RESISC Dataset

Dataset details

Last updated: 15 Dec 2022
Meta Album ID REM_SEN.RESISC
Domain ID REM_SEN
Domain Name Remote Sensing
Set Number 0
Dataset ID RESISC
Dataset Name RESISC
Short Description Remote sensing dataset
Long Description RESISC45 dataset(https://gcheng-nwpu.github.io/) gathers 700 RGB images of size 256x256 px for each of 45 scene categories. The data authors strive to provide a challenging dataset by increasing both within-class diversity and between-class similarity, as well as integrating many image variations. Even though RESISC45 does not propose a label hierarchy, it can be created from other common aerial image label organization scheme. We have preprocessed RESISC for Meta-Album by resizing the dataset to 128x128 px.
# Classes 45
# Images 31500
Keywords remote sensing, satellite image, aerial image, land cover
Data Format images
Image size 128x128
License
(original data release)		 CC-BY-NC 4.0
License URL
(original data release)		 https://creativecommons.org/licenses/by-nc/4.0/
License
(Meta-Album data release)		 CC-BY-NC 4.0
License URL
(Meta-Album data release)		 https://creativecommons.org/licenses/by-nc/4.0/
Source NWPU-RESISC45 Dataset
Source URL https://gcheng-nwpu.github.io/
Original Author Gong Cheng, Junwei Han, and Xiaoqiang Lu
Original contact chenggong1119@gmail.com
Meta Album author Phan Anh VU
Created Date 01 March 2022
Contact Name Ihsan Ullah
Contact Email meta-album@chalearn.org
Contact URL https://meta-album.github.io/

Download Meta-data files

Dataset Info Datasheet

Download Dataset from OpenML

Dataset Version OpenML ID
Micro 44246 Download
Mini 44290 Download
Extended 44324 Download

Code to download dataset using OpenML API

      # import openml
      import openml
  
      # download dataset with DATASET_ID. DATASET_ID is OpenML ID
      dataset = openml.datasets.get_dataset(DATASET_ID)
  
      # display dataset info
      print(dataset.name)

Sample Images

Cite this dataset 

@article{DBLP:journals/corr/ChengHL17,
  author    = {Gong Cheng and Junwei Han and Xiaoqiang Lu},
  title     = {Remote Sensing Image Scene Classification: Benchmark and State of the Art},
  journal   = {CoRR},
  volume    = {abs/1703.00121},
  year      = {2017},
  url       = {http://arxiv.org/abs/1703.00121},
  eprinttype = {arXiv},
  eprint    = {1703.00121},
  timestamp = {Mon, 02 Dec 2019 09:32:19 +0100},
  biburl    = {https://dblp.org/rec/journals/corr/ChengHL17.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}
Download as bib

Cite Meta-Album

  @inproceedings{meta-album-2022,
    title={Meta-Album: Multi-domain Meta-Dataset for Few-Shot Image Classification},
    author={Ullah, Ihsan and Carrion, Dustin and Escalera, Sergio and Guyon, Isabelle M and Huisman, Mike and Mohr, Felix and van Rijn, Jan N and Sun, Haozhe and Vanschoren, Joaquin and Vu, Phan Anh},
    booktitle={Thirty-sixth Conference on Neural Information Processing Systems Datasets and Benchmarks Track},
    url = {https://meta-album.github.io/},
    year = {2022}
  }
Download as bib