- Description:
RESISC45 dataset is a publicly available benchmark for Remote Sensing Image Scene Classification (RESISC), created by Northwestern Polytechnical University (NWPU). This dataset contains 31,500 images, covering 45 scene classes with 700 images in each class.
Homepage: http://www.escience.cn/people/JunweiHan/NWPU-RESISC45.html
Source code:
tfds.image_classification.Resisc45
Versions:
3.0.0
(default): No release notes.
Download size:
Unknown size
Dataset size:
Unknown size
Manual download instructions: This dataset requires you to download the source data manually into
download_config.manual_dir
(defaults to~/tensorflow_datasets/downloads/manual/
):
Dataset can be downloaded from OneDrive: https://1drv.ms/u/s!AmgKYzARBl5ca3HNaHIlzp_IXjs After downloading the rar file, please extract it to the manual_dir.Auto-cached (documentation): Unknown
Splits:
Split | Examples |
---|---|
'train' |
31,500 |
- Features:
FeaturesDict({
'filename': Text(shape=(), dtype=tf.string),
'image': Image(shape=(256, 256, 3), dtype=tf.uint8),
'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=45),
})
Supervised keys (See
as_supervised
doc):('image', 'label')
Figure (tfds.show_examples):
- Examples (tfds.as_dataframe):
- Citation:
@article{Cheng_2017,
title={Remote Sensing Image Scene Classification: Benchmark and State of the Art},
volume={105},
ISSN={1558-2256},
url={http://dx.doi.org/10.1109/JPROC.2017.2675998},
DOI={10.1109/jproc.2017.2675998},
number={10},
journal={Proceedings of the IEEE},
publisher={Institute of Electrical and Electronics Engineers (IEEE)},
author={Cheng, Gong and Han, Junwei and Lu, Xiaoqiang},
year={2017},
month={Oct},
pages={1865-1883}
}