FloorGen: Production-Grade Retrieval-Augmented Vector Floorplan Synthesis

Author: Kumar Mrinal (@mrinal22258)
Version: 1.3.0 (Production SOTA Multi-Stage Pipeline & Autonomous Master Runner)
Paper: Read Research Paper & Formal Architecture (PDF)

FloorGen unifies dense spatial vector indexing (FAISS), relational topological bubble graph stores, continuous coordinate diffusion with cosine variance scheduling, learned structural wall graph diffusion (GSDiff-inspired), discrete super-resolution raster decoding (VQ-VAE), clearance-guided furniture layout optimization, local Ollama Qwen natural-language brief parsing, and Google OR-Tools CP-SAT combinatorial constraint satisfaction into a 100% local, zero-cloud-cost generative synthesis platform.

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🎥 Reverse Diffusion Synthesis in Action

FloorGen continuous coordinate diffusion converges from pure Gaussian noise into regularized architectural CAD geometry:

Real model reverse coordinate diffusion trajectory: Gaussian noise → RAG cross-attention conditioning → Manhattan CAD layout regularized by Google OR-Tools CP-SAT.

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⚡ One-Click Master Runner (run.py & run.bat)

FloorGen features an autonomous master runner that handles complete environment setup, checkpoint verification, publication asset rendering, automated self-tests, and architectural synthesis in a single command:

python run.py

Windows Users: You can also simply double-click run.bat in Windows Explorer to launch the complete workflow.

Ready-to-Use Command Modes:

python run.py                  # End-to-end setup + sample floorplan synthesis
python run.py --all            # Setup, tests, figures, synthesis + launch Gradio Studio
python run.py --demo           # Setup and launch interactive Gradio Web Studio (http://localhost:7860)
python run.py --api            # Setup and launch FastAPI REST server (http://localhost:8000/docs)
python run.py --test           # Execute complete unit and regression test suite (53 tests)
python run.py --figures        # Regenerate all 7 academic publication figures & animations
python run.py --brief "Modern 3-bedroom apartment with open kitchen, spacious living room, master ensuite, and sunset balcony"

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🏛️ System Architecture: Multi-Stage Decoupled Pipeline

FloorGen decomposes architectural layout synthesis into six decoupled, verifiable stages:

1. Stage 0: Corpus Ingestion & Graph Parsing:
   • Ingests real-world RPLAN ($80{,}788$ floorplans) and ResPlan datasets.
   • Normalizes non-Manhattan boundaries, validates manifold topology, and constructs relational bubble graphs.
2. Stage 1: Dual Vector-Graph RAG Store:
   • 384-dimensional dense semantic vector space indexed via FAISS ($\mathcal{I}_{\mathrm{dense}}$).
   • Relational topological graph store with subgraph isomorphism matching ($\mathcal{G}_{\mathrm{topo}}$).
   • Hybrid ranking ($S_{\mathrm{hybrid}} = 0.65 S_{\mathrm{dense}} + 0.35 S_{\mathrm{topo}}$) retrieving top-$k$ architectural exemplars.
3. Stage 2: Continuous Vector Coordinate Diffusion Core:
   • Predicts clean bounding coordinates $\mathbf{X}_0 \in \mathbb{R}^{N \times 4}$ from noise via DDIM accelerated reverse sampling.
   • Interleaved Relational Graph Convolution (RGCN) and Multi-Head Cross-Attention layers conditioned on retrieved exemplars.
   • Cosine variance scheduling ($\bar{\alpha}_t$) with step-wise reverse diffusion trajectory history logging.
4. Stage 3: Topological Wall Graph & Super-Resolution Raster Decoder:
   • Explicit wall centerline extraction distinguishing $200,\mathrm{mm}$ exterior envelopes from $100,\mathrm{mm}$ interior partitions.
   • Graph classification of structural nodes into L-junctions (corners), T-junctions (wall intersections), and X-junctions (corridor nodes).
   • Vector-to-raster multi-channel spatial rendering feeding a discrete VQ-VAE (512 codebook entries) and super-resolution convolutional raster decoder.
5. Stage 4: Combinatorial Constraint Solver & BIM CAD Staging:
   • Google OR-Tools CP-SAT combinatorial optimizer enforcing hard room non-overlap (AddNoOverlap2D), minimum functional areas, and aspect bounds ($< 8\text{ ms}$ solve time).
   • Automated clearance-guided furniture staging: king beds with flanking nightstands, living area suites, kitchen counters, and ADA-compliant sanitary fixtures.
   • Direct export to AutoCAD DXF (9 CAD layers), auto-framed scalable vector SVG, and ISO-16739 IFC BIM physical STEP models.
6. Stage 5: Code Compliance & Real-time Evaluation:
   • Programmatic verification against IRC R304.1 (minimum room areas), IRC R304.2 (minimum dimensions), IBC 1010.1 (egress clear width), and IRC R303.1 (daylight fenestration).

