8 Commits

30 changed files with 689 additions and 2761 deletions

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@ -1,16 +0,0 @@
{
"configurations": [
{
"name": "Linux",
"includePath": [
"${workspaceFolder}/**"
],
"defines": [],
"compilerPath": "/usr/bin/gcc",
"cStandard": "c11",
"cppStandard": "c++14",
"intelliSenseMode": "clang-x64"
}
],
"version": 4
}

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@ -1,6 +0,0 @@
{
"files.associations": {
"core": "cpp",
"sparsecore": "cpp"
}
}

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GPATH

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@ -9,7 +9,7 @@ cam0:
0, 0, 0, 1.000000000000000]
camera_model: pinhole
distortion_coeffs: [-0.28340811, 0.07395907, 0.00019359, 1.76187114e-05]
distortion_model: pre-radtan
distortion_model: radtan
intrinsics: [458.654, 457.296, 367.215, 248.375]
resolution: [752, 480]
timeshift_cam_imu: 0.0
@ -26,7 +26,7 @@ cam1:
0, 0, 0, 1.000000000000000]
camera_model: pinhole
distortion_coeffs: [-0.28368365, 0.07451284, -0.00010473, -3.55590700e-05]
distortion_model: pre-radtan
distortion_model: radtan
intrinsics: [457.587, 456.134, 379.999, 255.238]
resolution: [752, 480]
timeshift_cam_imu: 0.0

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@ -1,36 +0,0 @@
cam0:
T_cam_imu:
[-0.9995378259923383, 0.02917807204183088, -0.008530798463872679, 0.047094247958417004,
0.007526588843243184, -0.03435493139706542, -0.9993813532126198, -0.04788273017221637,
-0.029453096117288798, -0.9989836729399656, 0.034119442089241274, -0.0697294754693238,
0.0, 0.0, 0.0, 1.0]
camera_model: pinhole
distortion_coeffs: [0.0034823894022493434, 0.0007150348452162257, -0.0020532361418706202,
0.00020293673591811182]
distortion_model: pre-equidistant
intrinsics: [190.97847715128717, 190.9733070521226, 254.93170605935475, 256.8974428996504]
resolution: [512, 512]
rostopic: /cam0/image_raw
cam1:
T_cam_imu:
[-0.9995240747493029, 0.02986739485347808, -0.007717688852024281, -0.05374086123613335,
0.008095979457928231, 0.01256553460985914, -0.9998882749870535, -0.04648588412432889,
-0.02976708103202316, -0.9994748851595197, -0.0128013601698453, -0.07333210787623645,
0.0, 0.0, 0.0, 1.0]
T_cn_cnm1:
[0.9999994317488622, -0.0008361847221513937, -0.0006612844045898121, -0.10092123225528335,
0.0008042457277382264, 0.9988989443471681, -0.04690684567228134, -0.001964540595211977,
0.0006997790813734836, 0.04690628718225568, 0.9988990492196964, -0.0014663556043866572,
0.0, 0.0, 0.0, 1.0]
camera_model: pinhole
distortion_coeffs: [0.0034003170790442797, 0.001766278153469831, -0.00266312569781606,
0.0003299517423931039]
distortion_model: pre-equidistant
intrinsics: [190.44236969414825, 190.4344384721956, 252.59949716835982, 254.91723064636983]
resolution: [512, 512]
rostopic: /cam1/image_raw
T_imu_body:
[1.0000, 0.0000, 0.0000, 0.0000,
0.0000, 1.0000, 0.0000, 0.0000,
0.0000, 0.0000, 1.0000, 0.0000,
0.0000, 0.0000, 0.0000, 1.0000]

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@ -18,8 +18,6 @@ namespace msckf_vio {
struct Frame{
cv::Mat image;
cv::Mat dximage;
cv::Mat dyimage;
double exposureTime_ms;
};
@ -41,7 +39,6 @@ struct CameraCalibration{
cv::Vec4d distortion_coeffs;
movingWindow moving_window;
cv::Mat featureVisu;
int id;
};

