| --- |
| dataset_info: |
| features: |
| - name: image |
| dtype: image |
| - name: objects |
| struct: |
| - name: bbox |
| list: |
| list: float64 |
| - name: categories |
| list: |
| class_label: |
| names: |
| '0': '0' |
| '1': '1' |
| '2': '2' |
| '3': '3' |
| '4': '4' |
| '5': '5' |
| '6': '6' |
| '7': '7' |
| '8': '8' |
| '9': '9' |
| '10': '10' |
| '11': '11' |
| '12': '12' |
| '13': '13' |
| '14': '14' |
| splits: |
| - name: train |
| num_bytes: 2759067041 |
| num_examples: 6656 |
| download_size: 2969930573 |
| dataset_size: 2759067041 |
| 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 |
| --- |
| |
|
|
| # MH Weed16 Weed Detection |
|
|
| A dataset for weed detection in Soybean fields. The dataset contains 6,656 images with 62,052 bounding box annotations across 15 categories. |
|
|
| This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{shinde2025indian, |
| title={An Indian annotated weed dataset for computer vision tasks in precision farming}, |
| author={Shinde, Sayali and Attar, Vahida}, |
| journal={Data in Brief}, |
| volume={61}, |
| pages={111691}, |
| year={2025}, |
| publisher={Elsevier} |
| } |
| ``` |
|
|
| Shinde, Sayali; Attar, Dr. Vahida; Technological University Pune, COEP; Technology Innovation Hub, Indian Statistical Institute Kolkata, IDEAS (2025), “MH-Weed16:An Indian Multiclass Annotated Weed Dataset for Computer Vision Tasks ”, Mendeley Data, V2, doi: 10.17632/d3n3mgjjbv.2 |
