RealWheat2021

The dataset is approximately 230 GB in size, compressed into 12 volumes and stored across 6 Zenodo repositories. 

A real wheat dataset (RealWheat2021) was constructed for network development and performance evaluation. First, the original UAV images were stitched and geometrically calibrated with the 11 GCPs using the Agisoft Metashape Professional 1.5.1 software (Agisoft LLC, St. Petersburg, Russia). The orthophotos were manually adjusted to the north-south direction, and regions of interest were then clipped using the ArcMap 10.8 software (ESRI, Redlands, USA). A total of ten orthophotos belonging to six growth stages were generated. Second, the ten orthophotos were partitioned into training and testing datasets, respectively, adhering to a ratio of 7:3. Notebally, the testing datasets include three Stages for studying the robustness of proposed methods on different growth stages. Third, the ArcGIS software was employed to label each plot within the orthophotos. Fourth, each orthophoto and its label file were cropped into patches using the ArcMap software. A predefined sliding window approach was employed to extract patches from each orthophoto and its corresponding label file, with each patch having a consistent width and height of 1024 pixels, encompassing approximately four plots. The sliding step of the window was set as 0 to avoid any intersection of each patch. Fifth, the patches were rotated for data augmentation. The patches cropped from the orthophotos were defined as the initial direction (0°). Then, each patch was rotated clockwise starting from 0° to 90° with an interval of 15° (0°, 15°, 30°, 45°, 60°, 75°, 90°) using a Python package named OpenCV. The corresponding labels were processed in the same way as the patches. Finally, the RealWheat2021 dataset was constructed with 115234 images.