Project-AgML/CCOD_cotton_flower_detection

Ccod Cotton Flower Detection

CCOD (Crop Canopy Organ-level Object Detection) is a UAV dataset of small plant organs seen from above crop canopies: cotton flowers and cotton bolls in Xinjiang, potato flowers at Keshan Farm in Heilongjiang, and rice panicles in Jiangsu, China. Images were captured at flowering or maturity from 12 m with the RGB camera of a DJI Mavic 3 Multispectral drone, cropped into 640 x 640 tiles (512 x 512 for rice), and annotated with dense bounding boxes, using a SAHI-YOLOv10n model to propose boxes that annotators then corrected. The crop_canopy column records which subset each image comes from, and the split column keeps the authors' 7:2:1 train/val/test split. The dataset contains 3,986 images with 333,300 bounding box annotations across 4 categories.

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

@article{liu2025improved,
  title={Improved Detection and Location of Small Crop Organs by Fusing UAV Orthophoto Maps and Raw Images},
  author={Liu, Huaiyang and Li, Huibin and Wang, Haozhou and Liu, Chuanghai and Qian, Jianping and Wang, Zhanbiao and Geng, Changxing},
  journal={Remote Sensing},
  volume={17},
  pages={906},
  year={2025},
  publisher={MDPI}
}

This dataset was reformatted from its original format to match HuggingFace standards.