Exemplar-Based Open-Set Panoptic Segmentation Network
EOPSN
PyTorch implementation for EOPSN.
We propose open-set panoptic segmentation task and propose a new baseline called EOPSN. The code is based on Detectron2
Usage
First, install requirements.
pip install -r requirements.txt
Then, install PyTorch 1.5+ and torchvision 0.6+:
conda install -c pytorch pytorch torchvision
Finally, you need to install Detectron2. To prevent version conflict, I recommand to install via included detectron2 folders. Regarding installation issue caused from detectron2, please refer to here.
cd detectron2
pip install -e ./
Data preparation
Download and extract COCO 2017 train and val images with annotations from http://cocodataset.org. We expect the directory structure to be the following:
datasets/coco
annotations/ # annotation json files
train2017/ # train images
val2017/ # val images
To convert