Text recognition in nature scene is currently applied in various intelligence equipment. The first step of text recognition is to precisely locate the text. In the Pixel Link text location methods, there are mainly two problems: too much background information is incorporated in the text region, and the test accuracy is insufficient. Aiming at these issues, an improved text location method was proposed to precisely locate the text in the natural scene. At first, an attention mechanism was incorporated into the original network. By focusing on the weight relationship between feature channels in the generated feature map, one can improve the weight coefficient of effective feature channels, and suppress the weight of inefficient or invalid feature channels. In the second, by changing the form of data set annotation, the coordinate points can be expressed as a series of sequence forms, so that the text lines can be framed adaptively in the LSTM model. At last, the located object is rotated according to the angle