A minimal set of tools for working with the KITTI dataset in Python
Project description
This package provides a minimal set of tools for working with the KITTI dataset [1] in Python. So far only the raw datasets and associated calibration data are supported.
Setup
To get started, simply clone the repository to your machine
git clone https://github.com/utiasSTARS/pykitti.git
and run the provided setup tool
cd pykitti python setup.py install
Notation
Homogeneous coordinate transformations are provided as 4x4 numpy.array objects and are denoted as T_destinationFrame_originFrame.
Pinhole camera intrinsics for camera N are provided as 3x3 numpy.array objects and are denoted as K_camN. Stereo pair baselines are given in meters as b_gray for the monochrome stereo pair (cam0 and cam1), and b_rgb for the color stereo pair (cam2 and cam3).
Example
More detailed examples can be found in the demos directory, but the general idea is to specify what dataset you want to load, then load the parts you need and do something with them:
import pykitti
basedir = '/your/dataset/dir'
date = '2011_09_26'
drive = '0019'
# The range argument is optional - default is None, which loads the whole dataset
data = pykitti.raw(basedir, date, drive, range(0, 50, 5))
# Sensor calibration data are loaded automatically
point_cam0 = data.calib.T_cam0_velo.dot(point_velo)
# Other data are loaded only if requested
data.load_oxts()
point_w = data.oxts[0].T_w_imu.dot(point_imu)
data.load_rgb()
cam2_image = data.rgb[0].leftOpenCV
Image data can be automatically converted to an OpenCV-friendly format (i.e., uint8 with BGR color channel ordering) simply by specifying an additional parameter in the image loader function:
data.load_gray(format='cv2') # Loads images as uint8 grayscale
data.load_rgb(format='cv2') # Loads images as uint8 with BGR orderingNote: This package does not actually require that OpenCV be installed on your system, except to run test_raw_cv2.py.
References
[1] A. Geiger, P. Lenz, C. Stiller, and R. Urtasun, “Vision meets robotics: The KITTI dataset,” Int. J. Robot. Research (IJRR), vol. 32, no. 11, pp. 1231–1237, Sep. 2013. http://www.cvlibs.net/datasets/kitti/