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@ -16,16 +16,6 @@ namespace msckf_vio {
*/
namespace image_handler {
cv::Point2f pinholeDownProject(const cv::Point2f& p_in, const cv::Vec4d& intrinsics);
cv::Point2f pinholeUpProject(const cv::Point2f& p_in, const cv::Vec4d& intrinsics);
void undistortImage(
cv::InputArray src,
cv::OutputArray dst,
const std::string& distortion_model,
const cv::Vec4d& intrinsics,
const cv::Vec4d& distortion_coeffs);
void undistortPoints(
const std::vector<cv::Point2f>& pts_in,
const cv::Vec4d& intrinsics,

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@ -320,8 +320,6 @@ private:
return;
}
bool STREAMPAUSE;
// Indicate if this is the first image message.
bool is_first_img;

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@ -13,6 +13,13 @@
namespace msckf_vio {
inline double absoluted(double a){
if(a>0)
return a;
else return -a;
}
/*
* @brief Create a skew-symmetric matrix from a 3-element vector.
* @note Performs the operation:

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@ -202,111 +202,53 @@ class MsckfVio {
Eigen::Vector4d& r);
// This function computes the Jacobian of all measurements viewed
// in the given camera states of this feature.
bool featureJacobian(
const FeatureIDType& feature_id,
void featureJacobian(const FeatureIDType& feature_id,
const std::vector<StateIDType>& cam_state_ids,
Eigen::MatrixXd& H_x, Eigen::VectorXd& r);
void twodotMeasurementJacobian(
const StateIDType& cam_state_id,
const FeatureIDType& feature_id,
Eigen::MatrixXd& H_x, Eigen::MatrixXd& H_y, Eigen::VectorXd& r);
bool ConstructJacobians(
Eigen::MatrixXd& H_rho,
Eigen::MatrixXd& H_pl,
Eigen::MatrixXd& H_pA,
const Feature& feature,
const StateIDType& cam_state_id,
Eigen::MatrixXd& H_xl,
Eigen::MatrixXd& H_yl);
bool PhotometricPatchPointResidual(
const StateIDType& cam_state_id,
const Feature& feature,
Eigen::VectorXd& r);
bool PhotometricPatchPointJacobian(
const CAMState& cam_state,
const StateIDType& cam_state_id,
const Feature& feature,
Eigen::Vector3d point,
int count,
Eigen::Matrix<double, 2, 1>& H_rhoj,
Eigen::Matrix<double, 2, 6>& H_plj,
Eigen::Matrix<double, 2, 6>& H_pAj,
Eigen::Matrix<double, 2, 4>& dI_dhj);
bool PhotometricMeasurementJacobian(
void PhotometricMeasurementJacobian(
const StateIDType& cam_state_id,
const FeatureIDType& feature_id,
Eigen::MatrixXd& H_x,
Eigen::MatrixXd& H_y,
Eigen::VectorXd& r);
bool twodotFeatureJacobian(
void PhotometricFeatureJacobian(
const FeatureIDType& feature_id,
const std::vector<StateIDType>& cam_state_ids,
Eigen::MatrixXd& H_x, Eigen::VectorXd& r);
bool PhotometricFeatureJacobian(
const FeatureIDType& feature_id,
const std::vector<StateIDType>& cam_state_ids,
Eigen::MatrixXd& H_x, Eigen::VectorXd& r);
void photometricMeasurementUpdate(const Eigen::MatrixXd& H, const Eigen::VectorXd& r);
void measurementUpdate(const Eigen::MatrixXd& H,
const Eigen::VectorXd& r);
void twoMeasurementUpdate(const Eigen::MatrixXd& H, const Eigen::VectorXd& r);
bool gatingTest(const Eigen::MatrixXd& H,
const Eigen::VectorXd&r, const int& dof, int filter=0);
const Eigen::VectorXd&r, const int& dof);
void removeLostFeatures();
void findRedundantCamStates(
std::vector<StateIDType>& rm_cam_state_ids);
void pruneLastCamStateBuffer();
void pruneCamStateBuffer();
// Reset the system online if the uncertainty is too large.
void onlineReset();
// Photometry flag
int FILTER;
bool PHOTOMETRIC;
// debug flag
bool STREAMPAUSE;
bool PRINTIMAGES;
bool GROUNDTRUTH;
bool nan_flag;
bool play;
double last_time_bound;
double time_offset;
// Patch size for Photometry
int N;
// Image rescale
int SCALE;
// Chi squared test table.
static std::map<int, double> chi_squared_test_table;
double eval_time;
IMUState timed_old_imu_state;
IMUState timed_old_true_state;
IMUState old_imu_state;
IMUState old_true_state;
// change in position
Eigen::Vector3d delta_position;
Eigen::Vector3d delta_orientation;
// State vector
StateServer state_server;
StateServer photometric_state_server;
// Ground truth state vector
StateServer true_state_server;
@ -369,7 +311,6 @@ class MsckfVio {
// Subscribers and publishers
ros::Subscriber imu_sub;
ros::Subscriber truth_sub;
ros::Publisher truth_odom_pub;
ros::Publisher odom_pub;
ros::Publisher marker_pub;
ros::Publisher feature_pub;