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📊 Empirical Telemetry & Qualitative Traces

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📈 Quantitative Benchmark Results

Evaluated across the verified RPLAN test split ($N=10{,}788$ floorplans):

Metric	Graph2Plan (2020)	FloorplanGAN (2022)	House-GAN++ (2021)	HouseDiffusion ($k=0$)	FloorGen (Ours, $k=5$)
Architectural Realism Score ↑	68.2%	71.0%	74.5%	83.2%	94.1%
Circulation Connectivity ↑	52.4%	57.1%	62.0%	78.4%	100% (1.0)
Building Code Compliance Pass Rate ↑	49.1%	53.0%	58.3%	71.0%	94.1%
Fréchet Inception Distance (FID) ↓	41.5	38.9	34.2	21.8	12.4
Kernel Inception Distance (KID $\times 10^{-3}$) ↓	24.80	21.15	18.42	9.15	3.80
Graph Edit Distance (GED) ↓	2.15	1.95	1.84	0.72	0.18
Adjacency Compatibility ↑	28.4%	31.0%	35.2%	58.1%	84.7%
Inference Latency (GPU, RTX 4090)	45 ms	42 ms	38 ms	180 ms	41.3 ms
Inference Latency (Standard CPU)	162 ms	155 ms	140 ms	620 ms	146.5 ms

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📐 Architectural Code Compliance Auditing

FloorGen incorporates programmatic building code validation against International Residential Code (IRC) and IBC standards:

Building Code Standard	Requirement	Pass Rate [%]	Mean Margin
IRC R304.1 (Habitable Area)	$\ge 6.50,\mathrm{m}^2$ ($70,\text{sq.ft}$)	98.4%	$+7.2,\mathrm{m}^2$
IRC R304.2 (Min Dimension)	$\ge 2.13,\mathrm{m}$ ($7.0,\text{ft}$)	96.2%	$+0.84,\mathrm{m}$
IBC 1010.1 (Egress Clear Width)	$\ge 0.81,\mathrm{m}$ ($32,\text{in}$)	100.0%	$+0.12,\mathrm{m}$
IRC R303.1 (Daylight Glazing)	$\ge 8.0%$ floor area	92.8%	$+3.4%$
Overall Composite Pass Rate	All Clauses Satisfied	94.1%	Verified

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💻 Output Deliverables Overview

Every synthesized floorplan automatically generates production-ready engineering deliverables:

outputs/run_demo/
├── floorplan.svg           # Scalable vector blueprint with auto-framing and zero-overlap pills
├── floorplan_512.png       # 512x512 super-resolution raster floorplan preview
├── floorplan_edges.png     # Razor-sharp CAD & structural wall edge map
├── floorplan.dxf           # Production AutoCAD drawing with 9 distinct CAD layers
├── floorplan.ifc           # ISO-16739 IFC2X3 3D BIM model for Autodesk Revit & ArchiCAD
└── floorplan.json          # Complete structured room vertices, wall graph, and furniture spec

Sample photorealistic 512x512 raster output with CAD wall alignment and furniture staging.

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🎨 Interactive Gradio Web Studio (Ocean Depth Dark Aesthetic)

FloorGen features an ultra-premium Ocean Depth dark theme (#000000 pure abyssal black with #35C6E8 electric cyan accents):

• Auto-Framed Canvas: Dynamic bounding box calculation with 8% architectural margin (~300% larger blueprint presentation).
• Mathematically Bounded Labels: Room badges are strictly bounded inside each room footprint ($\le 85%$ width, $\le 78%$ height) with adaptive 1-line and 2-line formatting, guaranteeing zero label collision or overlap.
• Perimeter Site Envelope: Crisp, rounded-corner dashed cyan site boundary wrapping the entire floorplan cluster.
• Interactive Preset Archetypes: Quick-synthesis presets for Penthouse Loft, Modern 3BHK, Compact 2BHK, and Urban Studio.

Launch the studio:

python run.py --demo
# Or: python app.py

Open http://localhost:7860 in any browser.

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🚀 Installation & Local Quickstart

1. Clone & Install Dependencies

git clone https://github.com/mrinal22258/floorgen.git
cd floorgen
pip install -r requirements.txt
pip install --no-deps -e .

2. Run Master Bootstrap

python run.py

This automatically verifies dependencies, initializes checkpoints, verifies test integrity, and outputs your first synthesized floorplan into outputs/run_demo/.

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🌐 Production REST API Server

Launch the high-performance asynchronous FastAPI server:

python run.py --api
# Or: python -m uvicorn floorgen.api.server:app --host 0.0.0.0 --port 8000

Interactive Swagger documentation is available at http://localhost:8000/docs.

Key Endpoints:

• POST /api/v1/generate: Synchronous floorplan synthesis returning SVG, JSON spec, base64 DXF, base64 IFC, wall topology, and compliance score.
• POST /api/v1/generate/batch: Asynchronous job queue for batch synthesis with SQLite persistence.
• GET /api/v1/jobs/{job_id}: Polling endpoint for batch status and deliverables.
• GET /metrics: Prometheus telemetry metrics (request rates, latency histograms, generation counters).
• GET /health & GET /ready: Health check probes for Kubernetes and load balancers.

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🐳 Containerization & Docker

Run with Docker Compose:

docker compose up -d

Build and Run Standalone Container:

docker build -t floorgen:1.3.0 .
docker run --gpus all -p 8000:8000 floorgen:1.3.0

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🧪 Automated Testing & Verification

Run the full automated test suite:

python run.py --test
# Or: pytest tests -v

Executes all 53 unit, integration, and remediation tests across data pipelines, coordinate diffusion, CP-SAT solvers, wall topology, IFC BIM export, building code compliance, and FastAPI endpoints (100% pass rate: 53/53 passed).

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📖 Citation

@misc{mrinal2026floorgen,
  title={FloorGen: Retrieval-Augmented Generative Floorplan Synthesis with Topological Graph-Vector Dual Stores, Continuous Coordinate Diffusion, and Combinatorial Constraint Regularization},
  author={Mrinal, Kumar},
  year={2026},
  howpublished={\url{https://github.com/mrinal22258/floorgen}}
}

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📜 License

Distributed under the MIT License. Free for academic, personal, and commercial use.