = 0; i < 4; i++ )

103
samples/c/latentsvmdetect.cpp
View File

@@ -1,11 +1,9 @@
#include "opencv2/core/core.hpp"
#include "opencv2/objdetect/objdetect.hpp"
#include "opencv2/highgui/highgui.hpp"
#include <stdio.h>
#ifdef HAVE_CONFIG_H
#include "cvconfig.h"
#include <cvconfig.h>
#endif
#ifdef HAVE_TBB
#include "tbb/task_scheduler_init.h"
@@ -15,41 +13,42 @@ using namespace cv;
void help()
{
printf( "This program demonstrated the use of the latentSVM detector.\n"
"It reads in a trained object model and then uses that to detect the object in an image\n"
"Usage: \n"
"./latentsvmdetect [--image_filename]=<image_filename, cat.jpg as default> \n"
" [--model_filename]=<model_filename, cat.xml as default> \n"
" [--threads_number]=<number of threads, -1 as default>\n"
"Example: \n"
"./latentsvmdetect --image_filename=cat.jpg --model_filename=cat.xml --threads_number=7 \n"
" Press any key to quit.\n");
printf( "This program demonstrated the use of the latentSVM detector.\n"
"It reads in a trained object model and then uses that to detect the object in an image\n"
"Call:\n"
"./latentsvmdetect [<image_filename> <model_filename> [<threads_number>]]\n"
" The defaults for image_filename and model_filename are cat.jpg and cat.xml respectively\n"
" Press any key to quit.\n");
}
const char* model_filename = "cat.xml";
const char* image_filename = "cat.jpg";
int tbbNumThreads = -1;
void detect_and_draw_objects( IplImage* image, CvLatentSvmDetector* detector, int numThreads = -1)
{
CvMemStorage* storage = cvCreateMemStorage(0);
CvSeq* detections = 0;
int i = 0;
int64 start = 0, finish = 0;
int64 start = 0, finish = 0;
#ifdef HAVE_TBB
tbb::task_scheduler_init init(tbb::task_scheduler_init::deferred);
if (numThreads > 0)
{
init.initialize(numThreads);
if (numThreads > 0)
{
init.initialize(numThreads);
printf("Number of threads %i\n", numThreads);
}
else
{
printf("Number of threads is not correct for TBB version");
return;
}
}
else
{
printf("Number of threads is not correct for TBB version");
return;
}
#endif
start = cvGetTickCount();
start = cvGetTickCount();
detections = cvLatentSvmDetectObjects(image, detector, storage, 0.5f, numThreads);
finish = cvGetTickCount();
printf("detection time = %.3f\n", (float)(finish - start) / (float)(cvGetTickFrequency() * 1000000.0));
finish = cvGetTickCount();
printf("detection time = %.3f\n", (float)(finish - start) / (float)(cvGetTickFrequency() * 1000000.0));
#ifdef HAVE_TBB
init.terminate();
@@ -57,43 +56,43 @@ void detect_and_draw_objects( IplImage* image, CvLatentSvmDetector* detector, in
for( i = 0; i < detections->total; i++ )
{
CvObjectDetection detection = *(CvObjectDetection*)cvGetSeqElem( detections, i );
CvRect bounding_box = detection.rect;
CvRect bounding_box = detection.rect;
cvRectangle( image, cvPoint(bounding_box.x, bounding_box.y),
cvPoint(bounding_box.x + bounding_box.width,
bounding_box.y + bounding_box.height),
bounding_box.y + bounding_box.height),
CV_RGB(255,0,0), 3 );
}
cvReleaseMemStorage( &storage );
}
int main(int argc, const char* argv[])
int main(int argc, char* argv[])
{
help();
CommandLineParser parser(argc, argv);
string imageFileName = parser.get<string>("image_filename", "cat.jpg");
string modelFileName = parser.get<string>("model_filename", "cat.xml");
int tbbNumThreads = parser.get<int>("threads_number", -1);
IplImage* image = cvLoadImage(imageFileName.c_str());
if (!image)
{
printf( "Unable to load the image\n"
help();
if (argc > 2)
{
image_filename = argv[1];
model_filename = argv[2];
if (argc > 3)
{
tbbNumThreads = atoi(argv[3]);
}
}
IplImage* image = cvLoadImage(image_filename);
if (!image)
{
printf( "Unable to load the image\n"
"Pass it as the first parameter: latentsvmdetect <path to cat.jpg> <path to cat.xml>\n" );
return -1;
}
CvLatentSvmDetector* detector = cvLoadLatentSvmDetector(modelFileName.c_str());
if (!detector)
{
printf( "Unable to load the model\n"
return -1;
}
CvLatentSvmDetector* detector = cvLoadLatentSvmDetector(model_filename);
if (!detector)
{
printf( "Unable to load the model\n"
"Pass it as the second parameter: latentsvmdetect <path to cat.jpg> <path to cat.xml>\n" );
cvReleaseImage( &image );
return -1;
}
cvReleaseImage( &image );
return -1;
}
detect_and_draw_objects( image, detector, tbbNumThreads );
cvNamedWindow( "test", 0 );
cvShowImage( "test", image );
cvWaitKey(0);
@@ -101,5 +100,5 @@ int main(int argc, const char* argv[])
cvReleaseImage( &image );
cvDestroyAllWindows();
return 0;
return 0;
}