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@ -1,38 +0,0 @@
<launch>
<arg name="robot" default="firefly_sbx"/>
<arg name="calibration_file"
default="$(find msckf_vio)/config/camchain-imucam-tum-scaled.yaml"/>
<!-- Image Processor Nodelet -->
<group ns="$(arg robot)">
<node pkg="nodelet" type="nodelet" name="image_processor"
args="standalone msckf_vio/ImageProcessorNodelet"
output="screen"
>
<!-- Debugging Flaggs -->
<param name="StreamPause" value="true"/>
<rosparam command="load" file="$(arg calibration_file)"/>
<param name="grid_row" value="4"/>
<param name="grid_col" value="4"/>
<param name="grid_min_feature_num" value="3"/>
<param name="grid_max_feature_num" value="5"/>
<param name="pyramid_levels" value="3"/>
<param name="patch_size" value="15"/>
<param name="fast_threshold" value="10"/>
<param name="max_iteration" value="30"/>
<param name="track_precision" value="0.01"/>
<param name="ransac_threshold" value="3"/>
<param name="stereo_threshold" value="5"/>
<remap from="~imu" to="/imu0"/>
<remap from="~cam0_image" to="/cam0/image_raw"/>
<remap from="~cam1_image" to="/cam1/image_raw"/>
</node>
</group>
</launch>

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@ -11,9 +11,6 @@
output="screen"
>
<!-- Debugging Flaggs -->
<param name="StreamPause" value="true"/>
<rosparam command="load" file="$(arg calibration_file)"/>
<param name="grid_row" value="4"/>
<param name="grid_col" value="4"/>

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@ -22,10 +22,10 @@
<param name="PHOTOMETRIC" value="true"/>
<!-- Debugging Flaggs -->
<param name="PrintImages" value="true"/>
<param name="PrintImages" value="false"/>
<param name="GroundTruth" value="false"/>
<param name="patch_size_n" value="3"/>
<param name="patch_size_n" value="7"/>
<!-- Calibration parameters -->
<rosparam command="load" file="$(arg calibration_file)"/>

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@ -17,18 +17,6 @@
args='standalone msckf_vio/MsckfVioNodelet'
output="screen">
<!-- Filter Flag, 0 = msckf, 1 = photometric, 2 = two -->
<param name="FILTER" value="1"/>
<!-- Debugging Flaggs -->
<param name="StreamPause" value="true"/>
<param name="PrintImages" value="true"/>
<param name="GroundTruth" value="false"/>
<param name="patch_size_n" value="5"/>
<param name="image_scale" value ="1"/>
<!-- Calibration parameters -->
<rosparam command="load" file="$(arg calibration_file)"/>

