The invention relates to the field of
crop breeding, in particular to a rice
brown spot detecting and counting method, which has the technical scheme that by improving a YOLOv8 model, introducing a C2f-EFA module, an ASFPN module, a WSIoU
loss function and a TADHead detection head and optimizing model performance, efficient and accurate rice
brown spot detecting and counting are realized, the accuracy and efficiency of
brown spot disease detecting and counting are improved, and the rice brown spot
disease detecting and counting method is suitable for large-scale popularization and application.
Technical support is provided for rice
disease analysis; wherein the C2f-EFA module enhances the feature expression ability of the disease spots and the disease leaves of the brown spot, the parameter quantity and the calculation complexity are remarkably reduced, and the method is suitable for a brown spot detection scene with
limited resources; the ASFPN module effectively improves the detection capability of the model on the brown spot disease spots and diseased leaves, and is suitable for
processing scenes with large scale difference, complex background and small disease spots; the TADHead detection head enhances the generalization ability of a brown spot detection model, enhances the detection precision of brown spot disease spots and diseased leaves, and ensures robustness under the condition of complex background or
low contrast; the WSIoU
loss function obviously improves the positioning accuracy of the disease spots and the disease leaves.