| dataset_info: | |
| features: | |
| - name: image | |
| dtype: image | |
| splits: | |
| - name: train | |
| num_bytes: 213191688 | |
| num_examples: 362 | |
| download_size: 213207032 | |
| dataset_size: 213191688 | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: train | |
| path: data/train-* | |
| license: cc-by-4.0 | |
| size_categories: | |
| - n<1K | |
| # Luffa Flowers | |
| This dataset comprises real-world RGB images of luffa flowers captured in natural agricultural field conditions in Binokdia, Faridpur, Bangladesh. Images were collected using a handheld smartphone camera during October 2023, providing unprocessed field-level visual data for computer vision analysis in crop health monitoring contexts. The dataset contains 362 images with no classification, segmentation, or bounding-box annotations. | |
| This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. | |
| ## Citation | |
| ```bibtex | |
| @article{sheikh2024luffafolio, | |
| title={LuffaFolio: A Multidimensional Image Dataset of Smooth Luffa}, | |
| author={Sheikh, Md Ripon and Islam, Md. Masudul and Himel, Galib Muhammad Shahriar}, | |
| journal={Data in Brief}, | |
| volume={53}, | |
| pages={110149}, | |
| year={2024}, | |
| publisher={Elsevier} | |
| } | |
| ``` | |
| *This dataset was reformatted from its original format to match HuggingFace standards.* | |