From Big to Small: Multi-Scale Local Planar Guidance for Monocular Depth Estimation
arXiv
Supplementary material
This pipeline is used to test the performance of the BTS depth estimation model. It
is subscribed to the camera/kitti
topic and passes the incoming images to the depth model.
The mock_publisher.py
is responsible for publishing the images.
Open a terminal and run:
$ roscore
On a new terminal, run the following code in your terminal once cd
in the directory.
$ python2 main.py
On a new terminal, run the following code in your terminal once cd
in the directory.
$ python2 mock_publisher.py config_test.txt
Where, the config_test.txt
contains the path to the KITTI images to be published.
The config file provides command line utilities in a file format for ease of use. The file contains:
--encoder densenet161_bts
--data_path /home/mcav/DATA/kitti_dataset
--image_path /2011_09_26/2011_09_26_drive_0022_sync/