The present application relates to pipeline
nondestructive testing image recognition technical field, specifically to pipeline internal defect intelligent detection method based on image recognition, including: through endoscopic equipment gathers pipeline internal surface annular scanning
image sequence, obtains the feature map set containing potential defect area through image preprocessing and multilevel
feature extraction;Defect candidate region is generated by using improved attention guide network to complete
feature fusion and defect candidate region focusing
processing, and the weighted feature expression of the candidate region is generated;Through defect morphology analysis and classification discrimination, output defect category
label and morphology parameter, and generate comprehensive defect evaluation report combined with pipeline structure information.The method is suitable for pipeline annular structure to realize global continuous acquisition, eliminate detection blind area, strengthen defect features through attention weighting, suppress redundant background interference, improve defect positioning accuracy and classification accuracy, and guarantee the integrity, accuracy and reliability of pipeline internal defect detection.