The dataset contains data from three vineyards of central Portugal: Esac (at Coimbra), Valdoeiro and Quinta de Baixo. The data was acquired with a UAS that had a multispectral sensor and a high-definition camera onboard. The acquired images were used to build orthomosaics and digital surface models (DSM) from the respective plots.
The dataset comprises:
- Mulstispectral (MS) orthomosaics (R,G,B,RE,NIR, and Thermal)
- High-definition (HD) orthomosaics (R,G,D)
- Digital Surface Models (DSM)
Figure 1: Outline of the three vineyards:
| RGB-HS | DSM | RGB-MS | False-Color RE-R-G | |
|---|---|---|---|---|
| ESAC | b | c | d | e |
| Valdoeiro | f | g | h | i |
| Quinta de Baixo | j | l | m | n |
For the three vineyards, ground truth masks (pixel-level labels) were generated. The masks include only one class, which identifies vines. However, only the Esac vineyard was completely labeled; the other two orthomosaics were only partially labeled.
Link :
Orthomosaics
│
├── esac
│ │
│ ├──altum
│ │ ├── ortho.tif
│ │ └── mask.tif
│ │
│ ├── x7
│ │ ├── ortho.tif
│ │ └── mask.tif
│ │
│ └── dsm.tif
│
│
├── valdoeiro
│ │
│ ├──altum
│ │ ├── ortho.tif
│ │ └── mask.tif
│ ├── x7
│ │ ├── ortho.tif
│ │ └── (not available)
│ │
│ └── dsm.tif
│
│
└── qtabaixo
│
├──altum
│ ├── ortho.tif
│ └── mask.tif
│
├── x7
│ ├── ortho.tif
│ └── (not available)
│
└── dsm.tif
Laptop: CUDA Version: 11.3
python 3.7
To run the pipeline proposed in paper.
run:
orthosegmentation.py
Please send an e-mail to [email protected]
If you use our framework, model, or predictions for any academic work, please cite the original paper.
@article{BARROS2022106782,
title = {Multispectral vineyard segmentation: A deep learning comparison study},
journal = {Computers and Electronics in Agriculture},
volume = {195},
pages = {106782},
year = {2022},
issn = {0168-1699},
doi = {https://doi.org/10.1016/j.compag.2022.106782},
url = {https://www.sciencedirect.com/science/article/pii/S0168169922000990},
author = {T. Barros and P. Conde and G. Gonçalves and C. Premebida and M. Monteiro and C.S.S. Ferreira and U.J. Nunes},
}
Copyright (c) 2021 Tiago Barros, Pedro Conde, Gil Gonçalves, Cristiano Premebida, Miguel Monteiro, Carla S.S. Ferreira, Urbano J. Nunes.
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