How to install datasets
June 17, 2024 · View on GitHub
We suggest putting all datasets under the same folder (say $DATA) to ease management and following the instructions below to organize datasets to avoid modifying the source code. The file structure looks like
$DATA/
|–– imagenet/
|–– caltech-101/
|–– oxford_pets/
|–– stanford_cars/
If you have some datasets already installed somewhere else, you can create symbolic links in $DATA/dataset_name that point to the original data to avoid duplicate download.
Datasets list:
The instructions to prepare each dataset are detailed below. To ensure reproducibility and fair comparison for future work, we provide fixed train/val/test splits for all datasets except ImageNet where the validation set is used as test set. The fixed splits are either from the original datasets (if available) or created by us.
Caltech101
- Create a folder named
caltech-101/under$DATA. - Download
101_ObjectCategories.tar.gzfrom http://www.vision.caltech.edu/Image_Datasets/Caltech101/101_ObjectCategories.tar.gz and extract the file under$DATA/caltech-101. - Download
split_zhou_Caltech101.jsonfrom this link and put it under$DATA/caltech-101.
The directory structure should look like
caltech-101/
|–– 101_ObjectCategories/
|–– split_zhou_Caltech101.json
OxfordPets
- Create a folder named
oxford_pets/under$DATA. - Download the images from https://www.robots.ox.ac.uk/~vgg/data/pets/data/images.tar.gz.
- Download the annotations from https://www.robots.ox.ac.uk/~vgg/data/pets/data/annotations.tar.gz.
- Download
split_zhou_OxfordPets.jsonfrom this link.
The directory structure should look like
oxford_pets/
|–– images/
|–– annotations/
|–– split_zhou_OxfordPets.json
StanfordCars
- Create a folder named
stanford_cars/under$DATA. - Download the train images http://ai.stanford.edu/~jkrause/car196/cars_train.tgz.
- Download the test images http://ai.stanford.edu/~jkrause/car196/cars_test.tgz.
- Download the train labels https://ai.stanford.edu/~jkrause/cars/car_devkit.tgz.
- Download the test labels http://ai.stanford.edu/~jkrause/car196/cars_test_annos_withlabels.mat.
- Download
split_zhou_StanfordCars.jsonfrom this link.
The directory structure should look like
stanford_cars/
|–– cars_test\
|–– cars_test_annos_withlabels.mat
|–– cars_train\
|–– devkit\
|–– split_zhou_StanfordCars.json
Flowers102
- Create a folder named
oxford_flowers/under$DATA. - Download the images and labels from https://www.robots.ox.ac.uk/~vgg/data/flowers/102/102flowers.tgz and https://www.robots.ox.ac.uk/~vgg/data/flowers/102/imagelabels.mat respectively.
- Download
cat_to_name.jsonfrom here. - Download
split_zhou_OxfordFlowers.jsonfrom here.
The directory structure should look like
oxford_flowers/
|–– cat_to_name.json
|–– imagelabels.mat
|–– jpg/
|–– split_zhou_OxfordFlowers.json
FGVCAircraft
- Download the data from https://www.robots.ox.ac.uk/~vgg/data/fgvc-aircraft/archives/fgvc-aircraft-2013b.tar.gz.
- Extract
fgvc-aircraft-2013b.tar.gzand keep onlydata/. - Move
data/to$DATAand rename the folder tofgvc_aircraft/.
The directory structure should look like
fgvc_aircraft/
|–– images/
|–– ... # a bunch of .txt files
DTD
- Download the dataset from https://www.robots.ox.ac.uk/~vgg/data/dtd/download/dtd-r1.0.1.tar.gz and extract it to
$DATA. This should lead to$DATA/dtd/. - Download
split_zhou_DescribableTextures.jsonfrom this link.
The directory structure should look like
dtd/
|–– images/
|–– imdb/
|–– labels/
|–– split_zhou_DescribableTextures.json
EuroSAT
- Create a folder named
eurosat/under$DATA. - Download the dataset from http://madm.dfki.de/files/sentinel/EuroSAT.zip and extract it to
$DATA/eurosat/. - Download
split_zhou_EuroSAT.jsonfrom here.
The directory structure should look like
eurosat/
|–– 2750/
|–– split_zhou_EuroSAT.json