calculate average of jacobis and residual to reduce to single point in caclualtion - does not produce desired result

.vscode/c_cpp_properties.json

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

.vscode/settings.json

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

README.md

@@ -1,22 +1,12 @@
 # MSCKF\_VIO
 
 
-The `MSCKF_VIO` package is a stereo-photometric version of MSCKF. The software takes in synchronized stereo images and IMU messages and generates real-time 6DOF pose estimation of the IMU frame.
+The `MSCKF_VIO` package is a stereo version of MSCKF. The software takes in synchronized stereo images and IMU messages and generates real-time 6DOF pose estimation of the IMU frame.
 
-This approach is based on the paper written by Ke Sun et al.
+The software is tested on Ubuntu 16.04 with ROS Kinetic.
-[https://arxiv.org/abs/1712.00036](https://arxiv.org/abs/1712.00036) and their Stereo MSCKF implementation, which tightly fuse the matched feature information of a stereo image pair into a 6DOF Pose.
-The approach implemented in this repository follows the semi-dense msckf approach tightly fusing the photometric
-information around the matched featues into the covariance matrix, as described and derived in the master thesis [Pose Estimation using a Stereo-Photometric Multi-State Constraint Kalman Filter](http://raphael.maenle.net/resources/sp-msckf/maenle_master_thesis.pdf).
-
-It's positioning is comparable to the approach from Ke Sun et al. with the photometric approach, with a higher
-computational load, especially with larger image patches around the feature. A video explaining the approach can be
-found on [https://youtu.be/HrqQywAnenQ](https://youtu.be/HrqQywAnenQ): 
-<br/>
-[![Stereo-Photometric MSCKF](https://img.youtube.com/vi/HrqQywAnenQ/0.jpg)](https://www.youtube.com/watch?v=HrqQywAnenQ)
-
-<br/>
-This software should be deployed using ROS Kinetic on Ubuntu 16.04 or 18.04.
 
+Video: [https://www.youtube.com/watch?v=jxfJFgzmNSw&t](https://www.youtube.com/watch?v=jxfJFgzmNSw&t=3s)<br/>
+Paper Draft: [https://arxiv.org/abs/1712.00036](https://arxiv.org/abs/1712.00036)
 
