def _make_info(self) -> DatasetInfo: return DatasetInfo( "mnist", categories=10, homepage="http://yann.lecun.com/exdb/mnist", valid_options=dict(split=("train", "test"), ), )
def _make_info(self) -> DatasetInfo: return DatasetInfo( "oxford-iiit-pet", type=DatasetType.IMAGE, homepage="https://www.robots.ox.ac.uk/~vgg/data/pets/", valid_options=dict(split=("trainval", "test"), ), )
def _make_info(self) -> DatasetInfo: return DatasetInfo( name="stanford-cars", homepage="https://ai.stanford.edu/~jkrause/cars/car_dataset.html", dependencies=("scipy", ), valid_options=dict(split=("test", "train"), ), )
def _make_info(self) -> DatasetInfo: return DatasetInfo( "semeion", categories=10, homepage= "https://archive.ics.uci.edu/ml/datasets/Semeion+Handwritten+Digit", )
def _make_info(self) -> DatasetInfo: return DatasetInfo( "caltech101", type=DatasetType.IMAGE, dependencies=("scipy", ), homepage="http://www.vision.caltech.edu/Image_Datasets/Caltech101", )
def _make_info(self) -> DatasetInfo: return DatasetInfo( "cifar100", type=DatasetType.RAW, homepage="https://www.cs.toronto.edu/~kriz/cifar.html", valid_options=dict(split=("train", "test"), ), )
def _make_info(self) -> DatasetInfo: return DatasetInfo( "celeba", type=DatasetType.IMAGE, homepage="https://mmlab.ie.cuhk.edu.hk/projects/CelebA.html", valid_options=dict(split=("train", "val", "test")), )
def _make_info(self) -> DatasetInfo: return DatasetInfo( "gtsrb", homepage="https://benchmark.ini.rub.de", categories=[f"{label:05d}" for label in range(43)], valid_options=dict(split=("train", "test")), )
def _make_info(self) -> DatasetInfo: return DatasetInfo( "sbd", dependencies=("scipy", ), homepage="http://home.bharathh.info/pubs/codes/SBD/download.html", valid_options=dict(split=("train", "val", "train_noval"), ), )
def _make_info(self) -> DatasetInfo: return DatasetInfo( "country211", homepage= "https://github.com/openai/CLIP/blob/main/data/country211.md", valid_options=dict(split=("train", "val", "test")), )
def _make_info(self) -> DatasetInfo: return DatasetInfo( "clevr", type=DatasetType.IMAGE, homepage="https://cs.stanford.edu/people/jcjohns/clevr/", valid_options=dict(split=("train", "val", "test")), )
def _make_info(self) -> DatasetInfo: return DatasetInfo( "fer2013", homepage="https://www.kaggle.com/c/challenges-in-representation-learning-facial-expression-recognition-challenge", categories=("angry", "disgust", "fear", "happy", "sad", "surprise", "neutral"), valid_options=dict(split=("train", "test")), )
def _make_info(self) -> DatasetInfo: return DatasetInfo( "qmnist", categories=10, homepage="https://github.com/facebookresearch/qmnist", valid_options=dict(split=("train", "test", "test10k", "test50k", "nist"), ), )
def _make_info(self) -> DatasetInfo: return DatasetInfo( "usps", homepage= "https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/multiclass.html#usps", valid_options=dict(split=("train", "test"), ), categories=10, )
def _make_info(self) -> DatasetInfo: return DatasetInfo( "pcam", homepage="https://github.com/basveeling/pcam", categories=2, valid_options=dict(split=("train", "test", "val")), dependencies=["h5py"], )
def _make_info(self) -> DatasetInfo: return DatasetInfo( "svhn", dependencies=("scipy", ), categories=10, homepage="http://ufldl.stanford.edu/housenumbers/", valid_options=dict(split=("train", "test", "extra")), )
def _make_info(self) -> DatasetInfo: return DatasetInfo( "kmnist", categories=[ "o", "ki", "su", "tsu", "na", "ha", "ma", "ya", "re", "wo" ], homepage="http://codh.rois.ac.jp/kmnist/index.html.en", valid_options=dict(split=("train", "test"), ), )
