Please create a config file called semantic_segmentation.cfg
that specifies the paths
to the datasets. Note that they are optional; you don't need to download and provide all datasets,
only the ones you intend to use. Replace the paths below with something that works for you:
[paths]
camvid=/datasets/camvid/CamVidData.zip
cityscapes=/datasets/cityscapes\cityscapes_segmentation.zip
isic2017=/datasets/isic2017/isic2017_segmentation_248x248.zip
pascal_voc=/datasets/pascal_voc2012/VOCdevkit/VOC2012
Note that the CamVid, Cityscapes and ISIC 2017 datasets must be converted to a ZIP-based format prior to use. You must run the provided conversion utilities to create these ZIP files.
- Download the Pascal VOC 2012 dataset (use the 'training/validation data' link).
- You will also want the augmented labels (download here) so you can use the augmented Pascal dataset (used in Mittal et al. and Hung et al.)
- Decompress the main main dataset file
VOCtrainval_11-May-2012.tar
- Unzip
SegmentationClassAug.zip
within theVOCdevkit/VOC2012
directory that was created by unpacking the main dataset. - Edit the
semantic_segmentation.cfg
configuration file and provide a path for thepascal_voc
setting. - Now run:
python download_pascal_aug_names.py
to download some index files
The specific split used in Mittal et al. can be found
in data/splits/pascal_aug/split_0.pkl
. This file was taken
as-is
from their repo.
- Sign up for a cityscapes account at https://www.cityscapes-dataset.com/
- Download the input images file
leftImg8bit_trainvaltest.zip
- Download the ground truth file
gtFine_trainvaltest.zip
. - Edit the
semantic_segmentation.cfg
configuration file and point thecityscapes
to a place where you want the converted Cityscapes ZIP to live - Run:
python convert_cityscapes.py /path/to/leftImg8bit_trainvaltest.zip /path/to/gtFine_trainvaltest.zip
The conversion process will downsample all images by a factor of 2 as in Mittal et al. and Hung et al..
- Download the ISIC 2017 zip files:
ISIC-2017_Training_Data.zip
,ISIC-2017_Training_Part1_GroundTruth.zip
,ISIC-2017_Validation_Data.zip
andISIC-2017_Validation_Part1_GroundTruth.zip
to a directory called e.g./path/to/isic_zips_directory
. - Run:
python convert_isic.py /path/to/isic_zips_directory
The conversion process will scale all images to a default size of 248x248
.
(Use the --out_size=<height>,<width>
when running convert_isic
to change this).