论文标题
自动从图形屏幕截图基于Deep Autocoder生成代码
Automatically Generating Codes from Graphical Screenshots Based on Deep Autocoder
论文作者
论文摘要
在软件前端开发过程中，将图形用户界面（GUI）图像转换为相应的前端代码的工作是不可避免的乏味的工作。已经有一些尝试使这项工作是自动的。但是，由于缺乏注意力机制的指导，这些模型产生的GUI代码并不准确。为了解决这个问题，我们提出了基于人工监督的注意机制的PixCoder。该方法是训练神经网络以预测输入GUI图像中的样式表，然后输出向量。 PixCoder根据输出向量生成针对特定平台的GUI代码。实验结果表明，PixCoder生成的GUI代码的准确性超过95％。
During software front-end development, the work to convert Graphical User Interface(GUI) image to the corresponding front-end code is an inevitable tedious work. There have been some attempts to make this work to be automatic. However, the GUI code generated by these models is not accurate due to the lack of attention mechanism guidance. To solve this problem, we propose PixCoder based on an artificially supervised attention mechanism. The approach is to train a neural network to predict the style sheets in the input GUI image and then output a vector. PixCoder generate the GUI code targeting specific platform according to the output vector. The experimental results have shown the accuracy of the GUI code generated by PixCoder is over 95%.
