//特征点检测
void SiftMatch::on_detectButton_clicked()
{
img1_Feat = cvCloneImage(img1);//复制图1，深拷贝，用来画特征点
img2_Feat = cvCloneImage(img2);//复制图2，深拷贝，用来画特征点
//默认提取的是LOWE格式的SIFT特征点
//提取并显示第1幅图片上的特征点
n1 = sift_features( img1, &feat1 );//检测图1中的SIFT特征点,n1是图1的特征点个数
export_features("feature1.txt",feat1,n1);//将特征向量数据写入到文件
draw_features( img1_Feat, feat1, n1 );//画出特征点
//cvNamedWindow(IMG1_FEAT);//创建窗口
//cvShowImage(IMG1_FEAT,img1_Feat);//显示
QString name1_Feat = name1;//文件名，原文件名加"_Feat"
cvSaveImage(name1_Feat.insert( name1_Feat.lastIndexOf(".",-1) , "_Feat").toAscii().data(),img1_Feat);//保存图片
//提取并显示第2幅图片上的特征点
n2 = sift_features( img2, &feat2 );//检测图2中的SIFT特征点，n2是图2的特征点个数
export_features("feature2.txt",feat2,n2);//将特征向量数据写入到文件
draw_features( img2_Feat, feat2, n2 );//画出特征点
//cvNamedWindow(IMG2_FEAT);//创建窗口
//cvShowImage(IMG2_FEAT,img2_Feat);//显示
QString name2_Feat = name2;//文件名，原文件名加"_Feat"
cvSaveImage(name2_Feat.insert( name2_Feat.lastIndexOf(".",-1) , "_Feat").toAscii().data(),img2_Feat);//保存图片
ui->detectButton->setEnabled(false);//禁用特征检测按钮
ui->radioButton_horizontal->setEnabled(true);//激活排列方向选择按钮
ui->radioButton_vertical->setEnabled(true);
ui->matchButton->setEnabled(true);//激活特征匹配按钮
}
int main( int argc, char** argv )
{
IplImage* img;
struct feature* features;
int n = 0;
fprintf( stderr, "Finding SIFT features...\n" );
img = cvLoadImage( img_file_name, 1 );
if( ! img )
{
fprintf( stderr, "unable to load image from %s", img_file_name );
exit( 1 );
}
n = _sift_features( img, &features, intvls, sigma, contr_thr, curv_thr,
img_dbl, descr_width, descr_hist_bins );
fprintf( stderr, "Found %d features.\n", n );
if( display )
{
draw_features( img, features, n );
cvNamedWindow( img_file_name, 1 );
cvShowImage( img_file_name, img );
cvWaitKey( 0 );
}
if( out_file_name != NULL )
export_features( out_file_name, features, n );
if( out_img_name != NULL )
cvSaveImage( out_img_name, img );
return 0;
}
int main2( int argc, char** argv )
{
IplImage* img;
struct feature* features;
int n = 0;
arg_parse( argc, argv );
fprintf( stderr, "Finding SIFT features...\n" );
img = cvLoadImage( img_file_name, 1 );
if( ! img )
fatal_error( "unable to load image from %s", img_file_name );
n = _sift_features( img, &features, intvls, sigma, contr_thr, curv_thr,
img_dbl, descr_width, descr_hist_bins );
fprintf( stderr, "Found %d features.\n", n );
if( display )
{
draw_features( img, features, n );
display_big_img( img, img_file_name );
cvWaitKey( 0 );
}
if( out_file_name != NULL )
export_features( out_file_name, features, n );
if( out_img_name != NULL )
cvSaveImage( out_img_name, img, NULL );
cvReleaseImage( &img );
return 0;
}
int main( int argc, char** argv )
{
IplImage* img;
struct feature* feat;
char* name;
int n;
char feat_image_name[200];
if (argc==3){//command:dspFeat .sift image
feat_file=argv[1];
img_file=argv[2];
}
img = cvLoadImage( img_file, 1 );
if( ! img )
fatal_error( "unable to load image from %s", img_file );
n = import_features( feat_file, feat_type, &feat );
if( n == -1 )
fatal_error( "unable to import features from %s", feat_file );
name = feat_file;
draw_features( img, feat, n );
cvNamedWindow( name, 1 );
cvShowImage( name, img );
sprintf_s(feat_image_name,200,"%s.jpg",feat_file);
cvSaveImage(feat_image_name,img,0);
cvWaitKey( 0 );
return 0;
}
int FeaturesDetectionApplication::main_loop(program_options::variables_map &options)
{
printf("FeaturesDetectionApplication::main_loop says hello world !\n");
