openGPC

Implements the sparse stereo method Global Patch Collider by Shenlong Wang, Sean Ryan Fanello, Christoph Rhemann, Shahram Izadi, Pushmeet Kohli, CVPR 2016

Requirements

• Eigen3
• libpng
• CMake >= 3.4
• Sintel Stereo or Optical Flow datasets (http://sintel.is.tue.mpg.de/stereo). This is only required if you would like to retrain a forest with different parameters. Example forests are provided in the repository in the forests directory.

Build

This is a header-only library and does not require building. The following instructions show how to build the examples contained in the directory samples. Assuming we are within the root directory of the cloned repository:

cd samples
mkdir build
cd build
cmake ..
make 

The source code heavily relies on SSE instructions, which are enabled by default. To build on another target platform such as ARM, supply the SSE=OFF argument to cmake, i.e. use cmake -DSSE=OFF .. instead of the above cmake ...

Downloading datasets

If you'd like to train with either of the Sintel datasets, please refer to downloadSintelOpticalFlow.sh and downloadSintelStereo.sh in the data directory. These scripts will download and unpack the respective datasets. Please note that both of these downloads are large (2 and 5GB)

Running the examples

All examples have default parameters and run out of the box. Upon calling the executables without arguments, usage information is displayed.

• extract: Mines a dataset from the Sintel dataset and stores it in an intermediary binary format. Requires the OpticalFlow dataset to be present (see section above)
• train: Trains a forest based on the dataset mined with extract. Requires a previously extracted dataset, produced by extract
• sparsematch: Sparse matching based on pretrained forest. Outputs disparity estimate to the build directory.

License

This software is licensed under the BSD 3-Clause License (also see https://opensource.org/licenses/BSD-3-Clause) for non-commercial use:

Copyright (c) 2018, ETH Zurich
All rights reserved.

Redistribution and use in source and binary forms, with or without modification, 
are permitted provided that the following conditions are met:

1. Redistributions of source code must retain the above copyright notice, this 
list of conditions and the following disclaimer.

2. Redistributions in binary form must reproduce the above copyright notice, 
this list of conditions and the following disclaimer in the documentation and/or 
other materials provided with the distribution.

3. Neither the name of the copyright holder nor the names of its contributors 
may be used to endorse or promote products derived from this software without 
specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND 
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED 
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE 
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR 
ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES 
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; 
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON 
ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT 
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS 
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.