how to visualize viz using RViz

[RussellGee]

the gif show the 2D result, i don't know how add the detect results into 2D point cloud. is there some tools to produce ..., i don't know . i am newer to ros rviz. my data source is rosbag from KITTI velodyne_points. step by the usage, i have got the follow out put:

$ rosrun multi_object_tracking_lidar kf_tracker

About to setup callback filterN=0 filterN=1 filterN=2 filterN=3 filterN=4 filterN=5 distMat.size()6 distMat[0].size()6 12.5153 12.1626 20.0648 10.9252 6.92213 26.0863 12.5153 12.1626 20.0648 10.9252 6.92213 26.0863 12.5153 12.1626 20.0648 10.9252 6.92213 26.0863 12.5153 12.1626 20.0648 10.9252 6.92213 26.0863 12.5153 12.1626 20.0648 10.9252 6.92213 26.0863 12.5153 12.1626 20.0648 10.9252 6.92213 26.0863 findIndexOfMin cALLED minEl=3.40282e+38 minIndex=0,4 Received minIndex=0,4 clusterCount=0 findIndexOfMin cALLED minEl=3.40282e+38 minIndex=1,3 Received minIndex=1,3 clusterCount=1 findIndexOfMin cALLED minEl=3.40282e+38 minIndex=2,1 Received minIndex=2,1 clusterCount=2 findIndexOfMin cALLED minEl=3.40282e+38 minIndex=3,0 Received minIndex=3,0 clusterCount=3 findIndexOfMin cALLED minEl=3.40282e+38 minIndex=4,2 Received minIndex=4,2 clusterCount=4 findIndexOfMin cALLED minEl=3.40282e+38 minIndex=5,5 Received minIndex=5,5 clusterCount=5 filterN=0 filterN=1 filterN=2 filterN=3 filterN=4 filterN=5 distMat.size()6 distMat[0].size()6 11.5807 5.98043 6.29488 10.3126 25.6532 12.725 11.3332 5.60705 5.95035 9.93752 25.2852 12.6304 11.0587 5.68 5.90826 10.0085 25.6847 12.1575 11.4436 6.4903 6.62139 10.8004 26.6076 12.1298 13.9819 8.2814 8.69094 12.5877 26.9738 14.7729 11.477 4.91065 5.55812 9.11519 23.712 13.4483 findIndexOfMin cALLED minEl=3.40282e+38 minIndex=5,1 Received minIndex=5,1 clusterCount=0 findIndexOfMin cALLED minEl=3.40282e+38 minIndex=2,2 Received minIndex=2,2 clusterCount=1 findIndexOfMin cALLED minEl=3.40282e+38 minIndex=1,3 Received minIndex=1,3 clusterCount=2 findIndexOfMin cALLED minEl=3.40282e+38 minIndex=3,0 Received minIndex=3,0 clusterCount=3 findIndexOfMin cALLED minEl=3.40282e+38 minIndex=0,5 Received minIndex=0,5 clusterCount=4 findIndexOfMin cALLED minEl=3.40282e+38 minIndex=4,4 Received minIndex=4,4 clusterCount=5 filterN=0 filterN=1 filterN=2 filterN=3 filterN=4 filterN=5 distMat.size()6 ...

and the cammand " rostopic echo /viz" : $ rostopic echo /viz markers:

• header: seq: 0 stamp: secs: 0 nsecs: 0 frame_id: "/map" ns: '' id: 0 type: 1 action: 0 pose: position: x: 4.52638244629 y: 5.33555030823 z: 6.87136125634e-05 orientation: x: 0.0 y: 0.0 z: 0.0 w: 0.0 scale: x: 0.3 y: 0.3 z: 0.3 color: r: 0.0 g: 0.0 b: 0.0 a: 1.0 lifetime: secs: 0 nsecs: 0 frame_locked: False points: [] colors: [] text: '' mesh_resource: '' mesh_use_embedded_materials: False

• header: seq: 0 stamp: secs: 0 nsecs: 0 frame_id: "/map" ns: '' id: 1 type: 1 action: 0 pose: position: x: -3.29236984253 y: 16.9774074554 z: -8.0042569607e-05 orientation: x: 0.0 y: 0.0 z: 0.0 w: 0.0 scale: x: 0.3 y: 0.3 z: 0.3 color: r: 1.0 g: 1.0 b: 1.0 a: 1.0 lifetime: secs: 0 nsecs: 0 frame_locked: False points: [] colors: [] text: '' mesh_resource: '' mesh_use_embedded_materials: False

• header: seq: 0 stamp: secs: 0 nsecs: 0 frame_id: "/map" ns: '' id: 2 type: 1 action: 0 pose: position: x: 8.20040512085 y: 8.98066139221 z: 2.25422081002e-08 orientation: x: 0.0 y: 0.0 z: 0.0 w: 0.0 scale: x: 0.3 y: 0.3 z: 0.3 color: r: 0.0 g: 1.0 b: 1.0 a: 1.0 lifetime: secs: 0 nsecs: 0 frame_locked: False points: [] colors: [] text: '' mesh_resource: '' mesh_use_embedded_materials: False

• header: seq: 0 stamp: secs: 0 nsecs: 0 frame_id: "/map" ns: '' id: 3 type: 1 action: 0 pose: position: x: -1.16644775867 y: -9.15706729889 z: 0.000111785302579 orientation: x: 0.0 y: 0.0 z: 0.0 w: 0.0 scale: x: 0.3 y: 0.3 z: 0.3 color: r: 1.0 g: 0.0 b: 1.0 a: 1.0 lifetime: secs: 0 nsecs: 0 frame_locked: False points: [] colors: [] text: '' mesh_resource: '' mesh_use_embedded_materials: False

• header: seq: 0 stamp: secs: 0 nsecs: 0 frame_id: "/map" ns: '' id: 4 type: 1 action: 0 pose: position: x: 0.540309131145 y: 6.70243358612 z: 7.79212678026e-06 orientation: x: 0.0 y: 0.0 z: 0.0 w: 0.0 scale: x: 0.3 y: 0.3 z: 0.3 color: r: 0.0 g: 1.0 b: 0.0 a: 1.0 lifetime: secs: 0 nsecs: 0 frame_locked: False points: [] colors: [] text: '' mesh_resource: '' mesh_use_embedded_materials: False

• header: seq: 0 stamp: secs: 0 nsecs: 0 frame_id: "/map" ns: '' id: 5 type: 1 action: 0 pose: position: x: 3.1932387352 y: 6.08556127548 z: -7.27250744603e-06 orientation: x: 0.0 y: 0.0 z: 0.0 w: 0.0 scale: x: 0.3 y: 0.3 z: 0.3 color: r: 1.0 g: 1.0 b: 1.0 a: 1.0 lifetime: secs: 0 nsecs: 0 frame_locked: False points: [] colors: [] text: '' mesh_resource: '' mesh_use_embedded_materials: False

  i am not sure whether Is the result correct or not

[RussellGee]

i have knew how to visualize viz.

[Surajj4837-th]

I m also trying to visualise the output, will you @praveen-palanisamy or @RussellGee or anyone elaborate the process. The topics are appearing in RViz and /filtered_cloud topic's data is visible but how to see the final output?