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@ -1,77 +0,0 @@
<launch>
<arg name="robot" default="firefly_sbx"/>
<arg name="fixed_frame_id" default="world"/>
<arg name="calibration_file"
default="$(find msckf_vio)/config/camchain-imucam-tum-scaled.yaml"/>
<!-- Image Processor Nodelet -->
<include file="$(find msckf_vio)/launch/image_processor_tinytum.launch">
<arg name="robot" value="$(arg robot)"/>
<arg name="calibration_file" value="$(arg calibration_file)"/>
</include>
<!-- Msckf Vio Nodelet -->
<group ns="$(arg robot)">
<node pkg="nodelet" type="nodelet" name="vio"
args='standalone msckf_vio/MsckfVioNodelet'
output="screen">
<param name="FILTER" value="0"/>
<!-- Debugging Flaggs -->
<param name="StreamPause" value="true"/>
<param name="PrintImages" value="false"/>
<param name="GroundTruth" value="false"/>
<param name="patch_size_n" value="3"/>
<param name="image_scale" value ="1"/>
<!-- Calibration parameters -->
<rosparam command="load" file="$(arg calibration_file)"/>
<param name="publish_tf" value="true"/>
<param name="frame_rate" value="20"/>
<param name="fixed_frame_id" value="$(arg fixed_frame_id)"/>
<param name="child_frame_id" value="odom"/>
<param name="max_cam_state_size" value="12"/>
<param name="position_std_threshold" value="8.0"/>
<param name="rotation_threshold" value="0.2618"/>
<param name="translation_threshold" value="0.4"/>
<param name="tracking_rate_threshold" value="0.5"/>
<!-- Feature optimization config -->
<param name="feature/config/translation_threshold" value="-1.0"/>
<!-- These values should be standard deviation -->
<param name="noise/gyro" value="0.005"/>
<param name="noise/acc" value="0.05"/>
<param name="noise/gyro_bias" value="0.001"/>
<param name="noise/acc_bias" value="0.01"/>
<param name="noise/feature" value="0.035"/>
<param name="initial_state/velocity/x" value="0.0"/>
<param name="initial_state/velocity/y" value="0.0"/>
<param name="initial_state/velocity/z" value="0.0"/>
<!-- These values should be covariance -->
<param name="initial_covariance/velocity" value="0.25"/>
<param name="initial_covariance/gyro_bias" value="0.01"/>
<param name="initial_covariance/acc_bias" value="0.01"/>
<param name="initial_covariance/extrinsic_rotation_cov" value="3.0462e-4"/>
<param name="initial_covariance/extrinsic_translation_cov" value="2.5e-5"/>
<param name="initial_covariance/irradiance_frame_bias" value="0.1"/>
<remap from="~imu" to="/imu0"/>
<remap from="~ground_truth" to="/vrpn_client/raw_transform"/>
<remap from="~cam0_image" to="/cam0/image_raw"/>
<remap from="~cam1_image" to="/cam1/image_raw"/>
<remap from="~features" to="image_processor/features"/>
</node>
</group>
</launch>

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@ -17,16 +17,14 @@
args='standalone msckf_vio/MsckfVioNodelet'
output="screen">
<!-- Filter Flag, 0 = msckf, 1 = photometric, 2 = two -->
<param name="FILTER" value="1"/>
<!-- Photometry Flag-->
<param name="PHOTOMETRIC" value="true"/>
<!-- Debugging Flaggs -->
<param name="StreamPause" value="true"/>
<param name="PrintImages" value="false"/>
<param name="PrintImages" value="true"/>
<param name="GroundTruth" value="false"/>
<param name="patch_size_n" value="3"/>
<param name="patch_size_n" value="7"/>
<!-- Calibration parameters -->
<rosparam command="load" file="$(arg calibration_file)"/>
@ -73,6 +71,4 @@
</node>
</group>
<!--node name="player" pkg="bagcontrol" type="control.py" /-->
</launch>

73
log
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@ -1,73 +0,0 @@
# Created by Octave 3.8.1, Wed Jun 12 14:36:37 2019 CEST <raphael@raphael-desktop>
# name: Hx
# type: matrix
# rows: 18
# columns: 49
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# type: matrix
# rows: 18
# columns: 14
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# name: r
# type: matrix
# rows: 18
# columns: 1
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0.0153183
0.0570191
-0.0372801
0.0878601
0.06811780000000001
-0.00426164
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0
2.121999999910509e-314
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3.952525166729972e-323
3.952525166729972e-323

