/KITTI-3D-Object-Visualization

Tools to visualize KITTI 3D object BBOX.

Primary LanguagePython

README

KITTI Dataset

This code helps visualize KITTI 3D object detection results based on KITTI DevKit. Data could be downloaded from official website and organized as follows:

<kitti-dataset-root>
|--training
  |--calib
    |--000000.txt
    |--000001.txt
    |--...
  |--image_2
    |--000000.png
    |--000001.png
    |--...
  |--label_2
    |--000000.txt
    |--000001.txt
    |--...
  |--pred_2
    |--000000.txt
    |--000001.txt
    |--...
|--testing
  |--calib
    |--000000.txt
    |--000001.txt
    |--...
  |--image_2
    |--000000.png
    |--000001.png
    |--...

Place predictions in /pred_2 folder to see results.

Installation

Dependencies

python == 3.8.10
matplotlib==3.5.2
numpy==1.23.0
pandas==1.4.3
Pillow==9.2.0
tqdm==4.64.0

Clone this repository

git clone git@github.com:QQQQ00243/KITTI-3D-Object-Visualization.git
cd KITTI-3D-Object-Visualization

Run

python run_demo.py --root-dir <root-of-dataset> --dataset <train-or-test> --output-dir <directory-to-save-plots> --pred <see-predictions>

By default, a folder named outputs will be created, where .png file with same index as its corresponding label file will be saved.

Demonstration of Results

Below are the results for GUPNet (Geometry Uncertainty Projection Network for Monocular 3D Object Detection).