def _make_info(self) -> DatasetInfo: return DatasetInfo( "dtd", homepage="https://www.robots.ox.ac.uk/~vgg/data/dtd/", valid_options=dict( split=("train", "test", "val"), fold=tuple(str(fold) for fold in range(1, 11)), ), )
def _make_info(self) -> DatasetInfo: name = "coco" categories, super_categories = zip( *DatasetInfo.read_categories_file(BUILTIN_DIR / f"{name}.categories")) return DatasetInfo( name, dependencies=("pycocotools", ), categories=categories, homepage="https://cocodataset.org/", valid_options=dict( split=("train", "val"), year=("2017", "2014"), annotations=(*self._ANN_DECODERS.keys(), None), ), extra=dict(category_to_super_category=FrozenMapping( zip(categories, super_categories))), )
def _make_info(self) -> DatasetInfo: return DatasetInfo( "voc", type=DatasetType.IMAGE, homepage="http://host.robots.ox.ac.uk/pascal/VOC/", valid_options=dict( split=("train", "val", "test"), year=("2012", ), task=("detection", "segmentation"), ), )
def _make_info(self) -> DatasetInfo: return DatasetInfo( "cub200", homepage= "http://www.vision.caltech.edu/visipedia/CUB-200-2011.html", dependencies=("scipy", ), valid_options=dict( split=("train", "test"), year=("2011", "2010"), ), )
def _make_info(self) -> DatasetInfo: return DatasetInfo( "sbd", type=DatasetType.IMAGE, dependencies=("scipy", ), homepage="http://home.bharathh.info/pubs/codes/SBD/download.html", valid_options=dict( split=("train", "val", "train_noval"), boundaries=(True, False), segmentation=(False, True), ), )
def _make_info(self) -> DatasetInfo: name = "imagenet" categories, wnids = zip( *DatasetInfo.read_categories_file(BUILTIN_DIR / f"{name}.categories")) return DatasetInfo( name, dependencies=("scipy", ), categories=categories, homepage="https://www.image-net.org/", valid_options=dict(split=("train", "val", "test")), extra=dict( wnid_to_category=FrozenMapping(zip(wnids, categories)), category_to_wnid=FrozenMapping(zip(categories, wnids)), sizes=FrozenMapping([ (DatasetConfig(split="train"), 1_281_167), (DatasetConfig(split="val"), 50_000), (DatasetConfig(split="test"), 100_000), ]), ), )
def _make_info(self) -> DatasetInfo: return DatasetInfo( "eurosat", homepage="https://github.com/phelber/eurosat", categories=( "AnnualCrop", "Forest", "HerbaceousVegetation", "Highway", "Industrial," "Pasture", "PermanentCrop", "Residential", "River", "SeaLake", ), )
def _make_info(self) -> DatasetInfo: return DatasetInfo( "emnist", categories=list(string.digits + string.ascii_uppercase + string.ascii_lowercase), homepage="https://www.westernsydney.edu.au/icns/reproducible_research/publication_support_materials/emnist", valid_options=dict( split=("train", "test"), image_set=( "Balanced", "By_Merge", "By_Class", "Letters", "Digits", "MNIST", ), ), )
def _make_info(self) -> DatasetInfo: return DatasetInfo( "fashionmnist", categories=( "T-shirt/top", "Trouser", "Pullover", "Dress", "Coat", "Sandal", "Shirt", "Sneaker", "Bag", "Ankle boot", ), homepage="https://github.com/zalandoresearch/fashion-mnist", valid_options=dict(split=("train", "test"), ), )
def _make_info(self) -> DatasetInfo: return DatasetInfo( "cifar10", type=DatasetType.RAW, homepage="https://www.cs.toronto.edu/~kriz/cifar.html", )
def _make_info(self) -> DatasetInfo: return DatasetInfo( type(self).__name__.lower(), homepage="https://www.cs.toronto.edu/~kriz/cifar.html", valid_options=dict(split=("train", "test")), )
def info(self) -> DatasetInfo: return DatasetInfo( "caltech101", categories=HERE / "caltech101.categories", homepage="http://www.vision.caltech.edu/Image_Datasets/Caltech101", )
def _make_info(self) -> DatasetInfo: return DatasetInfo( "caltech256", type=DatasetType.IMAGE, homepage="http://www.vision.caltech.edu/Image_Datasets/Caltech256", )