Datasets:
File size: 1,546 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': '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.* |