Datasets:

Project-AgML
/

weedy_rice_segmentation

dataset_info:
  features:
    - name: bands
      dtype: binary
    - name: bands_shape
      list: int64
    - name: bands_dtype
      dtype: string
    - name: rgb
      dtype: image
    - name: mask
      dtype: image
    - name: split
      dtype: string
    - name: acquisition_date
      dtype: string
    - name: time
      dtype: string
    - name: latitude
      dtype: string
    - name: longitude
      dtype: string
    - name: altitude
      dtype: string
  splits:
    - name: train
      num_bytes: 3946641326
      num_examples: 734
  download_size: 3874929121
  dataset_size: 3946641326
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
license: cc-by-4.0
task_categories:
  - image-segmentation
size_categories:
  - n<1K

Weedy Rice Segmentation

A dataset for semantic segmentation of weedy rice. The dataset contains 734 images with pixel-level mask annotations.

This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.

The original train/test/val split has been preserved in the split column.

Citation

@article{nguyen2025dataset,
  title={A dataset of aligned RGB and multispectral UAV imagery for semantic segmentation of weedy rice},
  author={Nguyen, Van-Hoa and Le, Cong-Doan and Truong, Minh-Tuyen and Bui, Mai-Phung Thi and Le, Thanh-Phong},
  journal={Data in Brief},
  volume={63},
  pages={112237},
  year={2025},
  publisher={Elsevier}
}

Nguyen, Van Hoa; Le, Cong-Doan; Truong, Minh-Tuyen; Bui, Mai-Phung; Le, Thanh-Phong (2025), “A Dataset of Aligned RGB and Multispectral UAV Imagery for Semantic Segmentation of Weedy Rice”, Mendeley Data, V1, doi: 10.17632/vt4s83pxx6.1

This dataset was reformatted from its original format to match HuggingFace standards.