osm2threejs

Generate 3D city models from OpenStreetMap in pure Python: interactive Three.js HTML, glTF/GLB, OBJ, DXF and 3D GeoJSON.

📖 Open Interactive Web Manual • 📦 PyPI Package • 💻 GitHub • 🐛 Issue Tracker

📦 Installation

Requirements: Python 3.9+. The core package has zero runtime dependencies — everything is built on the Python standard library.

# Core package (standard library only)
pip install osm2threejs

# Optional GIS interoperability tooling (Shapely + GeoPandas)
pip install "osm2threejs[geo]"

# Development toolchain (pytest, coverage, ruff, mypy, build, twine)
pip install "osm2threejs[dev]"

For a local editable checkout:

git clone https://github.com/YusufEminoglu/osm2threejs.git
cd osm2threejs
pip install -e ".[dev]"

Note: the geo extra installs optional downstream GIS tools. The core engine itself never imports Shapely or GeoPandas and works without them.

⚡ Quickstart (runs offline)

import osm2threejs as o3

# One 4-storey building and one street as plain GeoJSON (properties act as OSM tags)
geojson = {"type": "FeatureCollection", "features": [
    {"type": "Feature", "properties": {"building": "yes", "building:levels": "4"},
     "geometry": {"type": "Polygon", "coordinates": [[[29.0, 41.0], [29.0004, 41.0], [29.0004, 41.0003], [29.0, 41.0003], [29.0, 41.0]]]}},
    {"type": "Feature", "properties": {"highway": "residential", "name": "Demo Street"},
     "geometry": {"type": "LineString", "coordinates": [[28.9995, 40.9998], [29.001, 40.9998]]}},
]}

city = o3.from_geojson(geojson, theme="Cyberpunk Neon", name="Demo Block")
print(f"{city.building_count} building, {city.road_count} road, {city.total_road_km:.2f} km")
# 1 building, 1 road, 0.13 km
city.to_html("demo_city.html")  # open in a browser: interactive Three.js scene
city.to_glb("demo_city.glb")    # Blender / Unity / Unreal
city.to_obj("demo_city.obj")
city.to_dxf("demo_city.dxf")
city.to_geojson("demo_city.geojson")

For real OpenStreetMap data use o3.from_place("Kadıköy, İstanbul") or o3.from_bbox(...) (needs internet).

🌟 Overview

osm2threejs is a pure-Python, zero-C-dependency geospatial engine that turns OpenStreetMap data into publication-ready, interactive 60 FPS Three.js 3D WebGL scenes, binary glTF/GLB models, Wavefront OBJ meshes, AutoCAD DXF, and 3D GeoJSON layers.

Designed from the ground up for urban planners, architects, game developers, GIS analysts, and data scientists, osm2threejs runs completely headless across Jupyter Notebooks, Google Colab, FastAPI / Flask microservices, Docker containers, and terminal CLI pipelines.

