Datasets:

Project-AgML
/

fruitseg30_segmentation

dataset_info:
  features:
    - name: image
      dtype: image
    - name: mask
      dtype: image
    - name: crop_type
      dtype: string
  splits:
    - name: train
      num_bytes: 98971137
      num_examples: 1969
  download_size: 84142287
  dataset_size: 98971137
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
license: cc-by-4.0
task_categories:
  - image-classification
  - image-segmentation
size_categories:
  - 1K<n<10K

FruitSeg30 Segmentation

A dataset for semantic segmentation of common types of fruit in a lab environment. The dataset contains 1,969 images with pixel-level mask annotations.

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

Citation

@article{shamrat2024fruitseg30_segmentation,
  title={FruitSeg30\_Segmentation dataset \& mask annotations: A novel dataset for diverse fruit segmentation and classification},
  author={Shamrat, FM Javed Mehedi and Shakil, Rashiduzzaman and Idris, Mohd Yamani Idna and Akter, Bonna and Zhou, Xujuan},
  journal={Data in Brief},
  volume={56},
  pages={110821},
  year={2024},
  publisher={Elsevier}
}

Shamrat, F M Javed Mehedi; Shakil, Rashiduzzaman ; Idris, Mohd Yamani Idna ; Akter, Bonna; Zhou, Xujuan (2024), “FruitSeg30_Segmentation Dataset & Mask Annotations”, Mendeley Data, V3, doi: 10.17632/vkht8pfsp3.3

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