metadata

dataset_info:
  features:
    - name: image
      dtype: image
    - name: labels
      sequence: string
  splits:
    - name: train
      num_bytes: 803214220.7904668
      num_examples: 65489
    - name: validation
      num_bytes: 266197252.78758246
      num_examples: 21830
    - name: test
      num_bytes: 268741440.4589508
      num_examples: 21842
  download_size: 1320536329
  dataset_size: 1338152914.037
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: validation
        path: data/validation-*
      - split: test
        path: data/test-*

Dataset Card for MLRS Net

MLRSNet is a multi-label high spatial resolution remote sensing dataset for semantic scene understanding. It provides different perspectives of the world captured from satellites. That is, it is composed of high spatial resolution optical satellite images. MLRSNet contains 109,161 remote sensing images that are annotated into 46 categories, and the number of sample images in a category varies from 1,500 to 3,000. The images have a fixed size of 256×256 pixels with various pixel resolutions (~10m to 0.1m). Moreover, each image in the dataset is tagged with several of 60 predefined class labels, and the number of labels associated with each image varies from 1 to 13. The dataset can be used for multi-label based image classification, multi-label based image retrieval, and image segmentation.

Dataset Sources

Repository: https://github.com/cugbrs/MLRSNet
Paper : https://www.sciencedirect.com/science/article/abs/pii/S0924271620302677

Uses

The dataset has many use cases in remote sensing applications. It is crucial to get all the tags of the image. The algorithms trained on the model make things simpler in the applications.

Direct Use

Multilabel image classification
Remote sensing applications
Deep Learning
Scene Understanding

Dataset Structure

There are three splits in total : train, validation, test

It is important to note that the entries are shuffled and there is no chance of having a bias.

Dataset Creation

Source Data

I have got the dataset from https://data.mendeley.com/datasets/7j9bv9vwsx/3

Data Processing

I have converted it into hugging face dataset via this notebook https://colab.research.google.com/drive/12ONm4rToN-DE7CkHIs86gNN6w2iKIUJG?usp=sharing

Who are the contributors?

Xiaoman Qi,Panpan Zhu,Yuebin Wang,Liqiang Zhang,Junhuan Peng,Mengfan Wu,Jialong Chen,Xudong Zhao,Ning Zang,P.Takis Mathiopoulos

Citation

Qi, Xiaoman; Zhu, Panpan; Wang, Yuebin; Zhang, Liqiang; Peng, Junhuan; Wu, Mengfan; Chen, Jialong; Zhao, Xudong; Zang, Ning; Mathiopoulos, P.Takis (2021), “MLRSNet: A Multi-label High Spatial Resolution Remote Sensing Dataset for Semantic Scene Understanding”, Mendeley Data, V3, doi: 10.17632/7j9bv9vwsx.3

Dataset Card Authors

https://huggingface.co/vigneshwar472

Dataset Card Contact

Email : vigneshwar472@gmail.com