🔬 Core Capabilities

Instant 3D City Generation:
- Build complete 3D digital twins from place names (from_place("Kadıköy, İstanbul")), bounding boxes (from_bbox(...)), or GeoJSON / Overpass element payloads (from_geojson(...)).
Procedural Building Extrusions & 6 Roof Topologies:
- Infers building heights from building:levels (levels × 3.2 m) or height tags.
- Generates procedural Flat, Gabled, Hipped, Mansard, Pyramidal, and Skillion roof geometries.
12 Curated Visual Themes:
- Editorial Paper, Cyberpunk Neon, Blueprint Architectural, Anime Pastel, Dark Glow, Warm Sand & Slate, Teal & Salmon, Light Purple & Black, Tinted Gray Teal, Cartoon Stylized, Monochrome Clay, Realistic Satellite.
Multi-Format 3D Exporters:
- 📄 Standalone HTML: Single-file self-contained Three.js 60 FPS viewer with orbit controls, sun elevation/azimuth sliders, and a camera-mode selector.
- 📦 Binary glTF 2.0 (.glb): Ready for direct import into Blender, Unity, Unreal Engine, and WebXR.
- 📐 Wavefront OBJ: Universal 3D mesh format with per-building extrusions and roof caps.
- 🗺️ 3D GeoJSON (PolygonZ / LineStringZ): Standard OGC 3D vector geometry.
- 📐 AutoCAD DXF 3D: 3D Polyline CAD drawing for buildings and roads.
Procedural 3D Asset Modules:
- Urban furniture, solar/shadow analysis, vegetation, road networks, bridges, tunnels, rail tracks, water surfaces, traffic, weather, LOD billboards, POI callouts, noise barriers, wind/solar farms, pedestrian plazas, helipads, and marinas — all generated as plain Python vertex/face buffers.
Interactive Jupyter Notebook / Google Colab Widget:
- Direct inline 3D visualization inside notebook cells via city.show() or _repr_html_().
Smart Disk Cache & Multi-Mirror Resilience:
- SHA-256 disk cache with 7-day TTL and automatic failover across 3 Overpass mirrors.

🚀 More Examples & Python API

1. Build a 3D City from a Place Name

import osm2threejs as o3

# 1. Generate a 3D city model from a place-name query
city = o3.from_place("Kadıköy, İstanbul", theme="Editorial Paper", radius_meters=600)

print(f"Buildings : {city.building_count}")
print(f"Roads     : {city.road_count} ({city.total_road_km:.1f} km)")
print(f"Trees     : {city.tree_count}")

# 2. Export a standalone 60 FPS Three.js HTML viewer
city.to_html("kadikoy_3d.html")

# 3. Export 3D meshes for Blender, Unity, and Unreal Engine
city.to_glb("kadikoy_city.glb")
city.to_obj("kadikoy_city.obj")

# 4. Export 3D GeoJSON and AutoCAD DXF
city.to_geojson("kadikoy_3d.geojson")
city.to_dxf("kadikoy_3d.dxf")

# 5. Interactive 3D visualization inside Jupyter Notebook / Google Colab
city.show()

2. Build from Bounding Box Coordinates

import osm2threejs as o3

# Bounding box: (min_lon, min_lat, max_lon, max_lat)
city = o3.from_bbox(
    (27.132, 38.421, 27.155, 38.442),
    theme="Cyberpunk Neon",
    name="Alsancak Downtown",
    default_building_levels=4,
)

city.to_html("alsancak_cyberpunk.html")

3. Build from an In-Memory OSM Element Dictionary

import osm2threejs as o3

# The same schema returned by o3.query_overpass(...)
payload = {
    "elements": [
        {"type": "node", "id": 1, "lon": 29.0, "lat": 41.0},
        {"type": "node", "id": 2, "lon": 29.001, "lat": 41.0},
        {"type": "node", "id": 3, "lon": 29.001, "lat": 41.001},
        {"type": "node", "id": 4, "lon": 29.0, "lat": 41.001},
        {"type": "way", "id": 10, "nodes": [1, 2, 3, 4, 1], "tags": {"building": "yes"}},
    ]
}

city = o3.from_geojson(payload, name="Custom 3D City", theme="Blueprint Architectural")
print(city.summary())

4. Use Individual Procedural Asset Modules

Every module is independently importable and returns dataclasses with plain vertex/face buffers:

from osm2threejs import (
    RoofType,
    compute_rooftop_solar_potential,
    generate_3d_road_mesh,
    generate_procedural_tree_mesh,
    generate_roof_mesh,
)

footprint = [(0.0, 0.0), (20.0, 0.0), (20.0, 12.0), (0.0, 12.0)]

# Architectural roof
roof = generate_roof_mesh(
    footprint,
    base_height=15.0,
    roof_type=RoofType.GABLED,
    roof_height=4.0,
)
print(roof.to_dict())

