Rock image pore type identification method based on semantic segmentation

The invention discloses a rock image pore type identification method based on semantic segmentation. The method comprises the following steps: S1, establishing an initial deep learning network model;S2, acquiring an original rock image, and performing image cutting and image enhancement to obtain preprocessed image data; S3, acquiring an original image of the rock, and performing manual marking of pore positions and shapes to obtain marked label image data; S4, carrying out One-Hot encoding on the labeled label image data to obtain coded label data; S5, training the initial deep learning network model by taking the preprocessed image data and the encoded tag data as training samples to obtain a trained model; and S6, identifying the to-be-identified image by using the trained model. The method has the advantages that the noise resistance is high, the generalization capability is realized, the pore recognition precision can be improved, and the pore category recognition is realized. 本发明公开了一种基于语义分割的岩石图像孔隙类型识别方法