SEQ RESISC45#
Classes#
- class datasets.seq_resisc45.Resisc45(root, train=True, transform=None, target_transform=None, download=False)[source]#
Bases:
Dataset- LABELS = ['airplane', 'airport', 'baseball_diamond', 'basketball_court', 'beach', 'bridge', 'chaparral', 'church', 'circular_farmland', 'cloud', 'commercial_area', 'dense_residential', 'desert', 'forest', 'freeway', 'golf_course', 'ground_track_field', 'harbor', 'industrial_area', 'intersection', 'island', 'lake', 'meadow', 'medium_residential', 'mobile_home_park', 'mountain', 'overpass', 'palace', 'parking_lot', 'railway', 'railway_station', 'rectangular_farmland', 'river', 'roundabout', 'runway', 'sea_ice', 'ship', 'snowberg', 'sparse_residential', 'stadium', 'storage_tank', 'tennis_court', 'terrace', 'thermal_power_station', 'wetland']#
- N_CLASSES = 45#
- class datasets.seq_resisc45.SequentialResisc45(args)[source]#
Bases:
ContinualDataset- MEAN = [0.485, 0.456, 0.406]#
- STD = [0.229, 0.224, 0.225]#
- TEST_TRANSFORM = Compose( Resize(size=(256, 256), interpolation=bicubic, max_size=None, antialias=True) CenterCrop(size=(224, 224)) ToTensor() Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) )#
- 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=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) )#