Datasets:
| dataset_info: | |
| features: | |
| - name: image | |
| dtype: image | |
| - name: objects | |
| struct: | |
| - name: bbox | |
| list: | |
| list: float64 | |
| - name: categories | |
| list: | |
| class_label: | |
| names: | |
| '0': class0 | |
| - name: split | |
| dtype: string | |
| splits: | |
| - name: train | |
| num_bytes: 1224391 | |
| num_examples: 40 | |
| download_size: 1225894 | |
| dataset_size: 1224391 | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: train | |
| path: data/train-* | |
| license: cc-by-4.0 | |
| task_categories: | |
| - object-detection | |
| size_categories: | |
| - n<1K | |
| # Cottonsim Detection | |
| This dataset provides synthetic images of cotton plants in agricultural settings for object detection in crop monitoring. Captured using RealSense RGB-D cameras on a ground-based platform, the imagery simulates field conditions to support vision-guided agricultural robotics development. The dataset contains 40 images with 1,093 bounding box annotations across 1 category. | |
| This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. | |
| The original train/test/val split has been preserved in the `split` column. | |
| ## Citation | |
| ```bibtex | |
| @article{thayananthan2025cottonsim, | |
| title={CottonSim: A vision-guided autonomous robotic system for cotton harvesting in Gazebo simulation}, | |
| author={Thayananthan, Thevathayarajh and Zhang, Xin and Huang, Yanbo and Chen, Jingdao and Wijewardane, Nuwan K. and Martins, Vitor S. and Chesser, Gary D. and Goodin, Christopher T.}, | |
| journal={Computers and Electronics in Agriculture}, | |
| volume={239}, | |
| pages={110963}, | |
| year={2025}, | |
| publisher={Elsevier} | |
| } | |
| ``` | |
| *This dataset was reformatted from its original format to match HuggingFace standards.* | |