  Minimal problems in computer vision raise the demand of generating efficient
automatic solvers for polynomial equation systems. Given a polynomial system
repeated with different coefficient instances, the traditional Gr\"obner basis
or normal form based solution is very inefficient. Fortunately the Gr\"obner
basis of a same polynomial system with different coefficients is found to share
consistent inner structure. By precomputing such structures offline, Gr\"obner
basis as well as the polynomial system solutions can be solved automatically
and efficiently online. In the past decade, several tools have been released to
generate automatic solvers for a general minimal problems. The most recent tool
autogen from Larsson et al. is a representative of these tools with
state-of-the-art performance in solver efficiency. GAPS wraps and improves
autogen with more user-friendly interface, more functionality and better
stability. We demonstrate in this report the main approach and enhancement
features of GAPS. A short tutorial of the software is also included.