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@ -1,64 +0,0 @@
#!/usr/bin/env python
import rosbag
import rospy
from sensor_msgs.msg import Imu, Image
from geometry_msgs.msg import TransformStamped
import time
import signal
import sys
def signal_handler(sig, frame):
print('gracefully exiting the program.')
bag.close()
sys.exit(0)
def main():
global bag
cam0_topic = '/cam0/image_raw'
cam1_topic = '/cam1/image_raw'
imu0_topic = '/imu0'
grnd_topic = '/vrpn_client/raw_transform'
rospy.init_node('controlbag')
rospy.set_param('play_bag', False)
cam0_pub = rospy.Publisher(cam0_topic, Image, queue_size=10)
cam1_pub = rospy.Publisher(cam1_topic, Image, queue_size=10)
imu0_pub = rospy.Publisher(imu0_topic, Imu, queue_size=10)
grnd_pub = rospy.Publisher(grnd_topic, TransformStamped, queue_size=10)
signal.signal(signal.SIGINT, signal_handler)
bag = rosbag.Bag('/home/raphael/dev/MSCKF_ws/bag/TUM/dataset-corridor1_1024_16.bag')
for topic, msg, t in bag.read_messages(topics=[cam0_topic, cam1_topic, imu0_topic, grnd_topic]):
# pause if parameter set to false
flag = False
while not rospy.get_param('/play_bag'):
time.sleep(0.01)
if not flag:
print("stopped playback")
flag = not flag
if flag:
print("resume playback")
if topic == cam0_topic:
cam0_pub.publish(msg)
elif topic == cam1_topic:
cam1_pub.publish(msg)
elif topic == imu0_topic:
imu0_pub.publish(msg)
elif topic ==grnd_topic:
grnd_pub.publish(msg)
#print msg
bag.close()
if __name__== "__main__":
main()

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@ -1,64 +0,0 @@
#!/usr/bin/env python
import rosbag
import rospy
from sensor_msgs.msg import Imu, Image
from geometry_msgs.msg import TransformStamped
import time
import signal
import sys
def signal_handler(sig, frame):
print('gracefully exiting the program.')
bag.close()
sys.exit(0)
def main():
global bag
cam0_topic = '/cam0/image_raw'
cam1_topic = '/cam1/image_raw'
imu0_topic = '/imu0'
grnd_topic = '/vrpn_client/raw_transform'
rospy.init_node('controlbag')
rospy.set_param('play_bag', False)
cam0_pub = rospy.Publisher(cam0_topic, Image, queue_size=10)
cam1_pub = rospy.Publisher(cam1_topic, Image, queue_size=10)
imu0_pub = rospy.Publisher(imu0_topic, Imu, queue_size=10)
grnd_pub = rospy.Publisher(grnd_topic, TransformStamped, queue_size=10)
signal.signal(signal.SIGINT, signal_handler)
bag = rosbag.Bag('/home/raphael/dev/MSCKF_ws/bag/TUM/dataset-corridor1_1024_16.bag')
for topic, msg, t in bag.read_messages(topics=[cam0_topic, cam1_topic, imu0_topic, grnd_topic]):
# pause if parameter set to false
flag = False
while not rospy.get_param('/play_bag'):
time.sleep(0.01)
if not flag:
print("stopped playback")
flag = not flag
if flag:
print("resume playback")
if topic == cam0_topic:
cam0_pub.publish(msg)
elif topic == cam1_topic:
cam1_pub.publish(msg)
elif topic == imu0_topic:
imu0_pub.publish(msg)
elif topic ==grnd_topic:
grnd_pub.publish(msg)
#print msg
bag.close()
if __name__== "__main__":
main()

