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dataset_info:
  features:
    - name: image
      dtype: image
    - name: label
      dtype:
        class_label:
          names:
            '0': airplane
            '1': airport
            '2': baseball diamond
            '3': basketball court
            '4': beach
            '5': bridge
            '6': chaparral
            '7': church
            '8': circular farmland
            '9': cloud
            '10': commercial area
            '11': dense residential
            '12': desert
            '13': forest
            '14': freeway
            '15': golf course
            '16': ground track field
            '17': harbor
            '18': industrial area
            '19': intersection
            '20': island
            '21': lake
            '22': meadow
            '23': medium residential
            '24': mobile home park
            '25': mountain
            '26': overpass
            '27': palace
            '28': parking lot
            '29': railway
            '30': railway station
            '31': rectangular farmland
            '32': river
            '33': roundabout
            '34': runway
            '35': sea ice
            '36': ship
            '37': snowberg
            '38': sparse residential
            '39': stadium
            '40': storage tank
            '41': tennis court
            '42': terrace
            '43': thermal power station
            '44': wetland
  splits:
    - name: train
      num_bytes: 2383019
      num_examples: 18900
    - name: test
      num_bytes: 781557
      num_examples: 6300
    - name: contrast
      num_bytes: 831957
      num_examples: 6300
    - name: gaussian_noise
      num_bytes: 907557
      num_examples: 6300
    - name: impulse_noise
      num_bytes: 894957
      num_examples: 6300
    - name: jpeg_compression
      num_bytes: 932757
      num_examples: 6300
    - name: motion_blur
      num_bytes: 869757
      num_examples: 6300
    - name: pixelate
      num_bytes: 831957
      num_examples: 6300
    - name: spatter
      num_bytes: 819357
      num_examples: 6300
  download_size: 916981012
  dataset_size: 9252875

RESISC45

Overview

Usage

from datasets import load_dataset

# Load the dataset
dataset = load_dataset('tanganke/resisc45')

Dataset Information

The dataset is divided into the following splits:

  • Training set: Contains 18,900 examples, used for model training.
  • Test set: Contains 6,300 examples, used for model evaluation and benchmarking.

The dataset also includes the following augmented sets, which can be used for testing the model's robustness to various types of image corruptions:

  • Contrast-enhanced set: Contains 6,300 examples with enhanced contrast for improved feature visibility.
  • Gaussian noise set: Contains 6,300 examples where images have been corrupted with Gaussian noise.
  • Impulse noise set: Contains 6,300 examples with impulse noise.
  • JPEG compression set: Contains 6,300 examples where images have been compressed using JPEG encoding.
  • Motion blur set: Contains 6,300 examples with motion blur applied.
  • Pixelate set: Contains 6,300 examples where images have been pixelated.
  • Spatter set: Contains 6,300 examples with spatter noise.