Datasets:
metadata
dataset_info:
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- config_name: 2_side
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configs:
- config_name: 0_all
data_files:
- split: train
path: 0_all/train-*
- split: test
path: 0_all/test-*
- config_name: 1_top
data_files:
- split: daylight
path: 1_top/daylight-*
- split: indoorlight
path: 1_top/indoorlight-*
- split: infrared
path: 1_top/infrared-*
- split: train
path: 1_top/train-*
- split: test
path: 1_top/test-*
- config_name: 2_side
data_files:
- split: daylight
path: 2_side/daylight-*
- split: indoorlight
path: 2_side/indoorlight-*
- split: infrared
path: 2_side/infrared-*
- split: train
path: 2_side/train-*
- split: test
path: 2_side/test-*
- config_name: 3_external
data_files:
- split: train
path: 3_external/train-*
- split: test
path: 3_external/test-*
- config_name: a1_t2s
data_files:
- split: train
path: a1_t2s/train-*
- split: test
path: a1_t2s/test-*
- config_name: a2_s2t
data_files:
- split: train
path: a2_s2t/train-*
- split: test
path: a2_s2t/test-*
- config_name: b_light
data_files:
- split: train
path: b_light/train-*
- split: test
path: b_light/test-*
- config_name: c_external
data_files:
- split: train
path: c_external/train-*
- split: test
path: c_external/test-*
license: mit
task_categories:
- object-detection
tags:
- biology
pretty_name: COLO
size_categories:
- 1K<n<10K
COw LOcalization (COLO) Dataset
The COw LOcalization (COLO) dataset is designed to localize cows in various indoor environments using different lighting conditions and view angles. This dataset offers 1,254 images and 11,818 cow instances, serving as a benchmark for the precision livestock farming community.
Dataset Configurations
| Configuration | Training Split | Testing Split |
|---|---|---|
| 0_all | Top-View + Side-View | Top-View + Side-View |
| 1_top | Top-View | Top-View |
| 2_side | Side-View | Side-View |
| 3_external | External | External |
| a1_t2s | Top-View | Side-View |
| a2_s2t | Side-View | Top-View |
| b_light | Daylight | Indoor + NIR |
| c_external | Top-View + Side-View | External |
Download the Dataset
To download the dataset, you need to have the required Python dependencies installed. You can install them using either of the following commands:
python -m pip install pyniche
or
pip install pyniche
Once the dependencies are installed, use the Python console to provide the download destination folder in the root parameter and specify the export data format in the format parameter:
from pyniche.data.download import COLO
# Example: Download COLO in the YOLO format
COLO(
root="download/yolo", # Destination folder
format="yolo", # Data format
)
# Example: Download COLO in the COCO format
COLO(
root="download/coco", # Destination folder
format="coco", # Data format
)
Citation
@misc{das2024model,
title={A Model Generalization Study in Localizing Indoor Cows with COw LOcalization (COLO) dataset},
author={Mautushi Das and Gonzalo Ferreira and C. P. James Chen},
year={2024},
eprint={2407.20372},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
or
Das, M., Ferreira, G., & Chen, C. P. J. (2024). A Model Generalization Study in Localizing Indoor Cows with COw LOcalization (COLO) dataset. arXiv preprint arXiv:2407.20372