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1.39 kB
| dataset_info: | |
| features: | |
| - name: image | |
| dtype: image | |
| - name: mask | |
| dtype: image | |
| splits: | |
| - name: train | |
| num_bytes: 91123930 | |
| num_examples: 3348 | |
| download_size: 86330172 | |
| dataset_size: 91123930 | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: train | |
| path: data/train-* | |
| license: cc-by-4.0 | |
| task_categories: | |
| - image-segmentation | |
| size_categories: | |
| - 1K<n<10K | |
| # Greenhouse Leafy Segmentation | |
| A dataset for semantic segmentation of plants growing in a greenhouse hydroponic environment. The dataset contains 3,348 images with pixel-level mask annotations. | |
| This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. | |
| ## Citation | |
| ```bibtex | |
| @article{cardenasgallegos2025reliable, | |
| title={Reliable plant segmentation under variable greenhouse illumination conditions}, | |
| author={Cardenas-Gallegos, Jonathan S. and Severns, Paul M. and Klimeš, Pavel and N. Lacerda, Lorena and Peduzzi, Alicia and Soranz Ferrarezi, Rhuanito}, | |
| journal={Computers and Electronics in Agriculture}, | |
| volume={229}, | |
| pages={109711}, | |
| year={2025}, | |
| publisher={Elsevier} | |
| } | |
| ``` | |
| Jonathan Cárdenas. (2024). JSCG95/leafy-segmentation_CEA: Data availability release (Version V1.0.0) [Computer software]. Zenodo. https://doi.org/10.5281/zenodo.11110409 | |
| *This dataset was reformatted from its original format to match HuggingFace standards.* |