metadata
task_categories:
- image-segmentation
tags:
- roboflow
- roboflow2huggingface
Dataset Labels
['copiapoa', 'copiapoa-v2']
Number of Images
{'valid': 1060, 'test': 1013, 'train': 8028}
How to Use
- Install datasets:
pip install datasets
- Load the dataset:
from datasets import load_dataset
ds = load_dataset("aghent/Aerial-Semantic-Segmentation-Cactis", name="full")
example = ds['train'][0]
Roboflow Dataset Page
https://universe.roboflow.com/uai-63qde/instance-segmentation-kgvep/dataset/1
Citation
@misc{ instance-segmentation-kgvep_dataset,
title = { Instance Segmentation Dataset },
type = { Open Source Dataset },
author = { UAI },
howpublished = { \\url{ https://universe.roboflow.com/uai-63qde/instance-segmentation-kgvep } },
url = { https://universe.roboflow.com/uai-63qde/instance-segmentation-kgvep },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { nov },
note = { visited on 2023-11-04 },
}
License
CC BY 4.0
Dataset Summary
This dataset was exported via roboflow.com on November 4, 2023 at 2:50 AM GMT
Roboflow is an end-to-end computer vision platform that helps you
- collaborate with your team on computer vision projects
- collect & organize images
- understand and search unstructured image data
- annotate, and create datasets
- export, train, and deploy computer vision models
- use active learning to improve your dataset over time
For state of the art Computer Vision training notebooks you can use with this dataset, visit https://github.com/roboflow/notebooks
To find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com
The dataset includes 10101 images. Cactis are annotated in COCO format.
The following pre-processing was applied to each image:
No image augmentation techniques were applied.