SEQ EUROSAT RGB

Classes

class datasets.seq_eurosat_rgb.MyEuroSat(root, split='train', transform=None, target_transform=None)

Bases: Dataset

static get_class_names()

class datasets.seq_eurosat_rgb.SequentialEuroSatRgb(args)

Bases: ContinualDataset

MEAN = [0.48145466, 0.4578275, 0.40821073]

NAME: str = 'seq-eurosat-rgb'

N_CLASSES: int = 10

N_CLASSES_PER_TASK: int = 2

N_TASKS: int = 5

SETTING: str = 'class-il'

SIZE: Tuple[int] = (224, 224)

STD = [0.26862954, 0.26130258, 0.27577711]

TEST_TRANSFORM = Compose(     Resize(size=224, interpolation=bicubic, max_size=None, antialias=True)     CenterCrop(size=(224, 224))     ToTensor()     Normalize(mean=[0.48145466, 0.4578275, 0.40821073], std=[0.26862954, 0.26130258, 0.27577711]) )

TRANSFORM = Compose(     RandomResizedCrop(size=(224, 224), scale=(0.08, 1.0), ratio=(0.75, 1.3333), interpolation=bicubic, antialias=True)     RandomHorizontalFlip(p=0.5)     ToTensor()     Normalize(mean=[0.48145466, 0.4578275, 0.40821073], std=[0.26862954, 0.26130258, 0.27577711]) )

get_backbone()

get_batch_size()

get_class_names()

get_data_loaders()

static get_denormalization_transform()

get_epochs()

static get_loss()

static get_normalization_transform()

static get_prompt_templates()

static get_transform()

Functions

datasets.seq_eurosat_rgb.my_collate_fn(batch)