Industrial anomaly segmentation method, apparatus and device, and storage medium

Abstract

The invention discloses an industrial anomaly segmentation method and device, equipment and a storage medium, and relates to the field of industrial anomaly detection, and the method comprises the steps: obtaining an industrial defect data set, and carrying out the data preprocessing of an initial industrial defect image, so as to obtain a target industrial defect data set; performing fine tuning on the initial multi-modal pre-training model based on the target industrial defect data set to obtain a fine-tuned industrial multi-modal pre-training model; performing image reconstruction and foreground segmentation processing on the current industrial defect image by using the initial multi-modal pre-training model to obtain a first processed industrial defect image and a second processed industrial defect image; and inputting the first processed industrial defect image into the fine-tuned industrial multi-modal pre-training model to obtain a target reconstructed industrial defect image, and performing point multiplication on the target reconstructed industrial defect image and the second processed industrial defect image to obtain a target industrial defect image so as to complete industrial anomaly segmentation of the industrial defect image. And the industrial anomaly detection precision and the model generalization capability are improved.

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