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| dataset_info: | |
| features: | |
| - name: image | |
| dtype: image | |
| - name: label | |
| dtype: | |
| class_label: | |
| names: | |
| '0': Anthracnose | |
| '1': Healthy | |
| '2': Leaf Crinckle | |
| '3': Powdery Mildew | |
| '4': Yellow Mosaic | |
| splits: | |
| - name: train | |
| num_bytes: 121482774 | |
| num_examples: 1007 | |
| download_size: 121530406 | |
| dataset_size: 121482774 | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: train | |
| path: data/train-* | |
| license: cc-by-4.0 | |
| task_categories: | |
| - image-classification | |
| size_categories: | |
| - 1K<n<10K | |
| # BPLD Leaf Disease Classification | |
| A dataset for disease classification of Blackgram leaves. The dataset contains 1,007 images across 5 classes: Anthracnose, Healthy, Leaf Crinckle, Powdery Mildew, Yellow Mosaic. | |
| Images per class: | |
| - Anthracnose: 230 | |
| - Healthy: 221 | |
| - Leaf Crinckle: 152 | |
| - Powdery Mildew: 180 | |
| - Yellow Mosaic: 224 | |
| This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. | |
| ## Citation | |
| ```bibtex | |
| @article{talasila2022black, | |
| title={Black gram Plant Leaf Disease (BPLD) dataset for recognition and classification of diseases using computer-vision algorithms}, | |
| author={Talasila, Srinivas and Rawal, Kirti and Sethi, Gaurav and Mss, Sanjay and others}, | |
| journal={Data in Brief}, | |
| volume={45}, | |
| pages={108725}, | |
| year={2022}, | |
| publisher={Elsevier} | |
| } | |
| ``` | |
| Talasila, Srinivas; Rawal, Kirti; Sethi, Gaurav; MSS, Sanjay; M, Surya Prakash Reddy (2022), “Blackgram Plant Leaf Disease Dataset”, Mendeley Data, V3, doi: 10.17632/zfcv9fmrgv.3 |