| --- |
| 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 |
