Aiming at the problems of inconsistent text style before and after editing and insufficient readability of the generated new text in text image editing tasks， a text image editing method based on the guidance of font and character attributes was proposed. Firstly， the generation direction of text foreground style was guided by the font attribute classifier combined with font classification， perception and texture losses to improve the consistency of text style before and after editing. Secondly， the accurate generation of text glyphs was guided by the character attribute classifier combined with the character classification loss to reduce text artifacts and generation errors， and improve the readability of generated new text. Finally， the end-to-end fine-tuned training strategy was used to refine the generated results for the entire staged editing model. In the comparison experiments with SRNet （Style Retention Network） and SwapText， the proposed method achieves PSNR （Peak Signal-to-Noise Ratio） and SSIM （Structural SIMilarity） of 25.48 dB and 0.842， which are 2.57 dB and 0.055 higher than those of SRNet and 2.11 dB and 0.046 higher than those of SwapText， respectively； the Mean Square Error （MSE） is 0.004 3， which is 0.003 1 and 0.024 lower than that of SRNet and SwapText， respectively. Experimental results show that the proposed method can effectively improve the generation effect of text image editing.