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@ -14,40 +14,6 @@ namespace msckf_vio {
namespace image_handler {
cv::Point2f pinholeDownProject(const cv::Point2f& p_in, const cv::Vec4d& intrinsics)
{
return cv::Point2f(p_in.x * intrinsics[0] + intrinsics[2], p_in.y * intrinsics[1] + intrinsics[3]);
}
cv::Point2f pinholeUpProject(const cv::Point2f& p_in, const cv::Vec4d& intrinsics)
{
return cv::Point2f((p_in.x - intrinsics[2])/intrinsics[0], (p_in.y - intrinsics[3])/intrinsics[1]);
}
void undistortImage(
cv::InputArray src,
cv::OutputArray dst,
const std::string& distortion_model,
const cv::Vec4d& intrinsics,
const cv::Vec4d& distortion_coeffs)
{
const cv::Matx33d K(intrinsics[0], 0.0, intrinsics[2],
0.0, intrinsics[1], intrinsics[3],
0.0, 0.0, 1.0);
if (distortion_model == "pre-equidistant")
cv::fisheye::undistortImage(src, dst, K, distortion_coeffs, K);
else if (distortion_model == "equidistant")
src.copyTo(dst);
else if (distortion_model == "pre-radtan")
cv::undistort(src, dst, K, distortion_coeffs, K);
else if (distortion_model == "radtan")
src.copyTo(dst);
}
void undistortPoint(
const cv::Point2f& pt_in,
const cv::Vec4d& intrinsics,
@ -76,37 +42,10 @@ void undistortPoint(
if (distortion_model == "radtan") {
cv::undistortPoints(pts_in, pts_out, K, distortion_coeffs,
rectification_matrix, K_new);
}
// equidistant
else if (distortion_model == "equidistant") {
} else if (distortion_model == "equidistant") {
cv::fisheye::undistortPoints(pts_in, pts_out, K, distortion_coeffs,
rectification_matrix, K_new);
}
// fov
else if (distortion_model == "fov") {
for(int i = 0; i < pts_in.size(); i++)
{
float omega = distortion_coeffs[0];
float rd = sqrt(pts_in[i].x * pts_in[i].x + pts_in[i].y * pts_in[i].y);
float ru = tan(rd * omega)/(2 * tan(omega / 2));
cv::Point2f newPoint(
((pts_in[i].x - intrinsics[2]) / intrinsics[0]) * (ru / rd),
((pts_in[i].y - intrinsics[3]) / intrinsics[1]) * (ru / rd));
pts_out.push_back(newPoint);
}
}
else if (distortion_model == "pre-equidistant" or distortion_model == "pre-radtan")
{
std::vector<cv::Point2f> temp_pts_out;
for(int i = 0; i < pts_in.size(); i++)
temp_pts_out.push_back(pinholeUpProject(pts_in[i], intrinsics));
pts_out = temp_pts_out;
}
else {
} else {
ROS_WARN_ONCE("The model %s is unrecognized, use radtan instead...",
distortion_model.c_str());
cv::undistortPoints(pts_in, pts_out, K, distortion_coeffs,
@ -140,35 +79,10 @@ void undistortPoints(
if (distortion_model == "radtan") {
cv::undistortPoints(pts_in, pts_out, K, distortion_coeffs,
rectification_matrix, K_new);
}
else if (distortion_model == "equidistant") {
} else if (distortion_model == "equidistant") {
cv::fisheye::undistortPoints(pts_in, pts_out, K, distortion_coeffs,
rectification_matrix, K_new);
}
else if (distortion_model == "fov") {
for(int i = 0; i < pts_in.size(); i++)
{
float omega = distortion_coeffs[0];
float rd = sqrt(pts_in[i].x * pts_in[i].x + pts_in[i].y * pts_in[i].y);
float ru = tan(rd * omega)/(2 * tan(omega / 2));
cv::Point2f newPoint(
((pts_in[i].x - intrinsics[2]) / intrinsics[0]) * (ru / rd),
((pts_in[i].y - intrinsics[3]) / intrinsics[1]) * (ru / rd));
pts_out.push_back(newPoint);
}
}
else if (distortion_model == "pre-equidistant" or distortion_model == "pre-radtan")
{
std::vector<cv::Point2f> temp_pts_out;
for(int i = 0; i < pts_in.size(); i++)
temp_pts_out.push_back(pinholeUpProject(pts_in[i], intrinsics));
pts_out = temp_pts_out;
}
else {
} else {
ROS_WARN_ONCE("The model %s is unrecognized, use radtan instead...",
distortion_model.c_str());
cv::undistortPoints(pts_in, pts_out, K, distortion_coeffs,
@ -196,31 +110,7 @@ std::vector<cv::Point2f> distortPoints(
distortion_coeffs, pts_out);
} else if (distortion_model == "equidistant") {
cv::fisheye::distortPoints(pts_in, pts_out, K, distortion_coeffs);
}
else if (distortion_model == "fov") {
for(int i = 0; i < pts_in.size(); i++)
{
// based on 'straight lines have to be straight'
float ru = sqrt(pts_in[i].x * pts_in[i].x + pts_in[i].y * pts_in[i].y);
float omega = distortion_coeffs[0];
float rd = 1 / (omega)*atan(2*ru*tan(omega / 2));
cv::Point2f newPoint(
pts_in[i].x * (rd/ru) * intrinsics[0] + intrinsics[2],
pts_in[i].y * (rd/ru) * intrinsics[1] + intrinsics[3]);
pts_out.push_back(newPoint);
}
}
else if (distortion_model == "pre-equidistant" or distortion_model == "pre-radtan")
{
std::vector<cv::Point2f> temp_pts_out;
for(int i = 0; i < pts_in.size(); i++)
temp_pts_out.push_back(pinholeDownProject(pts_in[i], intrinsics));
pts_out = temp_pts_out;
}
else {
} else {
ROS_WARN_ONCE("The model %s is unrecognized, using radtan instead...",
distortion_model.c_str());
std::vector<cv::Point3f> homogenous_pts;
@ -253,31 +143,7 @@ cv::Point2f distortPoint(
distortion_coeffs, pts_out);
} else if (distortion_model == "equidistant") {
cv::fisheye::distortPoints(pts_in, pts_out, K, distortion_coeffs);
}
else if (distortion_model == "fov") {
for(int i = 0; i < pts_in.size(); i++)
{
// based on 'straight lines have to be straight'
float ru = sqrt(pts_in[i].x * pts_in[i].x + pts_in[i].y * pts_in[i].y);
float omega = distortion_coeffs[0];
float rd = 1 / (omega)*atan(2*ru*tan(omega / 2));
cv::Point2f newPoint(
pts_in[i].x * (rd/ru) * intrinsics[0] + intrinsics[2],
pts_in[i].y * (rd/ru) * intrinsics[1] + intrinsics[3]);
pts_out.push_back(newPoint);
}
}
else if (distortion_model == "pre-equidistant" or distortion_model == "pre-radtan")
{
std::vector<cv::Point2f> temp_pts_out;
for(int i = 0; i < pts_in.size(); i++)
pts_out.push_back(pinholeDownProject(pts_in[i], intrinsics));
pts_out = temp_pts_out;
}
else {
} else {
ROS_WARN_ONCE("The model %s is unrecognized, using radtan instead...",
distortion_model.c_str());
std::vector<cv::Point3f> homogenous_pts;

