Aiming at the problem that the detection effect of multi- directional arrangement text is still not ideal due to its large scale change and complex background interference,this paper proposes a multi-directional text detection method based on attention mechanism. Firstly,considering that there is a lot of interference information in natural scenes,a text feature extraction network is constructed to extract the text feature information in the image;Secondly,a text attention module (TAM) is added to the feature fusion model to suppress irrelevant information while highlighting textual information to enhance potential connections between text features;Finally,a progressive expansion module is used to gradually fuse the segmentation results obtained from the pre-expansion part at several different scales to obtain accurate detection results.The method is experimentally validated and analysed on datasets CTW1500 and ICDAR2015,and its F-values reach 80.4% and 83.0% respectively,which are 2.0% and 2.4% better than the next best method, indicating that the method is competitive with other methods in multi-directional text detection.