DATA.md

Prepare datasets

It is recommended to symlink the dataset root to $MONOCULAR-DEPTH-ESTIMATION-TOOLBOX/data. If your directory structure is different, you may need to change the corresponding paths in the config files.

KITTI

Download the offical dataset from this link, including the raw data (about 200G) and the fine-grained ground-truth depth maps.

Then, unzip the files into data/kitti. Remember to organize the directory structure following instructions (only need a few cut operations), and copy split files (names started with kitti) in splits folder into data/kitti. Here, We use eigen splits following the previous methods. The data directory structure is as follows：

GEDepth
├── depth
├── tools
├── configs
├── splits
├── data
│   ├── kitti
│   │   ├── input
│   │   │   ├── 2011_09_26
│   │   │   ├── 2011_09_28
│   │   │   ├── ...
│   │   │   ├── 2011_10_03
│   │   ├── gt_depth
│   │   │   ├── 2011_09_26_drive_0001_sync
│   │   │   ├── 2011_09_26_drive_0002_sync
│   │   │   ├── ...
│   │   │   ├── 2011_10_03_drive_0047_sync
│   │   ├── kitti_eigen_train.txt
│   │   ├── kitti_eigen_test.txt

Finally, pre-process the data to pre-compute the ground embedding and ground slope:

$ cd GEDepth
$ python tools/preprocess_data_kitti.py

DDAD

Download the offical dataset from this link.

Finally, pre-process the data to pre-compute the ground embedding and ground slope:

$ cd GEDepth
$ python tools/preprocess_data_ddad.py