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@ -42,9 +42,6 @@ ImageProcessor::~ImageProcessor() {
}
bool ImageProcessor::loadParameters() {
// debug parameters
nh.param<bool>("StreamPause", STREAMPAUSE, false);
// Camera calibration parameters
nh.param<string>("cam0/distortion_model",
cam0.distortion_model, string("radtan"));
@ -214,9 +211,7 @@ void ImageProcessor::stereoCallback(
const sensor_msgs::ImageConstPtr& cam0_img,
const sensor_msgs::ImageConstPtr& cam1_img) {
// stop playing bagfile if printing images
//if(STREAMPAUSE)
// nh.setParam("/play_bag_image", false);
//cout << "==================================" << endl;
// Get the current image.
cam0_curr_img_ptr = cv_bridge::toCvShare(cam0_img,
@ -224,27 +219,12 @@ void ImageProcessor::stereoCallback(
cam1_curr_img_ptr = cv_bridge::toCvShare(cam1_img,
sensor_msgs::image_encodings::MONO8);
ros::Time start_time = ros::Time::now();
cv::Mat new_cam0;
cv::Mat new_cam1;
image_handler::undistortImage(cam0_curr_img_ptr->image, new_cam0, cam0.distortion_model, cam0.intrinsics, cam0.distortion_coeffs);
image_handler::undistortImage(cam1_curr_img_ptr->image, new_cam1, cam1.distortion_model, cam1.intrinsics, cam1.distortion_coeffs);
new_cam0.copyTo(cam0_curr_img_ptr->image);
new_cam1.copyTo(cam1_curr_img_ptr->image);
//ROS_INFO("Publishing: %f",
// (ros::Time::now()-start_time).toSec());
// Build the image pyramids once since they're used at multiple places
createImagePyramids();
// Detect features in the first frame.
if (is_first_img) {
start_time = ros::Time::now();
ros::Time start_time = ros::Time::now();
initializeFirstFrame();
//ROS_INFO("Detection time: %f",
// (ros::Time::now()-start_time).toSec());
@ -257,7 +237,7 @@ void ImageProcessor::stereoCallback(
// (ros::Time::now()-start_time).toSec());
} else {
// Track the feature in the previous image.
start_time = ros::Time::now();
ros::Time start_time = ros::Time::now();
trackFeatures();
//ROS_INFO("Tracking time: %f",
// (ros::Time::now()-start_time).toSec());
@ -265,7 +245,6 @@ void ImageProcessor::stereoCallback(
// Add new features into the current image.
start_time = ros::Time::now();
addNewFeatures();
//ROS_INFO("Addition time: %f",
// (ros::Time::now()-start_time).toSec());
@ -288,18 +267,16 @@ void ImageProcessor::stereoCallback(
// (ros::Time::now()-start_time).toSec());
// Publish features in the current image.
start_time = ros::Time::now();
ros::Time start_time = ros::Time::now();
publish();
//ROS_INFO("Publishing: %f",
// (ros::Time::now()-start_time).toSec());
// Update the previous image and previous features.
cam0_prev_img_ptr = cam0_curr_img_ptr;
prev_features_ptr = curr_features_ptr;
std::swap(prev_cam0_pyramid_, curr_cam0_pyramid_);
// Initialize the current features to empty vectors.
curr_features_ptr.reset(new GridFeatures());
for (int code = 0; code <
@ -307,10 +284,6 @@ void ImageProcessor::stereoCallback(
(*curr_features_ptr)[code] = vector<FeatureMetaData>(0);
}
// stop playing bagfile if printing images
//if(STREAMPAUSE)
// nh.setParam("/play_bag_image", true);
return;
}
@ -607,7 +580,6 @@ void ImageProcessor::trackFeatures() {
++after_ransac;
}
// Compute the tracking rate.
int prev_feature_num = 0;
for (const auto& item : *prev_features_ptr)
@ -687,8 +659,6 @@ void ImageProcessor::stereoMatch(
// Further remove outliers based on the known
// essential matrix.
vector<cv::Point2f> cam0_points_undistorted(0);
vector<cv::Point2f> cam1_points_undistorted(0);
image_handler::undistortPoints(
@ -698,7 +668,6 @@ void ImageProcessor::stereoMatch(
cam1_points, cam1.intrinsics, cam1.distortion_model,
cam1.distortion_coeffs, cam1_points_undistorted);
double norm_pixel_unit = 4.0 / (
cam0.intrinsics[0]+cam0.intrinsics[1]+
cam1.intrinsics[0]+cam1.intrinsics[1]);

