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Semantic-Segmentation

Publications

"Efficient Semantic Segmentation using Gradual Grouping", Nikitha Vallurupalli, Sriharsha Annamaneni, Girish Varma, C V Jawahar, Manu Mathew, Soyeb Nagori, IEEE Embedded Vision Workshop, June 2018, Salt Lake City, UT. [pdf]

Requirements:

  • The Cityscapes dataset: Download the "leftImg8bit" for the RGB images and the "gtFine" for the labels. Please note that for training you should use the "_labelTrainIds" and not the "_labelIds", you can download the cityscapes scripts and use the conversor to generate trainIds from labelIds
  • Python 3.6
  • PyTorch: Make sure to install the Pytorch version for Python 3.6 with CUDA support (code only tested for CUDA 9.0).
  • Additional Python packages: numpy, matplotlib, Pillow, torchvision and visdom 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

Each folder contains code for proposed models that are described in the paper. For instructions please refer to the README on each folder

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