Global Wheat 2021 Object Detection Dataset and Pre-Trained Model by Institute of Agricultural Sciences

Images

6511 images

Explore Dataset

Global wheat head detection Dataset is the first large-scale dataset for wheat head detection from field optical images. It included a very large range of cultivars from differents continents. Wheat is a staple crop grown all over the world and consequently interest in wheat phenotyping spans the globe. Therefore, it is important that models developed for wheat phenotyping, such as wheat head detection networks, generalize between different growing environments around the world.

From this first experience, a few avenues for improvements have been identified regarding data size, head diversity, and label reliability. To address these issues, the 2020 dataset has been reexamined, relabeled, and complemented by adding 1722 images from 5 additional countries, allowing for 81,553 additional wheat heads. This is the official version of the Global Wheat Head Dataset presented in David et al. (2021).Labels are included in csv. The dataset is composed of more than 6000 images of 1024x1024 pixels containing 300k+ unique wheat heads, with the corresponding bounding boxes.

For more info, visit https://www.global-wheat.com/gwhd.html

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite This Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{
                            global-wheat-2021_dataset,
                            title = { Global Wheat 2021 Dataset },
                            type = { Open Source Dataset },
                            author = { Institute of Agricultural Sciences },
                            howpublished = { \url{ https://universe.roboflow.com/institute-of-agricultural-sciences/global-wheat-2021 } },
                            url = { https://universe.roboflow.com/institute-of-agricultural-sciences/global-wheat-2021 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2024 },
                            month = { may },
                            note = { visited on 2024-06-15 },
                            }