The invention discloses a tomato
leaf disease detection method based on an SSP-DETR model, and the method is realized through the SSP-DETR model, and comprises the steps: obtaining a tomato
leaf disease image
data set, and carrying out the classification; inputting the tomato
leaf disease image into a StarNet
network module for
feature extraction, and outputting feature maps P2, P3, P4 and P5 of different dimensions; inputting P5 into an attention
feature extraction module, and outputting F5; p2, P3, P4 and F5 are input into a multi-scale fusion module for
feature fusion; inputting the fused feature map into a Decoder decoder, and outputting a tomato leaf
disease area prediction frame; acquiring a tomato leaf
disease area prediction frame and
disease area classification in the corresponding tomato leaf disease image, and performing back propagation on the optimization model by using a
loss function; and inputting the tomato leaf disease image into the optimized model to obtain a
disease detection result. According to the method, the tomato leaf diseases can be comprehensively detected, the detection precision is high, and the robustness is good.