//init_gui(options);
//run_gui();
// initialization ---
gst_video_input_p.reset(new GstVideoInput(options));
features_detector_p.reset(new SimpleFAST(options));
// video output ---
rgb8_cimg_t current_image(gst_video_input_p->get_image_dimensions());
gst_video_input_p->get_new_image(current_image.view); // copy the data
CImgDisplay video_display(current_image.dimx(), current_image.dimy(), get_application_title().c_str());
video_display.show();
video_display.display(current_image);
// intermediary image --
gray8_image_t gray_image(current_image.view.dimensions());
// main loop ---
do
{
// get new image --
gst_video_input_p->get_new_image(current_image.view); // copy the data
// color to gray_image
copy_and_convert_pixels(current_image.view, boost::gil::view(gray_image));
// compute features
const vector<FASTFeature> &features =
features_detector_p->detect_features((const_view(gray_image)));
// plot features on output image
draw_features(features, current_image);
video_display.display(current_image);
// add a delay ---
wait_some_seconds(0.1); // [seconds]
}
while (video_display.is_closed == false);
return 0;
}
// [ref] ${OPENSIFT_HOME}/src/siftfeat.c
void extract_feature()
{
#if 1
const std::string in_img_file_name("./data/feature_analysis/sift/beaver.png");
const std::string out_sift_file_name("./data/feature_analysis/sift/beaver.sift");
const std::string out_img_file_name;
#elif 0
const std::string in_img_file_name("./data/feature_analysis/sift/marker_pen_2.bmp");
const std::string out_sift_file_name("./data/feature_analysis/sift/marker_pen_2.sift");
const std::string out_img_file_name;
#endif
const int display = 1;
const int intvls = SIFT_INTVLS;
const double sigma = SIFT_SIGMA;
const double contr_thr = SIFT_CONTR_THR;
const int curv_thr = SIFT_CURV_THR;
const int img_dbl = SIFT_IMG_DBL;
const int descr_width = SIFT_DESCR_WIDTH;
const int descr_hist_bins = SIFT_DESCR_HIST_BINS;
std::cout << "finding SIFT features..." << std::endl;
IplImage *img = cvLoadImage(in_img_file_name.c_str(), 1);
if (!img)
{
std::cout <<"unable to load image from " << in_img_file_name << std::endl;
return;
}
struct feature *features;
const int n = _sift_features(img, &features, intvls, sigma, contr_thr, curv_thr, img_dbl, descr_width, descr_hist_bins);
std::cout << "found " << n << " features." << std::endl;
if (display)
{
draw_features(img, features, n);
cvNamedWindow(in_img_file_name.c_str(), 1);
cvShowImage(in_img_file_name.c_str(), img);
cvWaitKey(0);
}
if (!out_sift_file_name.empty())
export_features((char *)out_sift_file_name.c_str(), features, n);
if (!out_img_file_name.empty())
cvSaveImage(out_img_file_name.c_str(), img);
}
int main( int argc, char** argv )
{
IplImage* img;
struct feature* feat;
char* name;
int n;
img = cvLoadImage( img_file, 1 );
if( ! img )
fatal_error( "unable to load image from %s", img_file );
n = import_features( feat_file, feat_type, &feat );
if( n == -1 )
fatal_error( "unable to import features from %s", feat_file );
name = feat_file;
draw_features( img, feat, n );
cvNamedWindow( name, 1 );
cvShowImage( name, img );
cvWaitKey( 0 );
return 0;
}
/* <ww, wh> is the size of the OpenGL window
*/
void draw_frame (int ww, int wh, botlcm_image_t **img1, botlcm_image_t **img2, int nimg, navlcm_feature_list_t *features1, navlcm_feature_list_t *features2, navlcm_feature_match_set_t *matches, double user_scale, double *user_trans, gboolean feature_finder_enabled, gboolean select, navlcm_feature_t *highlight_f, navlcm_feature_match_t *highlight_m, navlcm_feature_t *match_f1, navlcm_feature_t *match_f2, navlcm_feature_match_t *select_m, navlcm_feature_match_t *match, int feature_type, double precision, double recall)
