| --- |
| 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 |
| 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: 121519312 |
| num_examples: 1007 |
| download_size: 121530545 |
| dataset_size: 121519312 |
| --- |
| |
| # Blackgram Plant 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 |
