This commit is contained in:
Christian Forster
2014-06-11 17:42:06 +02:00
+2 -27
View File
@@ -14,39 +14,14 @@ Source your new `.bashrc` script, go to the new dataset folder and download the
source `~/.bashrc`
cd ${SVO_DATASET_DIR}
wget http://rpg.ifi.uzh.ch/datasets/flying_room_1_rig_1.tar.gz -O - | tar -xz
TODO: replace this dataset with new ones.
wget http://rpg.ifi.uzh.ch/datasets/sin2_tex2_h1_v8_d.tar.gz -O - | tar -xz
#### Run Benchmark
In the _CMakeLists.txt_ of SVO you need to set the `TRACE` flag to `TRUE` and recompile SVO.
Afterwards run
rosrun svo_analysis benchmark.py flying_room_1_fast
rosrun svo_analysis benchmark.py sin2_tex2_h1_v8_d
The script will create a new folder in `svo_analysis/results/`, run svo on the dataset and save the tracefile in this folder and at the end it will run some scripts to generate plots from the tracefile.
#### Dataset file
A dataset with motion-capture-system ground-truth should contain the following files
* _images.txt_
# timestamp img/imagename
1329330952.725747585296631 img/00000.png
1329330952.765715122222900 img/00001.png
1329330952.805604219436646 img/00002.png
...
* _groundtruth.txt_: groundtruth poses as acquired from a motion capture system
# timestamp tx ty tz qx qy qz qw
* _groundtruth_matched.txt_: the groundtruth pose associated to the images in images.txt. This file can be generated by the command:
cd my_dataset
rosrun svo_analysis associate.py images.txt groundtruth.txt