int main(int argc, char **argv)
{
ros::init(argc, argv, "uvc_cam");
ros::NodeHandle n;
ros::NodeHandle n_private("~");
std::string device;
std::string out_topic;
n_private.param<std::string>("device", device, "/dev/video0");
n_private.param<std::string>("topic", out_topic, "/camera/image");
int width, height, fps, modetect_lum, modetect_count;
n_private.param("width", width, 640);
n_private.param("height", height, 480);
n_private.param("fps", fps, 30);
n_private.param("motion_threshold_luminance", modetect_lum, 100);
n_private.param("motion_threshold_count", modetect_count, -1);
ros::Publisher pub = n.advertise<sensor_msgs::Image>(out_topic.c_str(), 1);
ROS_INFO("opening uvc_cam at %dx%d, %d fps", width, height, fps);
uvc_cam::Cam cam(device.c_str(), uvc_cam::Cam::MODE_RGB, width, height, fps);
cam.set_motion_thresholds(modetect_lum, modetect_count);
ros::Time t_prev(ros::Time::now());
int count = 0, skip_count = 0;
while (n.ok())
{
unsigned char *frame = NULL;
uint32_t bytes_used;
int buf_idx = cam.grab(&frame, bytes_used);
if (count++ % fps == 0)
{
ros::Time t(ros::Time::now());
ros::Duration d(t - t_prev);
ROS_INFO("%.1f fps skip %d", (double)fps / d.toSec(), skip_count);
t_prev = t;
}
if (frame)
{
sensor_msgs::Image image;
image.header.stamp = ros::Time::now();
image.encoding = sensor_msgs::image_encodings::RGB8;
image.height = height;
image.width = width;
image.step = 3 * width;
image.set_data_size( image.step * image.height );
/*
uint8_t* bgr = &(image.data[0]);
for (uint32_t y = 0; y < height; y++)
for (uint32_t x = 0; x < width; x++)
{
// hack... flip bgr to rgb
uint8_t *p = frame + y * width * 3 + x * 3;
uint8_t *q = bgr + y * width * 3 + x * 3;
q[0] = p[2]; q[1] = p[1]; q[2] = p[0];
}
*/
memcpy(&image.data[0], frame, width * height * 3);
pub.publish(image);
cam.release(buf_idx);
}
else
skip_count++;
}
return 0;
}
/* ------------------------------------------------------------------------- */
void MainWindow::on_method2_clicked()
{
int index_prev;
int index_now;
QString ymlFile;
vector<KeyPoint> imgpts1_tmp;
vector<KeyPoint> imgpts2_tmp;
imgpts.resize(filelist.size());
on_PB_Sift_clicked();
cout << endl << endl << endl << "Using Method 2:" <<endl;
vector<DMatch> matches;
cv::Matx34d P_0;
cv::Matx34d P_1;
P_0 = cv::Matx34d(1,0,0,0,
0,1,0,0,
0,0,1,0);
cv::Mat_<double> t_prev = (cv::Mat_<double>(3,1) << 0, 0, 0);
cv::Mat_<double> R_prev = (cv::Mat_<double>(3,3) << 0, 0, 0,
0, 0, 0,
0, 0, 0);
cv::Mat_<double> R_prev_inv = (cv::Mat_<double>(3,3) << 0, 0, 0,
0, 0, 0,
0, 0, 0);
cv::Mat_<double> t_now = (cv::Mat_<double>(3,1) << 0, 0, 0);
cv::Mat_<double> R_now = (cv::Mat_<double>(3,3) << 0, 0, 0,
0, 0, 0,
0, 0, 0);
cv::Mat_<double> t_new = (cv::Mat_<double>(3,1) << 0, 0, 0);
cv::Mat_<double> R_new = (cv::Mat_<double>(3,3) << 0, 0, 0,
0, 0, 0,
0, 0, 0);
reconstruct_first_two_view();
std::cout << "Pmat[0] = " << endl << Pmats[0]<<endl;
std::cout << "Pmat[1] = " << endl << Pmats[1]<<endl;
for(index_now = 2; index_now<filelist.size(); index_now++)
{
cout << endl << endl << endl <<endl;
cout << "dealing with " << filelist.at(index_now).fileName().toStdString() << endl;
cout << endl;
index_prev = index_now - 1;
descriptors1.release();
descriptors1 = descriptors2;
descriptors2.release();
ymlFile = ymlFileDir;
ymlFile.append(filelist.at(index_now).fileName()).append(".yml");
restore_descriptors_from_file(ymlFile.toStdString(),imgpts[index_now],descriptors2);
matches.clear();
//matching
matching_fb_matcher(descriptors1,descriptors2,matches);
