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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
```bibtex
@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.* |