Datasets:
File size: 1,591 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': Ripe quince
'1': Unripe quince
splits:
- name: train
num_bytes: 4473166727
num_examples: 1515
download_size: 5812591565
dataset_size: 4473166727
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
---
# QuinceSet Detection
A dataset for detection of quince fruit. The dataset contains 1,515 images with 17,171 bounding box annotations across 2 categories.
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
## Citation
```bibtex
@article{kaufmane2022quinceset,
title={QuinceSet: Dataset of annotated Japanese quince images for object detection},
author={Kaufmane, Ed{\=\i}te and Sudars, Kaspars and Namat{\=e}vs, Ivars and Kalni{\c{n}}a, Ieva and Judvaitis, J{\=a}nis and Bala{\v{s}}s, Rihards and Strauti{\c{n}}a, Sarm{\=\i}te},
journal={Data in Brief},
volume={42},
pages={108332},
year={2022},
publisher={Elsevier}
}
```
Kaufmane, E., Sudars, K., Namatēvs, I., Kalniņa, I., Judvaitis, J., Balašs, R.& Strautiņa, S. (2022). QuinceSet: Dataset of Annotated Japanese Quince Images for Object Detection. Data in Brief. https://doi.org/10.5281/zenodo.6402251
*This dataset was reformatted from its original format to match HuggingFace standards.* |