  In real-world usage, existing GAN image generation tools come up short due to
their lack of intuitive interfaces and limited flexibility. To overcome these
limitations, we developed CanvasPic, an innovative tool for flexible GAN image
generation. Our tool introduces a novel 2D layout design that allows users to
intuitively control image attributes based on real-world images. By interacting
with the distances between images in the spatial layout, users are able to
conveniently control the influence of each attribute on the target image and
explore a wide range of generated results. Considering practical application
scenarios, a user study involving 24 participants was conducted to compare our
tool with existing tools in GAN image generation. The results of the study
demonstrate that our tool significantly enhances the user experience, enabling
more effective achievement of desired generative results.
