Grading of wheat powdery mildew based on pixel point

Powdery mildew is an important factor affecting wheat yield and global food security, and precise grading of wheat powdery mildew images is an important means of computer-aided precision control. This article is based on the improved Swin Unet method for segmenting images of wheat powdery mildew and calculating the areas of wheat leaf lesions and healthy regions; By using the principle of pixel statistics to calculate the ratio of lesion area to leaf area, and utilizing the segmentation results of lesions for pixel statistics, the severity of wheat powdery mildew can be accurately evaluated. This research method can accurately segment wheat powdery mildew in complex backgrounds, providing scientific basis for automatic grading and early prevention of wheat powdery mildew in complex field environments.