# Setup Builtin Datasets 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 expects to find datasets in the structure described below. 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](https://github.com/facebookresearch/detectron2/blob/master/MODEL_ZOO.md) contains configs and models that use these builtin datasets. ## Expected dataset structure for COCO instance/keypoint detection: ``` 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`. ## Expected dataset structure for PanopticFPN: ``` 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. ## Expected dataset structure for LVIS instance segmentation: ``` 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 for evaluation of models trained on the COCO dataset. ## 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/ ``` Install cityscapes scripts by: ``` pip install git+https://github.com/mcordts/cityscapesScripts.git ``` Note: labelTrainIds.png are created using cityscapesescript with: ``` CITYSCAPES_DATASET=$DETECTRON2_DATASETS/cityscapes python cityscapesscripts/preparation/createTrainIdLabelImgs.py ``` They are not needed for instance segmentation. ## Expected dataset structure for Pascal VOC: ``` VOC20{07,12}/ Annotations/ ImageSets/ Main/ trainval.txt test.txt # train.txt or val.txt, if you use these splits JPEGImages/ ```