 ## License
 
@@ -38,6 +28,16 @@ cd your_work_space
 catkin_make --pkg msckf_vio --cmake-args -DCMAKE_BUILD_TYPE=Release
 ```
 
+## Calibration
+
+An accurate calibration is crucial for successfully running the software. To get the best performance of the software, the stereo cameras and IMU should be hardware synchronized. Note that for the stereo calibration, which includes the camera intrinsics, distortion, and extrinsics between the two cameras, you have to use a calibration software. **Manually setting these parameters will not be accurate enough.** [Kalibr](https://github.com/ethz-asl/kalibr) can be used for the stereo calibration and also to get the transformation between the stereo cameras and IMU. The yaml file generated by Kalibr can be directly used in this software. See calibration files in the `config` folder for details. The two calibration files in the `config` folder should work directly with the EuRoC and [fast flight](https://github.com/KumarRobotics/msckf_vio/wiki) datasets. The convention of the calibration file is as follows:
+
+`camx/T_cam_imu`: takes a vector from the IMU frame to the camx frame.
+`cam1/T_cn_cnm1`: takes a vector from the cam0 frame to the cam1 frame.
+
+The filter uses the first 200 IMU messages to initialize the gyro bias, acc bias, and initial orientation. Therefore, the robot is required to start from a stationary state in order to initialize the VIO successfully.
+
+
 ## EuRoC and UPenn Fast flight dataset example usage
 
 First obtain either the [EuRoC](https://projects.asl.ethz.ch/datasets/doku.php?id=kmavvisualinertialdatasets) or the [UPenn fast flight](https://github.com/KumarRobotics/msckf_vio/wiki/Dataset) dataset.
@@ -75,8 +75,6 @@ To visualize the pose and feature estimates you can use the provided rviz config
 
 ## ROS Nodes
 
-The general structure is similar to the structure of the MSCKF implementation this repository is derived from.
-
 ### `image_processor` node
 
 **Subscribed Topics**

config/camchain-imucam-euroc.yaml

@@ -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

config/camchain-imucam-tum-scaled.yaml

@@ -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]

include/msckf_vio/cam_state.h

@@ -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;
 };
 
 

include/msckf_vio/image_handler.h

@@ -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,

include/msckf_vio/image_processor.h

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

include/msckf_vio/math_utils.hpp

@@ -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:

include/msckf_vio/msckf_vio.h

@@ -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(
+    void featureJacobian(const FeatureIDType& feature_id,
-        const FeatureIDType& feature_id,
         const std::vector<StateIDType>& cam_state_ids,
         Eigen::MatrixXd& H_x, Eigen::VectorXd& r);
 
 
-    void twodotMeasurementJacobian(
+    void PhotometricMeasurementJacobian(
-        const StateIDType& cam_state_id,
+    const StateIDType& cam_state_id,
-        const FeatureIDType& feature_id,
+    const FeatureIDType& feature_id,
-        Eigen::MatrixXd& H_x, Eigen::MatrixXd& H_y, Eigen::VectorXd& r);
+    Eigen::MatrixXd& H_x,
+    Eigen::MatrixXd& H_y,
+    Eigen::VectorXd& r);
 
-    bool ConstructJacobians(
+    void PhotometricFeatureJacobian(
-        Eigen::MatrixXd& H_rho,
+    const FeatureIDType& feature_id,
-        Eigen::MatrixXd& H_pl,
+    const std::vector<StateIDType>& cam_state_ids,
-        Eigen::MatrixXd& H_pA,
+    Eigen::MatrixXd& H_x, Eigen::VectorXd& r);
-        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(
-        const StateIDType& cam_state_id,
-        const FeatureIDType& feature_id,
-        Eigen::MatrixXd& H_x,
-        Eigen::MatrixXd& H_y,
-        Eigen::VectorXd& r);
-
-
-    bool twodotFeatureJacobian(
-        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;

launch/image_processor_tinytum.launch

@@ -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>

launch/image_processor_tum.launch

@@ -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"/>

launch/msckf_vio_debug_tum.launch

@@ -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)"/>

launch/msckf_vio_euroc.launch

@@ -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)"/>
 

launch/msckf_vio_tinytum.launch

@@ -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>

launch/msckf_vio_tum.launch

@@ -17,16 +17,14 @@
       args='standalone msckf_vio/MsckfVioNodelet'
       output="screen">
 
-
+      <!-- Photometry Flag-->
-      <!-- Filter Flag, 0 = msckf, 1 = photometric, 2 = two -->
+      <param name="PHOTOMETRIC" value="true"/>
-      <param name="FILTER" value="1"/>
 
       <!-- Debugging Flaggs -->
-      <param name="StreamPause" value="true"/>
+      <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)"/>
 
@@ -73,6 +71,4 @@
     </node>
   </group>
 
-  <!--node name="player" pkg="bagcontrol" type="control.py" /-->
-
 </launch>

log

@@ -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
- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 313.795 -58.7912 139.778 -46.7616 144.055 86.9644 0 -314.123 55.6434 -140.648 46.7616 -144.055 -86.9644 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 441.06 -94.50069999999999 174.424 -53.7653 204.822 120.248 0 -441.685 90.1101 -175.657 53.7653 -204.822 -120.248 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 225.35 -54.5629 77.60599999999999 -21.1425 105.886 60.3706 0 -225.756 52.3373 -78.2406 21.1425 -105.886 -60.3706 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 175.128 20.6203 175.127 -79.63939999999999 73.245 62.1868 0 -174.573 -22.5235 -175.576 79.63939999999999 -73.245 -62.1868 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 296.962 43.5469 311.307 -143.667 123.399 108.355 0 -295.905 -46.7952 -312.063 143.667 -123.399 -108.355 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 126.283 117.889 311.864 -161.264 38.8521 71.8019 0 -124.464 -119.541 -312.118 161.264 -38.8521 -71.8019 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 49.2502 63.7166 155.071 -80.81950000000001 12.7732 32.1826 0 -48.2934 -64.4113 -155.157 80.81950000000001 -12.7732 -32.1826 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 69.59699999999999 154.579 335.384 -179.355 9.212580000000001 62.0364 0 -67.35599999999999 -155.735 -335.462 179.355 -9.212580000000001 -62.0364 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -66.6965 304.947 500.218 -285.589 -71.31010000000001 55.5058 0 70.8009 -305.077 -499.831 285.589 71.31010000000001 -55.5058 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 323.404 -62.2043 141.092 -46.6015 148.737 89.1108 0 0 0 0 0 0 0 0 -324.336 57.8552 -141.991 46.6015 -148.737 -89.1108 1 0 0 0 0 0 0 0
- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 454.208 -99.3095 175.986 -53.4094 211.276 123.174 0 0 0 0 0 0 0 0 -455.779 93.0992 -177.158 53.4094 -211.276 -123.174 1 0 0 0 0 0 0 0
- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 231.884 -57.0266 78.2559 -20.8926 109.118 61.8183 0 0 0 0 0 0 0 0 -232.824 53.8025 -78.80719999999999 20.8926 -109.118 -61.8183 1 0 0 0 0 0 0 0
- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 181.715 18.8525 177.045 -80.08499999999999 76.3716 63.8254 0 0 0 0 0 0 0 0 -181.07 -20.839 -177.959 80.08499999999999 -76.3716 -63.8254 1 0 0 0 0 0 0 0
- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 308.249 40.5812 314.711 -144.494 128.766 111.207 0 0 0 0 0 0 0 0 -306.972 -43.8825 -316.328 144.494 -128.766 -111.207 1 0 0 0 0 0 0 0
- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 133.309 116.865 315.474 -162.598 42.0763 73.8353 0 0 0 0 0 0 0 0 -130.603 -117.454 -316.931 162.598 -42.0763 -73.8353 1 0 0 0 0 0 0 0
- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 52.4426 63.3607 156.902 -81.5288 14.2139 33.1222 0 0 0 0 0 0 0 0 -50.9976 -63.4393 -157.607 81.5288 -14.2139 -33.1222 1 0 0 0 0 0 0 0
- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 75.5508 154.234 339.369 -180.995 11.859 63.8956 0 0 0 0 0 0 0 0 -72.1041 -153.816 -340.865 180.995 -11.859 -63.8956 1 0 0 0 0 0 0 0
- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -62.0551 306.357 506.351 -288.542 -69.50409999999999 57.4562 0 0 0 0 0 0 0 0 68.6262 -303.028 -508.423 288.542 69.50409999999999 -57.4562 1 0 0 0 0 0 0 0
-
-
-# name: Hy
-# type: matrix
-# rows: 18
-# columns: 14
- 1.56267 0 0 0 0 0 0 0 0 0 0.252873 0 0 0.110387
- 0 1.56267 0 0 0 0 0 0 0 0 0.453168 0 0 0.162961
- 0 0 1.56267 0 0 0 0 0 0 0 0.638441 0 0 0.0873758
- 0 0 0 1.56267 0 0 0 0 0 0 0.21031 0 0 0.0321517
- 0 0 0 0 1.56267 0 0 0 0 0 0.375554 0 0 0.0505151
- 0 0 0 0 0 1.56267 0 0 0 0 0.638441 0 0 -0.0336034
- 0 0 0 0 0 0 1.56267 0 0 0 0.157733 0 0 -0.0232704
- 0 0 0 0 0 0 0 1.56267 0 0 0.212814 0 0 -0.0688343
- 0 0 0 0 0 0 0 0 1.56267 0 0.360532 0 0 -0.187745
- 1.56267 0 0 0 0 0 0 0 0 0 0 0.252873 0 0.322811
- 0 1.56267 0 0 0 0 0 0 0 0 0 0.453168 0 0.467319
- 0 0 1.56267 0 0 0 0 0 0 0 0 0.638441 0 0.245907
- 0 0 0 1.56267 0 0 0 0 0 0 0 0.21031 0 0.135725
- 0 0 0 0 1.56267 0 0 0 0 0 0 0.375554 0 0.225277
- 0 0 0 0 0 1.56267 0 0 0 0 0 0.638441 0 0.012926
- 0 0 0 0 0 0 1.56267 0 0 0 0 0.157733 0 -0.0108962
- 0 0 0 0 0 0 0 1.56267 0 0 0 0.212814 0 -0.06974909999999999
- 0 0 0 0 0 0 0 0 1.56267 0 0 0.360532 0 -0.318846
-
-
-# name: r
-# type: matrix
-# rows: 18
-# columns: 1
- 0.0354809
- 0.0153183
- 0.0570191
- -0.0372801
- 0.0878601
- 0.06811780000000001
- -0.00426164
- 5.162985999041026e-321
- 6.927779999999998e-310
- 0
- 2.121999999910509e-314
- 0
- 0
- 0
- 3.6073900000086e-313
- 4.446590812571219e-323
- 3.952525166729972e-323
- 3.952525166729972e-323
-
-

src/bagcontrol.py

@@ -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()

src/control.py

@@ -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()

src/image_handler.cpp

@@ -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);
-  } 
+  } else if (distortion_model == "equidistant") {
-  // equidistant
-  else if (distortion_model == "equidistant") {
     cv::fisheye::undistortPoints(pts_in, pts_out, K, distortion_coeffs,
                                  rectification_matrix, K_new);
-  }
+  } else {
-  // 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 {
     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 {
-  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 {
     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 {
-  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 {
     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 {
-  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 {
     ROS_WARN_ONCE("The model %s is unrecognized, using radtan instead...",
                   distortion_model.c_str());
     std::vector<cv::Point3f> homogenous_pts;
@@ -289,5 +155,5 @@ cv::Point2f distortPoint(
   return pts_out[0];
 }
 
-  } // namespace image_handler
+	} // namespace image_handler
 } // namespace msckf_vio

src/image_processor.cpp

@@ -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
+  //cout << "==================================" << endl;
-  //if(STREAMPAUSE)
-   // nh.setParam("/play_bag_image", false);
 
   // 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)
@@ -647,14 +619,9 @@ void ImageProcessor::stereoMatch(
     image_handler::undistortPoints(cam0_points, cam0.intrinsics, cam0.distortion_model,
                     cam0.distortion_coeffs, cam0_points_undistorted,
                     R_cam0_cam1);
-<<<<<<< HEAD
-    cam1_points = distortPoints(cam0_points_undistorted, cam1_intrinsics,
-                                cam1_distortion_model, cam1_distortion_coeffs);
-=======
 
     cam1_points = image_handler::distortPoints(cam0_points_undistorted, cam1.intrinsics,
                                 cam1.distortion_model, cam1.distortion_coeffs);
->>>>>>> photometry-jakobi
   }
 
   // Track features using LK optical flow method.
@@ -692,8 +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(
@@ -703,7 +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]);

src/shrinkImage.py

@@ -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)