164
samples/c/mser_sample.cpp
View File

@@ -2,24 +2,17 @@
* Copyright<68> 2009, Liu Liu All rights reserved.
*/
#include "opencv2/core/core.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/imgproc/imgproc_c.h"
#include <iostream>
using namespace std;
using namespace cv;
void help()
{
printf("\nThis program demonstrates the Maximal Extremal Region interest point detector.\n"
"It finds the most stable (in size) dark and white regions as a threshold is increased.\n"
"\n Usage: \n"
"./mser_sample [--image_filename] <path_and_image_filename, default is 'puzzle.png'> \n"
"Example: \n"
"./mser_sample --image_filename=puzzle.png \n");
printf("\nThis program demonstrates the Maximal Extremal Region interest point detector.\n"
"It finds the most stable (in size) dark and white regions as a threshold is increased.\n"
"\nCall:\n"
"./mser_sample <path_and_image_filename, Default is 'puzzle.png'>\n\n");
}
static CvScalar colors[] =
@@ -51,81 +44,90 @@ static uchar bcolors[][3] =
};
int main( int argc, const char** argv )
int main( int argc, char** argv )
{
help();
char path[1024];
IplImage* img;
help();
if (argc!=2)
{
strcpy(path,"puzzle.png");
img = cvLoadImage( path, CV_LOAD_IMAGE_GRAYSCALE );
if (!img)
{
printf("\nUsage: mser_sample <path_to_image>\n");
return 0;
}
}
else
{
strcpy(path,argv[1]);
img = cvLoadImage( path, CV_LOAD_IMAGE_GRAYSCALE );
}
if (!img)
{
printf("Unable to load image %s\n",path);
return 0;
}
IplImage* rsp = cvLoadImage( path, CV_LOAD_IMAGE_COLOR );
IplImage* ellipses = cvCloneImage(rsp);
cvCvtColor(img,ellipses,CV_GRAY2BGR);
CvSeq* contours;
CvMemStorage* storage= cvCreateMemStorage();
IplImage* hsv = cvCreateImage( cvGetSize( rsp ), IPL_DEPTH_8U, 3 );
cvCvtColor( rsp, hsv, CV_BGR2YCrCb );
CvMSERParams params = cvMSERParams();//cvMSERParams( 5, 60, cvRound(.2*img->width*img->height), .25, .2 );
CommandLineParser parser(argc, argv);
double t = (double)cvGetTickCount();
cvExtractMSER( hsv, NULL, &contours, storage, params );
t = cvGetTickCount() - t;
printf( "MSER extracted %d contours in %g ms.\n", contours->total, t/((double)cvGetTickFrequency()*1000.) );
uchar* rsptr = (uchar*)rsp->imageData;
// draw mser with different color
for ( int i = contours->total-1; i >= 0; i-- )
{
CvSeq* r = *(CvSeq**)cvGetSeqElem( contours, i );
for ( int j = 0; j < r->total; j++ )
{
CvPoint* pt = CV_GET_SEQ_ELEM( CvPoint, r, j );
rsptr[pt->x*3+pt->y*rsp->widthStep] = bcolors[i%9][2];
rsptr[pt->x*3+1+pt->y*rsp->widthStep] = bcolors[i%9][1];
rsptr[pt->x*3+2+pt->y*rsp->widthStep] = bcolors[i%9][0];
}
}
// find ellipse ( it seems cvfitellipse2 have error or sth?
for ( int i = 0; i < contours->total; i++ )
{
CvContour* r = *(CvContour**)cvGetSeqElem( contours, i );
