---
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