Accepted at IROS. Will be published soon!!
If you use this software in your research, please cite our publications:
For instructions please refer to the README on each folder:
- train contains tools for training the network for semantic segmentation.Use python main_release_iros.py --savedir <save_dir> --datadir <data_dir> --num-epochs <> --batch-size <> --decoder --iouVal
- trained_models Contains the trained models used in the papers. NOTE: the pytorch version is slightly different from the torch models.
- The dataset: Download the "leftImg8bit" for the RGB images and the "gtFine" for the labels.
- Python 3.6: If you don't have Python3.6 in your system, I recommend installing it with Anaconda
- PyTorch 0.2 and above: Make sure to install the Pytorch version for Python 3.6 with CUDA support (code only tested for CUDA 8.0).
- Additional Python packages: numpy, matplotlib, Pillow, torchvision and visdom (optional for --visualize flag)
In Anaconda you can install with:
conda install numpy matplotlib torchvision Pillow conda install -c conda-forge visdom
If you use Pip (make sure to have it configured for Python3.6) you can install with:
pip install numpy matplotlib torchvision Pillow visdom
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which allows for personal and research use only. For a commercial license please contact the authors. You can view a license summary here: http://creativecommons.org/licenses/by-nc/4.0/