| --- |
| dataset_info: |
| features: |
| - name: image |
| dtype: image |
| - name: mask |
| dtype: image |
| splits: |
| - name: train |
| num_bytes: 29891139 |
| num_examples: 258 |
| download_size: 29915145 |
| dataset_size: 29891139 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| task_categories: |
| - image-segmentation |
| size_categories: |
| - n<1K |
| --- |
| |
| # Red Grapes And Leaves Segmentation |
|
|
| A dataset for semantic segmentation of Red Grapes And Leaves Segmentation. The dataset contains 258 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 |
| @inproceedings{kalampokas2020semantic, |
| title={Semantic segmentation of vineyard images using convolutional neural networks}, |
| author={Kalampokas, Theofanis and Tziridis, Konstantinos and Nikolaou, Alexandros and Vrochidou, Eleni and Papakostas, George A and Pachidis, Theodore and Kaburlasos, Vassilis G}, |
| booktitle={International Conference on Engineering Applications of Neural Networks}, |
| pages={292--303}, |
| year={2020}, |
| organization={Springer} |
| } |
| ``` |
