| --- |
| dataset_info: |
| features: |
| - name: image |
| dtype: image |
| - name: mask |
| dtype: |
| image: |
| mode: L |
| splits: |
| - name: train |
| num_bytes: 223331091 |
| num_examples: 148 |
| download_size: 223347077 |
| dataset_size: 223331091 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| task_categories: |
| - image-segmentation |
| size_categories: |
| - n<1K |
| --- |
| # Apple Flower Segmentation |
|
|
| A dataset for semantic segmentation of apple flowers. The dataset contains 148 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{8392727, |
| author={Dias, Philipe A. and Tabb, Amy and Medeiros, Henry}, |
| journal={IEEE Robotics and Automation Letters}, |
| title={Multispecies Fruit Flower Detection Using a Refined Semantic Segmentation Network}, |
| year={2018}, |
| volume={3}, |
| number={4}, |
| pages={3003-3010}, |
| doi={10.1109/LRA.2018.2849498} |
| } |
| ``` |
