Datasets:
File size: 1,637 Bytes
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dataset_info:
features:
- name: image
dtype: image
- name: mask
dtype: image
- name: objects
struct:
- name: bbox
list:
list: int64
- name: categories
list:
class_label:
names:
'0': ''
'1': large
'2': medium
'3': small
splits:
- name: train
num_bytes: 686518729
num_examples: 89
download_size: 686516546
dataset_size: 686518729
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
license: cc-by-4.0
task_categories:
- object-detection
size_categories:
- n<1K
---
# Avoair Db Annotated
This dataset provides real RGB imagery of avocado orchards captured from a DJI Phantom Pro 4 UAV in field conditions across the Kenitra/Allal Tazi region, Morocco. The images are annotated for object detection, focusing on avocado fruit size variations within agricultural monitoring applications. The dataset contains 89 images with 7,428 bounding box annotations across 3 categories.
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
## Citation
```bibtex
@article{elamraoui2022avo,
title={Avo-AirDB: An avocado UAV Database for agricultural image segmentation and classification},
author={EL Amraoui, Khalid and Lghoul, Mouataz and Ezzaki, Ayoub and Masmoudi, Lhoussaine and Hadri, Majid and Elbelrhiti, Hicham and Simo, Aziz Abdou},
journal={Data in Brief},
volume={45},
pages={108738},
year={2022},
publisher={Elsevier}
}
```
*This dataset was reformatted from its original format to match HuggingFace standards.*
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