CvBox2D box = cvFitEllipse2( r );
box.angle=(float)CV_PI/2-box.angle;
if ( r->color > 0 )
cvEllipseBox( ellipses, box, colors[9], 2 );
else
cvEllipseBox( ellipses, box, colors[2], 2 );
}
string imageFileName = parser.get<string>("image_filename", "puzzle.png");
cvSaveImage( "rsp.png", rsp );
IplImage* img;
cvNamedWindow( "original", 0 );
cvShowImage( "original", img );
cvNamedWindow( "response", 0 );
cvShowImage( "response", rsp );
img = cvLoadImage( imageFileName.c_str(), CV_LOAD_IMAGE_GRAYSCALE );
if (!img)
{
printf("Unable to load image %s\n",imageFileName.c_str());
help();
return 0;
}
cvNamedWindow( "ellipses", 0 );
cvShowImage( "ellipses", ellipses );
IplImage* rsp = cvLoadImage( imageFileName.c_str(), CV_LOAD_IMAGE_COLOR );
IplImage* ellipses = cvCloneImage(rsp);
cvCvtColor(img,ellipses,CV_GRAY2BGR);
CvSeq* contours;
CvMemStorage* storage= cvCreateMemStorage();
IplImage* hsv = cvCreateImage( cvGetSize( rsp ), IPL_DEPTH_8U, 3 );
cvCvtColor( rsp, hsv, CV_BGR2YCrCb );
CvMSERParams params = cvMSERParams();//cvMSERParams( 5, 60, cvRound(.2*img->width*img->height), .25, .2 );
cvWaitKey(0);
double t = (double)cvGetTickCount();
cvExtractMSER( hsv, NULL, &contours, storage, params );
t = cvGetTickCount() - t;
printf( "MSER extracted %d contours in %g ms.\n", contours->total, t/((double)cvGetTickFrequency()*1000.) );
uchar* rsptr = (uchar*)rsp->imageData;
// draw mser with different color
for ( int i = contours->total-1; i >= 0; i-- )
{
CvSeq* r = *(CvSeq**)cvGetSeqElem( contours, i );
for ( int j = 0; j < r->total; j++ )
{
CvPoint* pt = CV_GET_SEQ_ELEM( CvPoint, r, j );
rsptr[pt->x*3+pt->y*rsp->widthStep] = bcolors[i%9][2];
rsptr[pt->x*3+1+pt->y*rsp->widthStep] = bcolors[i%9][1];
rsptr[pt->x*3+2+pt->y*rsp->widthStep] = bcolors[i%9][0];
}
}
// find ellipse ( it seems cvfitellipse2 have error or sth?
for ( int i = 0; i < contours->total; i++ )
{
CvContour* r = *(CvContour**)cvGetSeqElem( contours, i );
CvBox2D box = cvFitEllipse2( r );
box.angle=(float)CV_PI/2-box.angle;
if ( r->color > 0 )
cvEllipseBox( ellipses, box, colors[9], 2 );
else
cvEllipseBox( ellipses, box, colors[2], 2 );
}
cvSaveImage( "rsp.png", rsp );
cvNamedWindow( "original", 0 );
cvShowImage( "original", img );
cvNamedWindow( "response", 0 );
cvShowImage( "response", rsp );
cvNamedWindow( "ellipses", 0 );
cvShowImage( "ellipses", ellipses );
cvWaitKey(0);
cvDestroyWindow( "original" );
cvDestroyWindow( "response" );
cvDestroyWindow( "ellipses" );
cvReleaseImage(&rsp);
cvReleaseImage(&img);
cvReleaseImage(&ellipses);
cvDestroyWindow( "original" );
cvDestroyWindow( "response" );
cvDestroyWindow( "ellipses" );
cvReleaseImage(&rsp);
cvReleaseImage(&img);
cvReleaseImage(&ellipses);
}

