fixstars / Libsgm
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libSGM
A CUDA implementation performing Semi-Global Matching.
Introduction
libSGM is library that implements in CUDA the Semi-Global Matching algorithm.
From a pair of appropriately calibrated input images, we can obtain the disparity map.
Features
Because it uses CUDA, we can compute the disparity map at high speed.
Performance
The libSGM performance obtained from benchmark sample
Settings
- image size : 1024 x 440
- disparity size : 128
- sgm path : 4 path
- subpixel : enabled
Results
| Device | CUDA version | Processing Time[Milliseconds] | FPS |
|---|---|---|---|
| GTX 1080 Ti | 10.1 | 2.0 | 495.1 |
| GeForce RTX 3080 | 11.1 | 1.5 | 651.3 |
| Tegra X2 | 10.0 | 28.5 | 35.1 |
| Xavier(MODE_15W) | 10.2 | 17.3 | 57.7 |
| Xavier(MAXN) | 10.2 | 9.0 | 110.7 |
Requirements
libSGM needs CUDA (compute capabilities >= 3.5) to be installed.
Moreover, to build the sample, we need the following libraries:
- OpenCV 3.0 or later
- CMake 3.1 or later
Build Instructions
$ git clone https://github.com/fixstars/libSGM.git
$ cd libSGM
$ git submodule update --init # It is needed if ENABLE_TESTS option is set to ON
$ mkdir build
$ cd build
$ cmake ../ # Several options available
$ make
Sample Execution
$ pwd
.../libSGM
$ cd build
$ cmake .. -DENABLE_SAMPLES=on
$ make
$ cd sample/movie/
$ ./stereo_movie <left image path format> <right image path format> <disparity_size>
left image path format: the format used for the file paths to the left input images
right image path format: the format used for the file paths to the right input images
disparity_size: the maximum number of disparities (optional)
"disparity_size" is optional. By default, it is 128.
Next, we explain the meaning of the "left image path format" and "right image path format".
When provided with the following set of files, we should pass the "path formats" given below.
left_image_0000.pgm
left_image_0001.pgm
left_image_0002.pgm
left_image_0003.pgm
...
right_image_0000.pgm
right_image_0001.pgm
right_image_0002.pgm
right_image_0003.pgm
$ ./stereo_movie left_image_%04d.pgm right_image_%04d.pgm
The sample images available at Daimler Urban Scene Segmentation Benchmark Dataset 2014 are used to test the software.
Test Execution
libSGM uses Google Test for tests as Git submodule.
So, we need to init submodule by following command firstly.
$ pwd
.../libSGM
$ git submodule update --init
We can run tests after a build.
$ pwd
.../libSGM
$ cd build
$ cd test
$ ./sgm-test
Test code compares our implementation of each functions to naive implementation.
Author
The "adaskit Team"
The adaskit is an open-source project created by Fixstars Corporation and its subsidiary companies including Fixstars Autonomous Technologies, aimed at contributing to the ADAS industry by developing high-performance implementations for algorithms with high computational cost.
License
Apache License 2.0