| --- |
| dataset_info: |
| features: |
| - name: image |
| dtype: image |
| - name: objects |
| struct: |
| - name: bbox |
| list: |
| list: int64 |
| - name: categories |
| list: |
| class_label: |
| names: |
| '0': Wheat Head |
| splits: |
| - name: train |
| num_bytes: 3717767435 |
| num_examples: 6512 |
| download_size: 3742198889 |
| dataset_size: 3717767435 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| license: cc-by-sa-4.0 |
| task_categories: |
| - object-detection |
| size_categories: |
| - 1K<n<10K |
| --- |
| # Wheat Head Counting |
|
|
| A dataset for object detection of Wheat Head Counting. The dataset contains 6,512 images with 275,466 bounding box annotations across 1 category. |
|
|
| This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{david2020global, |
| title={Global Wheat Head Detection (GWHD) dataset: a large and diverse dataset of high-resolution RGB-labelled images to develop and benchmark wheat head detection methods},\ |
| author={David, Etienne and Madec, Simon and Sadeghi-Tehran, Pouria and Aasen, Helge and Zheng, Bangyou and Liu, Shouyang and Kirchgessner, Norbert and Ishikawa, Goro and Nagasawa, Koichi and Badhon, Minhajul A and others}, |
| journal={Plant Phenomics}, |
| volume={2020}, |
| year={2020}, |
| publisher={Science Partner Journal} |
| } |
| ``` |