36
samples/c/one_way_sample.cpp
View File

@@ -7,24 +7,18 @@
*
*/
#include "opencv2/core/core.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc_c.h"
#include <string>
void help()
{
printf("\nThis program demonstrates the one way interest point descriptor found in features2d.hpp\n"
"Correspondences are drawn\n"
"Usage: \n"
"./one_way_sample [--path]=<path_to_samples, '../../../opencv/samples/c' as default> \n"
" [--first_image]=<first image file, scene_l.bmp as default> \n"
" [--second_image]=<second image file, scene_r.bmp as default>\n"
"For example: \n"
" ./one_way_sample --path=../../../opencv/samples/c --first_image=scene_l.bmp --second_image=scene_r.bmp \n");
printf("\nThis program demonstrates the one way interest point descriptor found in features2d.hpp\n"
"Correspondences are drawn\n");
printf("Format: \n./one_way_sample [path_to_samples] [image1] [image2]\n");
printf("For example: ./one_way_sample ../../../opencv/samples/c scene_l.bmp scene_r.bmp\n");
}
using namespace cv;
@@ -32,19 +26,21 @@ using namespace cv;
IplImage* DrawCorrespondences(IplImage* img1, const vector<KeyPoint>& features1, IplImage* img2,
const vector<KeyPoint>& features2, const vector<int>& desc_idx);
int main(int argc, const char** argv)
int main(int argc, char** argv)
{
help();
CommandLineParser parser(argc, argv);
std::string path_name = parser.get<string>("path", "../../../opencv/samples/c");
std::string img1_name = path_name + "/" + parser.get<string>("first_image", "scene_l.bmp");
std::string img2_name = path_name + "/" + parser.get<string>("second_image", "scene_r.bmp");
const char images_list[] = "one_way_train_images.txt";
const CvSize patch_size = cvSize(24, 24);
const int pose_count = 1; //50
const int pose_count = 50;
if (argc != 3 && argc != 4)
{
help();
return 0;
}
std::string path_name = argv[1];
std::string img1_name = path_name + "/" + std::string(argv[2]);
std::string img2_name = path_name + "/" + std::string(argv[3]);
printf("Reading the images...\n");
IplImage* img1 = cvLoadImage(img1_name.c_str(), CV_LOAD_IMAGE_GRAYSCALE);

65
samples/c/tree_engine.cpp
View File

@@ -1,26 +1,21 @@
#include "opencv2/core/core.hpp"
#include "opencv2/ml/ml.hpp"
#include "opencv2/core/core_c.h"
#include <stdio.h>
#include <map>
using namespace std;
using namespace cv;
void help()
{
printf(
"\nThis sample demonstrates how to use different decision trees and forests including boosting and random trees:\n"
"CvDTree dtree;\n"
"CvBoost boost;\n"
"CvRTrees rtrees;\n"
"CvERTrees ertrees;\n"
"CvGBTrees gbtrees;\n"
"Usage: \n"
" ./tree_engine [--response_column]=<specified the 0-based index of the response, 0 as default> \n"
"[--categorical_response]=<specifies that the response is categorical, 0-false, 1-true, 0 as default> \n"
"[--csv_filename]=<is the name of training data file in comma-separated value format> \n"
);
printf(
"\nThis sample demonstrates how to use different decision trees and forests including boosting and random trees:\n"
"CvDTree dtree;\n"
"CvBoost boost;\n"
"CvRTrees rtrees;\n"
"CvERTrees ertrees;\n"
"CvGBTrees gbtrees;\n"
"Call:\n\t./tree_engine [-r <response_column>] [-c] <csv filename>\n"
"where -r <response_column> specified the 0-based index of the response (0 by default)\n"
"-c specifies that the response is categorical (it's ordered by default) and\n"
"<csv filename> is the name of training data file in comma-separated value format\n\n");
}
@@ -64,24 +59,34 @@ void print_result(float train_err, float test_err, const CvMat* _var_imp)
printf("\n");
}
int main(int argc, const char** argv)
int main(int argc, char** argv)
{
help();
CommandLineParser parser(argc, argv);
string filename = parser.get<string>("csv_filename");
int response_idx = parser.get<int>("response_column", 0);
bool categorical_response = (bool)parser.get<int>("categorical_response", 1);
if(filename.empty())
if(argc < 2)
{
printf("\n Please, select value for --csv_filename key \n");
help();
return -1;
return 0;
}
const char* filename = 0;
int response_idx = 0;
bool categorical_response = false;
for(int i = 1; i < argc; i++)
{
if(strcmp(argv[i], "-r") == 0)
sscanf(argv[++i], "%d", &response_idx);
else if(strcmp(argv[i], "-c") == 0)
categorical_response = true;
else if(argv[i][0] != '-' )
filename = argv[i];
else
{
printf("Error. Invalid option %s\n", argv[i]);
help();
return -1;
}
}
printf("\nReading in %s...\n\n",filename.c_str());
printf("\nReading in %s...\n\n",filename);
CvDTree dtree;
CvBoost boost;
CvRTrees rtrees;
@@ -93,7 +98,7 @@ int main(int argc, const char** argv)
CvTrainTestSplit spl( 0.5f );
if ( data.read_csv( filename.c_str() ) == 0)
if ( data.read_csv( filename ) == 0)
{
data.set_response_idx( response_idx );
if(categorical_response)