Datasets:
File size: 1,330 Bytes
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dataset_info:
features:
- name: image
dtype: image
- name: objects
struct:
- name: bbox
list:
list: float64
- name: categories
list:
class_label:
names:
'0': green
'1': red
splits:
- name: train
num_bytes: 3522691102
num_examples: 520
download_size: 3522739307
dataset_size: 3522691102
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
license: cc-by-4.0
task_categories:
- object-detection
size_categories:
- n<1K
---
# Tomato Factory Detection
A dataset for detection of tomatoes in a plant factory setting. The dataset contains 520 images with 8,223 bounding box annotations across 2 categories.
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
## Citation
```bibtex
@article{wu2023dataset,
title={A dataset of tomato fruits images for object detection in the complex lighting environment of plant factories},
author={Wu, Zhen-wei and Liu, Ming-hao and Sun, Cheng-xiu and Wang, Xin-fa},
journal={Data in Brief},
volume={48},
pages={109291},
year={2023},
publisher={Elsevier}
}
```
Wu, Zhenwei; Wang, Xinfa; Liu, Minghao; Sun, Chengxiu (2026), “TomatoPlantfactoryDataset”, Mendeley Data, V3, doi: 10.17632/8h3s6jkyff.3 |