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Prepare Datasets for DiffCut

To run the evaluation, download and set up PASCAL VOC, PASCAL Context, COCO-Stuff164k, Cityscapes, and ADE20k datasets. This data preparation document partly follows FC-CLIP instructions.

The datasets are assumed to exist in a directory with the structure described below.

$datasets/
  ADEChallengeData2016/
  coco/
  cityscapes/
  VOCdevkit/
  pascal_ctx_d2/
  pascal_voc_d2/

Expected dataset structure for COCO:

coco/
  annotations/
    {val}2017/ # png annotations
  images/
    {val}2017/ # jpg images

Download and unzip:

wget http://images.cocodataset.org/zips/val2017.zip
wget http://calvin.inf.ed.ac.uk/wp-content/uploads/data/cocostuffdataset/stuffthingmaps_trainval2017.zip

Expected dataset structure for Cityscapes:

cityscapes/
  gtFine/
    train/
      aachen/
        color.png, instanceIds.png, labelIds.png, polygons.json,
        labelTrainIds.png
      ...
    val/
    test/
  leftImg8bit/
    train/
    val/
    test/

Expected dataset structure for ADE20k (A150):

ADEChallengeData2016/
  annotations/
  images/

Download and unzip:

wget http://data.csail.mit.edu/places/ADEchallenge/ADEChallengeData2016.zip

Expected dataset structure for PASCAL Context (PC-59) and PASCAL VOC (PAS-21):

VOCdevkit/
  VOC2012/
    Annotations/
    JPEGImages/
    ImageSets/
      Segmentation/
  VOC2010/
    JPEGImages/
    trainval/
    trainval_merged.json
# generated by prepare_pascal_voc_sem_seg.py
pascal_voc_d2/
  images/
  annotations_pascal21/
  # pascal 20 excludes the background class
  annotations_pascal20/
# generated by prepare_pascal_ctx_sem_seg.py
pascal_ctx_d2/
  images/
  annotations_ctx59/

PASCAL VOC (PAS-21/PAS-20)

Download the dataset from http://host.robots.ox.ac.uk/pascal/VOC/:

cd $DETECTRON2_DATASETS
wget http://host.robots.ox.ac.uk/pascal/VOC/voc2012/VOCtrainval_11-May-2012.tar
# generate folder VOCdevkit/VOC2012
tar -xvf VOCtrainval_11-May-2012.tar

Generate directory pascal_voc_d2 running:

python datasets/prepare_pascal_voc_sem_seg.py

PASCAL Context (PC-59)

Download the dataset from http://host.robots.ox.ac.uk/pascal/VOC/ and annotation from https://www.cs.stanford.edu/~roozbeh/pascal-context/:

cd $DETECTRON2_DATASETS
wget http://host.robots.ox.ac.uk/pascal/VOC/voc2010/VOCtrainval_03-May-2010.tar
# generate folder VOCdevkit/VOC2010
tar -xvf VOCtrainval_03-May-2010.tar 
wget https://www.cs.stanford.edu/~roozbeh/pascal-context/trainval.tar.gz
# generate folder VOCdevkit/VOC2010/trainval
tar -xvzf trainval.tar.gz -C VOCdevkit/VOC2010 
wget https://codalabuser.blob.core.windows.net/public/trainval_merged.json -P VOCdevkit/VOC2010/

Install Detail API by:

git clone https://github.com/zhanghang1989/detail-api.git
rm detail-api/PythonAPI/detail/_mask.c
pip install -e detail-api/PythonAPI/

Generate directory pascal_ctx_d2/images and pascal_ctx_d2/annotations_ctx59 running:

python datasets/prepare_pascal_ctx_sem_seg.py