{
if (!img1[0]) return;
// determine scale factor
float window_scale = .95*fmin (.25*ww/img1[0]->width, 1.0*wh/img1[0]->height);
float ratio = user_scale* window_scale;
double trans1[2] = {user_trans[0], user_trans[1]};
double trans2[2] = {user_trans[0], user_trans[1] + ratio*img1[0]->height};
if (!select) {
// draw images
draw_images (img1, nimg, ratio, trans1);
draw_images (img2, nimg, ratio, trans2);
}
// this is the current match to be (or not to be) added to ground-truth
if (match) {
draw_match (match, GREEN, 2, img1[0]->width, img1[0]->height, ratio, trans1, trans2);
draw_match_ends (match, RED, 4, img1[0]->width, img1[0]->height, ratio, trans1, trans2);
}
// draw features
assert (check_gl_error ("1"));
draw_features (features1, RED, 4, ratio, trans1, select, NAME_POINT1, highlight_f, feature_finder_enabled);
assert (check_gl_error ("1"));
draw_features (features2, RED, 4, ratio, trans2, select, NAME_POINT2, highlight_f, feature_finder_enabled);
assert (check_gl_error ("1"));
// draw matches
draw_matches (matches, YELLOW, 2, img1[0]->width, img1[0]->height, ratio, trans1, trans2, select, highlight_m, select_m);
// draw selected items
if (features1 && features2) {
draw_select_feature (match_f1, features1->width, GREEN, 12, ratio, trans1);
draw_select_feature (match_f2, features2->width, GREEN, 12, ratio, trans2);
}
// draw feature thumbnails
if (!select && select_m) {
draw_img_subregion (img1, nimg, select_m->src.col, select_m->src.row, select_m->src.sensorid, select_m->src.scale, select_m->src.ori, feature_type, 0, 0);
draw_img_subregion (img2, nimg, select_m->dst[0].col, select_m->dst[0].row, select_m->dst[0].sensorid, select_m->dst[0].scale, select_m->dst[0].ori, feature_type, 0, wh/2);
} else if (!select && highlight_m) {
draw_img_subregion (img1, nimg, highlight_m->src.col, highlight_m->src.row, highlight_m->src.sensorid, highlight_m->src.scale, highlight_m->src.ori, feature_type, 0, 0);
draw_img_subregion (img2, nimg, highlight_m->dst[0].col, highlight_m->dst[0].row, highlight_m->dst[0].sensorid, highlight_m->dst[0].scale, highlight_m->dst[0].ori, feature_type, 0, wh/2);
} else {
if (!select && highlight_f) {
draw_img_subregion (img1, nimg, highlight_f->col, highlight_f->row, highlight_f->sensorid, highlight_f->scale, highlight_f->ori, feature_type, 0, 0);
draw_img_subregion (img2, nimg, highlight_f->col, highlight_f->row, highlight_f->sensorid, highlight_f->scale, highlight_f->ori, feature_type, 0, wh/2);
}
if (!select && match_f1)
draw_img_subregion (img1, nimg, match_f1->col, match_f1->row, match_f1->sensorid, match_f1->scale, match_f1->ori, feature_type, 0, 0);
if (!select && match_f2)
draw_img_subregion (img2, nimg, match_f2->col, match_f2->row, match_f2->sensorid, match_f2->scale, match_f2->ori, feature_type, 0, wh/2);
}
assert (check_gl_error ("1"));
if (!select) {
// display text info
if (matches)
display_msg (10, wh-20, ww, wh, RED, 0, "# matches: %d", matches->num);
if (features1 && features2)
display_msg (200, wh-20, ww, wh, RED, 0, "# features: %d/%d", features1->num, features2->num);
display_msg (500, wh-20, ww, wh, RED, 0, "precision: %.2f%% recall: %.2f %%", 100.0*precision, 100.0*recall);
}
}
