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svo_analysis

README.md

SVO Analysis

Download Test Data

Create a folder where you will store all datasets, e.g.:

mkdir Datasets

In your .bashrc script, create a new environment variable pointing to the dataset folder:

export SVO_DATASET_DIR=${HOME}/Datasets

Source your new .bashrc script, go to the new dataset folder and download the test data:

source `~/.bashrc`
cd ${SVO_DATASET_DIR}
wget http://rpg.ifi.uzh.ch/datasets/flying_room_1_rig_1.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

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