Datasets:
File size: 1,673 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': tree
'1': flower
'2': premature
'3': unripe
'4': ripe
'5': spoiled
splits:
- name: train
num_bytes: 436051831
num_examples: 3098
download_size: 447273427
dataset_size: 436051831
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
---
# Cashew Detection
A dataset for object detection of cashew flowers and fruits. The dataset contains 3,098 images with 88,364 bounding box annotations across 6 categories.
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
## Citation
```bibtex
@article{sanya2024coffee,
title={Coffee and cashew nut dataset: A dataset for detection, classification, and yield estimation for machine learning applications},
author={Sanya, Rahman and Nabiryo, Ann Lisa and Tusubira, Jeremy Francis and Murindanyi, Sudi and Katumba, Andrew and Nakatumba-Nabende, Joyce},
journal={Data in Brief},
volume={52},
pages={109952},
year={2024},
publisher={Elsevier}
}
```
Nakatumba-Nabende, Joyce; Katumba, Andrew; Sanya, Rahman; Tusubira, Jeremy; Murindanyi, Sudi; Namanya, Gloria; Nabiryo, Ann (2023), “Coffee and Cashew Nut Dataset”, Mendeley Data, V1, doi: 10.17632/r46c6bpfpf.1
*This dataset was reformatted from its original format to match HuggingFace standards.* |