matching_good_matching_filter(matches);
imggoodpts1.clear();
imggoodpts2.clear();
P_0 = cv::Matx34d(1,0,0,0,
0,1,0,0,
0,0,1,0);
P_1 = cv::Matx34d(1,0,0,0,
0,1,0,0,
0,0,1,0);
outCloud.clear();
if(FindCameraMatrices(K,Kinv,distcoeff,
imgpts[index_prev],imgpts[index_now],
imggoodpts1,imggoodpts2,
P_0,P_1,
matches,
outCloud))
{//if can find camera matries
R_prev(0,0) = Pmats[index_prev](0,0);
R_prev(0,1) = Pmats[index_prev](0,1);
R_prev(0,2) = Pmats[index_prev](0,2);
R_prev(1,0) = Pmats[index_prev](1,0);
R_prev(1,1) = Pmats[index_prev](1,1);
R_prev(1,2) = Pmats[index_prev](1,2);
R_prev(2,0) = Pmats[index_prev](2,0);
R_prev(2,1) = Pmats[index_prev](2,1);
R_prev(2,2) = Pmats[index_prev](2,2);
t_prev(0) = Pmats[index_prev](0,3);
t_prev(1) = Pmats[index_prev](1,3);
t_prev(2) = Pmats[index_prev](2,3);
R_now(0,0) = P_1(0,0);
R_now(0,1) = P_1(0,1);
R_now(0,2) = P_1(0,2);
R_now(1,0) = P_1(1,0);
R_now(1,1) = P_1(1,1);
R_now(1,2) = P_1(1,2);
R_now(2,0) = P_1(2,0);
R_now(2,1) = P_1(2,1);
R_now(2,2) = P_1(2,2);
t_now(0) = P_1(0,3);
t_now(1) = P_1(1,3);
t_now(2) = P_1(2,3);
invert(R_prev, R_prev_inv);
t_new = t_prev + R_prev * t_now ;
R_new = R_now * R_prev;
// //store estimated pose
Pmats[index_now] = cv::Matx34d (R_new(0,0),R_new(0,1),R_new(0,2),t_new(0),
R_new(1,0),R_new(1,1),R_new(1,2),t_new(1),
R_new(2,0),R_new(2,1),R_new(2,2),t_new(2));
cout << "Pmats[index_now]:" << endl << Pmats[index_now] << endl;
}
else
{
break;
}
}
cout << endl;
cout << endl;
cout << endl;
//visualization
imgpts.clear();
imgpts.resize(filelist.size());
for( index_now = 1; index_now<filelist.size(); index_now++)
{
index_prev = index_now - 1;
descriptors1.release();
descriptors2.release();
ymlFile = ymlFileDir;
ymlFile.append(filelist.at(index_prev).fileName()).append(".yml");
cout << ymlFile.toStdString()<< endl;
restore_descriptors_from_file(ymlFile.toStdString(),imgpts[index_prev],descriptors1);
ymlFile = ymlFileDir;
ymlFile.append(filelist.at(index_now).fileName()).append(".yml");
cout << ymlFile.toStdString()<< endl;
restore_descriptors_from_file(ymlFile.toStdString(),imgpts[index_now],descriptors2);
matches.clear();
//matching
matching_fb_matcher(descriptors1,descriptors2,matches);
matching_good_matching_filter(matches);
imgpts1_tmp.clear();
imgpts2_tmp.clear();
GetAlignedPointsFromMatch(imgpts[index_prev], imgpts[index_now], matches, imgpts1_tmp, imgpts2_tmp);
cout << imgpts1_tmp.size() << endl;
cout << imgpts1_tmp.size() << endl;
outCloud.clear();
std::vector<cv::KeyPoint> correspImg1Pt;
double mean_proj_err = TriangulatePoints(imgpts1_tmp, imgpts2_tmp, K, Kinv,distcoeff, Pmats[index_prev], Pmats[index_now], outCloud, correspImg1Pt);
std::vector<CloudPoint> outCloud_tmp;
outCloud_tmp.clear();
for (unsigned int i=0; i<outCloud.size(); i++)
{
if(outCloud[i].reprojection_error <= 3){
//cout << "surving" << endl;
outCloud[i].imgpt_for_img.resize(filelist.size());
for(int j = 0; j<filelist.size();j++)
{
outCloud[i].imgpt_for_img[j] = -1;
}
outCloud[i].imgpt_for_img[index_now] = matches[i].trainIdx;
outCloud_tmp.push_back(outCloud[i]);
}
}
outCloud.clear();
outCloud= outCloud_tmp;
cout << outCloud_tmp.size() << endl;
for(unsigned int i=0;i<outCloud.size();i++)
{
outCloud_all.push_back(outCloud[i]);
}
outCloud_new = outCloud;
}
for( int i = 0; i<filelist.size(); i++)
Pmats[i](1,3) =0;
GetRGBForPointCloud(outCloud_all,pointCloudRGB);
ui->widget->update(getPointCloud(),
getPointCloudRGB(),
getCameras());
cout << "finished" <<endl <<endl;
}
