https://github.com/tum-vision/mono_dataset_code
Code for Monocular Visual Odometry Dataset - https://vision.cs.tum.edu/data/datasets/mono-dataset
https://github.com/tum-vision/mono_dataset_code
Last synced: 2 months ago
JSON representation
Code for Monocular Visual Odometry Dataset - https://vision.cs.tum.edu/data/datasets/mono-dataset
- Host: GitHub
- URL: https://github.com/tum-vision/mono_dataset_code
- Owner: tum-vision
- License: bsd-3-clause
- Created: 2016-07-08T08:23:16.000Z (almost 9 years ago)
- Default Branch: master
- Last Pushed: 2023-06-12T04:04:55.000Z (almost 2 years ago)
- Last Synced: 2025-03-30T03:04:09.275Z (2 months ago)
- Language: C++
- Size: 2.59 MB
- Stars: 287
- Watchers: 20
- Forks: 119
- Open Issues: 17
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Install
#### 1. Install Eigen & OpenCV (if you don't have it):
sudo apt-get install libeigen3-dev libopencv-dev
#### 2. install ziplib:
sudo apt-get install zlib1g-dev
cd thirdparty
tar -zxvf libzip-1.1.1.tar.gz
cd libzip-1.1.1/
./configure
make
sudo make install
sudo cp lib/zipconf.h /usr/local/include/zipconf.h # (no idea why that is needed).
#### 3. install aruco marker detection (optional - only required for vignette calibration):
see eg here:
http://maztories.blogspot.de/2013/07/installing-aruco-augmented-reality.html
tested with version 1.3.0. which is included in /thirdparty.
#### 4. Build
cmake . && make
# Usage: C++ code
## playbackDataset: read images, photometric undistortion & rectification.
Shows images of a dataset. Meant as example code regarding how to read the dataset.
Run with (and replace X with the location of the dataset. Mind the trailing slash):
./playDataset X/sequence_01/
optionally, the calibration is used for
- rectification ( r )
- response function inversion ( g )
- vignette removal ( v )
- removal of over-exposed (white) images. ( o ).
Pressing the respective key toggles the option. See code for details.
# responseCalib: calibrate response function.
Performs photometric calibration from a set of images, showing the exact same scene at different exposures.
Run with (and replace X with the location of the dataset. Mind the trailing slash):
./responseCalib X/CalibrationDatasets/narrow_sweep1/"
outputs some intermediate results, and pcalib.txt containing the calibrated inverse response function to ./photoCalibResult.
See code for details.
# vignetteCalib: calibrate vignette.
Performs photometric calibration from a set of images, showing a flat surface with an ARMarker.
Run with (and replace X with the location of the dataset. Mind the trailing slash):
./vignetteCalib X/CalibrationDatasets/narrow_vignette/"
outputs some intermediate results, and vignette.png (16-bit png) containing the calibrated vignette function.
vignetteSmoothed.png is a slightly smoothed version, mainly to remove the black borders (pixels at the border are never observed). See code for details.
**WARNING: requires a lot of Memory (16GB ram for 1000 input images)**! Can easily be changed at the cost of slightly slower runtime... you'll have to do that yourself though.
# Usage: Matlab evaluation code
Implements Sim(3) alignment of a tracked trajectory to the ground-truth segments, and subsequent computation of the different error values. See MatlabEvaluationCode/Example.m for an example, and some documentation regarding the computed values. Further, we include example results computed with DSO for all 50 sequences.
# License
The code provided in this repository is licensed under the BSD license.