Detectron2 has builtin support for a few datasets.
The datasets are assumed to exist in a directory specified by the environment variable
DETECTRON2_DATASETS
.
Under this directory, detectron2 will look for datasets in the structure described below, if needed.
$DETECTRON2_DATASETS/
coco/
lvis/
cityscapes/
VOC20{07,12}/
You can set the location for builtin datasets by export DETECTRON2_DATASETS=/path/to/datasets
.
If left unset, the default is ./datasets
relative to your current working directory.
The model zoo
contains configs and models that use these builtin datasets.
coco/
annotations/
instances_{train,val}2017.json
person_keypoints_{train,val}2017.json
{train,val}2017/
# image files that are mentioned in the corresponding json
You can use the 2014 version of the dataset as well.
Some of the builtin tests (dev/run_*_tests.sh
) uses a tiny version of the COCO dataset,
which you can download with ./prepare_for_tests.sh
.
coco/
annotations/
panoptic_{train,val}2017.json
panoptic_{train,val}2017/ # png annotations
panoptic_stuff_{train,val}2017/ # generated by the script mentioned below
Install panopticapi by:
pip install git+https://github.com/cocodataset/panopticapi.git
Then, run python prepare_panoptic_fpn.py
, to extract semantic annotations from panoptic annotations.
coco/
{train,val,test}2017/
lvis/
lvis_v0.5_{train,val}.json
lvis_v0.5_image_info_test.json
Install lvis-api by:
pip install git+https://github.com/lvis-dataset/lvis-api.git
Run python prepare_cocofied_lvis.py
to prepare "cocofied" LVIS annotations, which can be used to evaluate models trained on the COCO dataset.
cityscapes/
gtFine/
train/
aachen/
color.png, instanceIds.png, labelIds.png, polygons.json,
labelTrainIds.png
...
val/
test/
leftImg8bit/
train/
val/
test/
Install cityscapes scripts by:
pip install git+https://github.com/mcordts/cityscapesScripts.git
Note: to create labelTrainIds.png, first prepare the above structure, then run cityscapesescript with:
CITYSCAPES_DATASET=/path/to/abovementioned/cityscapes python cityscapesscripts/preparation/createTrainIdLabelImgs.py
These files are not needed for instance segmentation.
VOC20{07,12}/
Annotations/
ImageSets/
Main/
trainval.txt
test.txt
# train.txt or val.txt, if you use these splits
JPEGImages/
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