---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: objects
    struct:
    - name: bbox
      list:
        list: float64
    - name: categories
      list:
        class_label:
          names:
            '0': '0'
  - name: split
    dtype: string
  splits:
  - name: train
    num_bytes: 1162832609
    num_examples: 1880
  download_size: 1115800954
  dataset_size: 1162832609
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
license: cc-by-4.0
task_categories:
- object-detection
size_categories:
- 1K<n<10K
---
# Litchi Fruit Detection

A dataset for object detection of litchi fruit. The dataset contains 1,880 images with 39,415 bounding box annotations across 1 category.

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

The original train/test/val split has been preserved in the `split` column.

## Citation

```bibtex
@article{peng2026litchi,
  title={Litchi-SORT: Overcoming occlusion and motion instability for accurate low-altitude UAV-based litchi tracking and counting},
  author={Peng, Hongxing and Chen, Lide and Xie, Haopei and Liu, Huanai and Li, Ximing},
  journal={Smart Agricultural Technology},
  volume={14},
  pages={102159},
  year={2026},
  publisher={Elsevier}
}
```
Li, W. (2026). Litchi-UAV: A UAV-based Litchi Fruit Detection Dataset for Precision Agriculture [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.19364014

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