Datasets:
Tasks:
Image Classification
Modalities:
Image
Formats:
imagefolder
Languages:
English
Size:
1K - 10K
License:
Update dataset description
Browse files
README.md
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The dataset is a foliage image dataset generated using a tool called [Foliagen](https://github.com/nabinpakka/FoliageGenerator).
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The generation process utilizes single leaf image datasets, namely, [ASDID](https://datadryad.org/dataset/doi:10.5061/dryad.41ns1rnj3),
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[PlantVillage](https://github.com/spMohanty/PlantVillage-Dataset), and [Soybean Leaf Disease Dataset](https://www.kaggle.com/datasets/sivm205/soybean-diseased-leaf-dataset).
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## License
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This dataset is released under the [Academic Free License v3.0 (AFL-3.0)](https://opensource.org/licenses/AFL-3.0) which is compatible with the license of the datasets it uses
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The dataset is a foliage image dataset generated using a tool called [Foliagen](https://github.com/nabinpakka/FoliageGenerator).
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The generation process utilizes single leaf image datasets, namely, [ASDID](https://datadryad.org/dataset/doi:10.5061/dryad.41ns1rnj3),
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[PlantVillage](https://github.com/spMohanty/PlantVillage-Dataset), and [Soybean Leaf Disease Dataset](https://www.kaggle.com/datasets/sivm205/soybean-diseased-leaf-dataset).
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A generated foliage image dataset can be arbitrarily sized, with each of its image having a specified rate of diseased
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leaves (denoted by γ) and the rest being healthy ones. Being annotated by design, such generated datasets are valuable for (1) evaluating the SOTA classifiers when
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applied to practical use and (2) pre-training general SOTA classifiers, making it possible to fine-tune them using any real-world foliage image dataset for improved
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classification performance.
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## License
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This dataset is released under the [Academic Free License v3.0 (AFL-3.0)](https://opensource.org/licenses/AFL-3.0) which is compatible with the license of the datasets it uses
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