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VBR Development Kit

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VBR Development Kit

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This kit contains utilities to work on the VBR SLAM dataset -# :hammer_and_wrench: Install +# Install ```shell pip install vbr-devkit ``` -# :rocket: Usage -You will find here the list of available commands to interact with our dataset +You can install autocompletion for our package by typing: + +```shell +vbr --install-completion +``` + +you might need to restart the shell for the autocompletion to take effect. +# Usage ## Download sequences +You can list the available sequences you can download by typing: + +```shell +vbr list +``` +You should see something similar to this +![list](https://github.com/rvp-group/vbr-devkit/assets/5305530/c195e5b0-c5ee-4abb-a7f5-2ce97474ac4f) + +After choosing your sequence, you can type + ```shell -vbr_download --dataset --save-dir +vbr download ``` -You can get the list of all the available sequences by using the `-h | --help` flag +For instance, we could save `campus_train0` as follows: ```shell -❯ vbr_download -h -usage: vbr_download [-h] --dataset - {all,campus_test0,campus_test1,campus_train0,campus_train1,ciampino_test0,ciampino_t -est1,ciampino_train0,ciampino_train1,colosseo_test0,colosseo_train0,diag_test0,diag_train0,pincio_test0, -pincio_train0,spagna_test0,spagna_train0} - --save-dir PATH +vbr download campus_train0 ~/data/ +``` +**N.B.** The script will actually save the sequence at `/vbr_slam//`. Moreover, by calling the previous command, we expect the following directory: +``` +data + - vbr_slam + - campus + - campus_train0 + - vbr_calib.yaml + - campus_train0_gt.txt + - campus_train0_00.bag + - campus_train0_01.bag + - campus_train0_02.bag + - campus_train0_03.bag + - campus_train0_04.bag +``` + +## Convert format -╭─ options ────────────────────────────────────────────────────────────────────────────────────────────╮ -│ -h, --help show this help message and exit │ -│ --dataset │ -│ {all,campus_test0,campus_test1,campus_train0,campus_train1,ciampino_test0,ciampino_test1,ciampino_t… │ -│ (required) │ -│ --save-dir PATH (required) │ -╰──────────────────────────────────────────────────────────────────────────────────────────────────────╯ +The sequences are provided in ROS1 format. We offer a convenient tool to change representation if you prefer working on a different format. +You can see the supported formats by typing: + +```shell +vbr convert --help ``` +To convert a bag or a sequence of bags, type: +```shell +vbr convert +``` + +for instance, we could convert the `campus_train0` sequence to `kitti` format as follows: + +```shell +vbr convert kitti ~/data/vbr_slam/campus/campus_train0/campus_train0_00.bag ~/data/campus_train0_00_kitti/ +``` + +We can expect the following result: + +``` +data + - campus_train0_00_kitti + - camera_left + - timestamps.txt + - data + - 0000000000.png + - 0000000001.png + - ... + - camera_right + - timestamps.txt + - data + - 0000000000.png + - 0000000001.png + - ... + - ouster_points + - timestamps.txt + - data + - .dtype.pkl + - 0000000000.bin + - 0000000001.bin + - ... + - ... +``` + +**N.B.** In KITTI format, point clouds are embedded in binary files that can be opened using `Numpy` and `pickle` as follows: + +```python +import numpy as np +import pickle + +with open("campus_train0_00_kitti/ouster_points/data/.dtype.pkl", "rb") as f: + cdtype = pickle.load(f) + +cloud_numpy = np.fromfile("/campus_train0_00_kitti/ouster_points/data/0000000000.bin", dtype=cdtype) +```