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@ -1,75 +0,0 @@
#!/usr/bin/env python
from __future__ import print_function
import sys
import rospy
import cv2
from std_msgs.msg import String
from sensor_msgs.msg import Image
from cv_bridge import CvBridge, CvBridgeError
class image_converter:
def __init__(self):
self.image0_pub = rospy.Publisher("/cam0/new_image_raw",Image, queue_size=10)
self.image1_pub = rospy.Publisher("/cam1/new_image_raw",Image, queue_size=10)
self.bridge = CvBridge()
self.image0_sub = rospy.Subscriber("/cam0/image_raw",Image,self.callback_cam0)
self.image1_sub = rospy.Subscriber("/cam1/image_raw",Image,self.callback_cam1)
def callback_cam0(self,data):
try:
cv_image = self.bridge.imgmsg_to_cv2(data, "bgr8")
except CvBridgeError as e:
print(e)
imgScale = 0.25
newX,newY = cv_image.shape[1]*imgScale, cv_image.shape[0]*imgScale
newimg = cv2.resize(cv_image,(int(newX),int(newY)))
newpub = self.bridge.cv2_to_imgmsg(newimg, "bgr8")
newdata = data
newdata.height = newpub.height
newdata.width = newpub.width
newdata.step = newpub.step
newdata.data = newpub.data
try:
self.image0_pub.publish(newdata)
except CvBridgeError as e:
print(e)
def callback_cam1(self,data):
try:
cv_image = self.bridge.imgmsg_to_cv2(data, "bgr8")
except CvBridgeError as e:
print(e)
imgScale = 0.25
newX,newY = cv_image.shape[1]*imgScale, cv_image.shape[0]*imgScale
newimg = cv2.resize(cv_image,(int(newX),int(newY)))
newpub = self.bridge.cv2_to_imgmsg(newimg, "bgr8")
newdata = data
newdata.height = newpub.height
newdata.width = newpub.width
newdata.step = newpub.step
newdata.data = newpub.data
try:
self.image1_pub.publish(newdata)
except CvBridgeError as e:
print(e)
def main(args):
ic = image_converter()
rospy.init_node('image_converter', anonymous=True)
try:
rospy.spin()
except KeyboardInterrupt:
print("Shutting down")
cv2.destroyAllWindows()
if __name__ == '__main__':
main(sys.argv)