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wgisd

Embrapa WGISD: Embrapa Wine Grape Instance Segmentation Dataset

https://github.com/dataset-ninja/wgisd

Science Score: 44.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ○
    Academic email domains
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (0.6%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

Embrapa WGISD: Embrapa Wine Grape Instance Segmentation Dataset

Basic Info
  • Host: GitHub
  • Owner: dataset-ninja
  • License: other
  • Language: Python
  • Default Branch: main
  • Size: 68.2 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created over 2 years ago · Last pushed 7 months ago
Metadata Files
Readme License Citation

README.md

Embrapa WGISD: Embrapa Wine Grape Instance Segmentation Dataset

WGISD is a dataset for instance segmentation, semantic segmentation, and object detection tasks.

Owner

  • Name: dataset-ninja
  • Login: dataset-ninja
  • Kind: organization

Citation (CITATION.md) 

If you make use of the WGISD data, please cite the following reference:

```bibtex
@dataset{thiago_santos_2019_3361736,
  author       = {Thiago Santos and
                  de Souza, Leonardo and
                  dos Santos Andreza and
                  Avila, Sandra},
  title        = {{Embrapa Wine Grape Instance Segmentation Dataset – 
                   Embrapa WGISD}},
  month        = jul,
  year         = 2019,
  note         = {{The building of the WGISD dataset was supported by 
                   the Embrapa SEG Project 01.14.09.001.05.04, Image-
                   based metrology for Precision Agriculture and
                   Phenotyping, and the CNPq PIBIC Program (grants
                   161165/2017-6 and 125044/2018-6).}},
  publisher    = {Zenodo},
  version      = {1.0.0},
  doi          = {10.5281/zenodo.3361736},
  url          = {https://doi.org/10.5281/zenodo.3361736}
}
```

[Source](https://zenodo.org/record/3361736/export/hx)

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Dependencies

requirements.txt pypi