Comments (9)
Hi @lixiangyu-1008 , I have released the tool that I used for converting sfmlearner result from 5-frames to a whole trajectory.
There are many ways to concatenate the predictions to form a whole trajectory and here is just one of the ways.
please check the following link.
https://github.com/Huangying-Zhan/Depth-VO-Feat/tree/master/tools/sfmlearner_odometry_tool
For visualizing sfmlearner result, I would recommend the following tool:
https://github.com/MichaelGrupp/evo
It is better to view the result in 3D, especially sequence 10. I notice that the 2D visualization in the paper looks weird to some people, including myself at the beginning.
There is a rotation issue in the result and it can be found from the 3D visualization.
Note that, the sfmlearner result that we compared to was the result the authors released.
Please check here
https://github.com/tinghuiz/SfMLearner/blob/master/kitti_eval/download_kitti_pose_eval_data.sh
We recently found that the updated model in SfMlearner give better result and we evaluate the result in one of our recent work. Please check here:
https://arxiv.org/abs/1909.09803
from depth-vo-feat.
Thanks for you reply.
I will have a try!
from depth-vo-feat.
could please share the pose results of sfmlearner? Since the website of download link can not surf.
my email: [email protected]
thanks :)
from depth-vo-feat.
here is the original link
http://people.eecs.berkeley.edu/~tinghuiz/projects/SfMLearner/pose_eval_data.tar
Please let me know if it doesn't work.
from depth-vo-feat.
It's work now, maybe yesterday caused by the internet.
thank you!
from depth-vo-feat.
hi
I have change the SfMlearner to the full trajectory as you said.
but I use the evaluation code to evaluate the seq.9and 10 .the results are:
Sequence: 9
Average translational RMSE (%): 70.42703633858463
Average rotational error (deg/100m): 30.31412894682484
Sequence: 10
Average translational RMSE (%): 51.7403945088599
Average rotational error (deg/100m): 20.95954803583636
-------------------- For Copying ------------------------------
from depth-vo-feat.
Hi, could you post the trajectory plot as well so I can have more clues about the result?
from depth-vo-feat.
hi here is the trajectory and results:
1. solve_global_pose = True:
Sequence: 9
Average translational RMSE (%): 70.42703633858463
Average rotational error (deg/100m): 30.31412894682484
Sequence: 10
Average translational RMSE (%): 51.7403945088599
Average rotational error (deg/100m): 20.95954803583636
-------------------- For Copying ------------------------------
trajectory:
seq.09:
seq.10:
2.solve_global_pose = False:
Sequence: 9
Average translational RMSE (%): 102.76902434117726
Average rotational error (deg/100m): 30.31412894682484
Sequence: 10
Average translational RMSE (%): 97.63435792829532
Average rotational error (deg/100m): 20.95954803583636
-------------------- For Copying ------------------------------
seq.09:
seq.10:
from depth-vo-feat.
I haven't seen something like this before.
If you have modified the tool, could you send me the modified version so I can take a look?
my email: [email protected]
Also, please send me the final trajectory files you got from those setups.
from depth-vo-feat.
Related Issues (20)
- Depth HOT 1
- need gpu for running HOT 4
- Get wrong Results HOT 8
- doubts on the odometry HOT 7
- when I run evaluation_tools.py to generate_depth_npy, has error"target_blobs.size() == source_layer.blobs_size() (5 vs. 3) Incompat ible number of blobs for layer bn_1" HOT 5
- No register converter error occured when running the Python Layer('SE3') in odometry_deploy.prototxt HOT 5
- pretrained model in dropbox can't download HOT 4
- Something Wrong with the odometry result. HOT 5
- F0418 21:31:37.329504 11665 image_data_layer.cpp:49] Check failed: !lines_.empty() File is empty HOT 3
- Hello,when i run ./experiments/depth/train.sh ,it occur a error : no module named pygeometry,but i try import geometry,it works.And i am sure i install PyGeometry module HOT 1
- Questions about "Differentiable geometry modules" HOT 8
- about trajectories plot HOT 2
- For the rmse of odom result HOT 4
- still cannot repeat your experiment, please help! HOT 8
- Training on odometry split HOT 4
- Results of visual odometry on supplementary material.
- hi how to use this project
- Transform relative location to absolute location in SfMLearner HOT 2
- An issue about the compiling of caffe
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