| --- |
| dataset_info: |
| features: |
| - name: image |
| dtype: image |
| - name: objects |
| struct: |
| - name: bbox |
| list: |
| list: float64 |
| - name: categories |
| list: |
| class_label: |
| names: |
| '0': Ripe quince |
| '1': Unripe quince |
| splits: |
| - name: train |
| num_bytes: 4473166727 |
| num_examples: 1515 |
| download_size: 5812591565 |
| dataset_size: 4473166727 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| license: cc-by-4.0 |
| task_categories: |
| - object-detection |
| size_categories: |
| - 1K<n<10K |
| --- |
| # QuinceSet Detection |
|
|
| A dataset for detection of quince fruit. The dataset contains 1,515 images with 17,171 bounding box annotations across 2 categories. |
|
|
| This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{kaufmane2022quinceset, |
| title={QuinceSet: Dataset of annotated Japanese quince images for object detection}, |
| author={Kaufmane, Ed{\=\i}te and Sudars, Kaspars and Namat{\=e}vs, Ivars and Kalni{\c{n}}a, Ieva and Judvaitis, J{\=a}nis and Bala{\v{s}}s, Rihards and Strauti{\c{n}}a, Sarm{\=\i}te}, |
| journal={Data in Brief}, |
| volume={42}, |
| pages={108332}, |
| year={2022}, |
| publisher={Elsevier} |
| } |
| ``` |
|
|
| Kaufmane, E., Sudars, K., Namatēvs, I., Kalniņa, I., Judvaitis, J., Balašs, R.& Strautiņa, S. (2022). QuinceSet: Dataset of Annotated Japanese Quince Images for Object Detection. Data in Brief. https://doi.org/10.5281/zenodo.6402251 |
|
|
| *This dataset was reformatted from its original format to match HuggingFace standards.* |
