Datasets:
File size: 1,796 Bytes
a4a6fb1 e02487f a4a6fb1 e02487f 24eaf29 e02487f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 | ---
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: 61971353
num_examples: 481
download_size: 61982604
dataset_size: 61971353
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
license: cc-by-4.0
task_categories:
- object-detection
size_categories:
- n<1K
---
# Apple Fruitlet Detection
This dataset provides real LiDAR point cloud imagery of cocoa fruitlets in a field environment within Cameroon's agroforestry systems. Captured using a ground-based Leica ScanStation C10 during August 2019, the 3D data offers detailed structural representations for object detection and crop monitoring applications. The dataset contains 481 images with 3,892 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{peynaud2024terrestrial,
title={Terrestrial LiDAR point cloud dataset of cocoa trees grown in agroforestry systems in Cameroon},
author={Peynaud, Emilie and Momo Takoudjou, Stéphane},
journal={Data in Brief},
volume={53},
pages={110108},
year={2024},
publisher={Elsevier}
}
```
Checola, G., Moser, D., Sonego, P., Iob, C., Micheli, F., & Franceschi, P. (2025). Fruitlet image dataset for apple phenotyping during early development [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.14844598
*This dataset was reformatted from its original format to match HuggingFace standards.*
|