aghent/Aerial-Semantic-Segmentation-Cactis

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.