Datasets:

Project-AgML
/

litchi_fruit_detection

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

@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.