FLOOR PLAN GENERATION USING GAN

Abstract

Whenever landowner wants to build a house, he needs to prepare design (floor plan) of the house. He needs to decide where the main entrace, opening will be, how is he going to split the room, what portion of buildings will be seperated for bedroom, kitchen, bathroom etc. These are general questions that hits in mind. In order to solve these queries, he consult an architect. Architect would use different planning tools to generate the plan of the building. Initially, it would be difficult for an architect to make plan. So, Floor Plan Generation using GAN that would produce conceptual floor plan that best suits parcel of the land to provide a vision that can help architects was introduced. Architects would be able to choose among generated plan and then modify accordingly. This method would be relatively easier than directly generating plan from scratch. Moreover, to generate the plan, the system will get parcel of the land from architect, mapped it to footprint, room split and finally furnished room. The system will use conditional GAN for generation. It will also generate the 3D model of generated floor plan. Here, datasets for training with 55.3% accuracy for parcel and footprint and done manually for remaining. Similarly 98.27% accurately prepared furnished datasets using template matching and parameter tuning was prepared. The gan model image was generated with 1.6629 ± 0.1558 Inception Score for footprint, 2.0637 ± 0.1436 Inception Score for roomsplit, 1.7543 ± 0.0949 Inception Score for roomsplit. And the corresponding FID score are 99.148, 55.375, 65.957 respectively.