# KITTI-Dataset **Repository Path**: myth1665/KITTI-Dataset ## Basic Information - **Project Name**: KITTI-Dataset - **Description**: Visualising LIDAR data from KITTI dataset. - **Primary Language**: Unknown - **License**: Apache-2.0 - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 1 - **Forks**: 0 - **Created**: 2020-11-03 - **Last Updated**: 2021-03-30 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # KITTI Dataset Exploration ## Dependencies Apart from the common dependencies like `numpy` and `matplotlib` notebook requires [`pykitti`](https://github.com/utiasSTARS/pykitti). You can install `pykitti` via pip using: ``` pip install pykitti ``` ## Project structure | File | Description | | ---------------------- | ------------------------------------------------------------------------------------------------ | | `kitti-dataset.ipynb` | Jupyter Notebook with dataset visualisation routines and output. | | `parseTrackletXML.py` | Methods for parsing tracklets (e.g. dataset labels), originally created by Christian Herdtweck. | | `utilities.py` | Convenient logging routines. | ## Dataset I have used one of the raw datasets available on [KITTI website](http://www.cvlibs.net/datasets/kitti/raw_data.php). See the first one in the list: [2011_09_26_drive_0001 (0.4 GB)](http://kitti.is.tue.mpg.de/kitti/raw_data/2011_09_26_drive_0001/2011_09_26_drive_0001_sync.zip). * **Length**: 114 frames (00:11 minutes) * **Image resolution**: `1392 x 512` pixels * **Labels**: 12 Cars, 0 Vans, 0 Trucks, 0 Pedestrians, 0 Sitters, 2 Cyclists, 1 Trams, 0 Misc I mainly focused on point cloud data and plotting labeled tracklets for visualisation. Cars are marked in **blue**, trams in **red** and cyclists in **green**.

Point cloud data with labels

For a more in-depth exploration and implementation details [see notebook](kitti-dataset.ipynb).