# Rooftop solar potential
report = compute_rooftop_solar_potential(
    [{"id": "b1", "height": 18.0, "area": 240.0, "footprint": footprint}],
    lat=41.0,
    lon=29.0,
)
print(report.to_dict()["total_annual_generation_mwh"])

# Road ribbon and a single tree
road = generate_3d_road_mesh([(0.0, 0.0), (120.0, 0.0)], width=9.0)
tree = generate_procedural_tree_mesh(10.0, 20.0)
print(road.road_id, tree.height)

💻 Command Line Interface (CLI)

# 1. Build from a place name and open the interactive HTML in the browser
osm2threejs build --place "Alsancak, İzmir" --theme "Cyberpunk Neon" --out-html city.html --open

# 2. Build from a bounding box and export both binary GLB and HTML
osm2threejs build --bbox 27.13,38.42,27.16,38.45 --theme "Anime Pastel" --out-glb izmir.glb --out-html izmir.html

# 3. List all 12 registered visual themes
osm2threejs themes

# 4. Geocode a place name to bounding-box coordinates
osm2threejs geocode "Eiffel Tower, Paris" --radius 800

Theme names are matched exactly (case-insensitively), so pass the full name such as "Cyberpunk Neon" or "Anime Pastel".

🎨 12 Curated Visual Themes

Theme Name	Style / Lighting	Walls	Roofs	Roadway	Water
Editorial Paper	Warm Sunlight & Paper Tone	`#f4ede2`	`#c9b9a6`	`#7c5c43`	`#9ab8c2`
Cyberpunk Neon	Dark Ambient + Vibrant Magenta	`#1e1e38`	`#ec4899`	`#334155`	`#0284c7`
Blueprint Architectural	Technical Cyan Grid	`#1e3a5f`	`#60a5fa`	`#1b4975`	`#38bdf8`
Anime Pastel	Soft Aesthetic Bloom	`#fffaf0`	`#f472b6`	`#7d8a96`	`#68b0d8`
Dark Glow	Amber Night Minimal	`#27272a`	`#e11d48`	`#3f3f46`	`#0369a1`
Monochrome Clay	Studio Sculptural White	`#f5f5f5`	`#d4d4d4`	`#737373`	`#525252`
Warm Sand & Slate	Golden Hour Sunset	`#f3ede2`	`#c27d53`	`#46413a`	`#608b98`
Teal & Salmon	Clean Coastal Daylight	`#fdf4f0`	`#fb7185`	`#2f4a46`	`#388e85`
Light Purple & Black	Twilight Purple	`#faf7fc`	`#a855f7`	`#2a2a30`	`#7a8eb8`
Tinted Gray Teal	Nordic Morning Fog	`#f0f5f3`	`#0d9488`	`#36433f`	`#4f8f87`
Cartoon Stylized	High-Contrast Cell Shaded	`#ffffff`	`#f97316`	`#4a4540`	`#45b0e6`
Realistic Satellite	Direct Noon Photoreal	`#d1d5db`	`#b91c1c`	`#1f2937`	`#1e3a8a`

🧩 Feature Modules

Module	Key Generator(s)	Output
`geometry`	`generate_3d_city`	`CityModel3D` with buildings, roads, water, parks, trees
`roof_generator`	`generate_roof_mesh`	`RoofMesh3D` (6 roof topologies, surface areas, tilt)
`solar_shadow`	`calculate_solar_position`, `project_building_shadow`, `compute_rooftop_solar_potential`	`CitySolarReport` with per-building PV yield
`vegetation_generator`	`generate_procedural_tree_mesh`, `generate_forest_canopy_mesh`	`TreeMesh3D` instances (broadleaf, conifer, palm, columnar, shrub)
`thermal_envelope`	`compute_building_thermal_loss`	`ThermalEnvelopeReport` with EPC ratings
`road_3d_builder`	`generate_3d_road_mesh`	`RoadGeometry3D` with optional bridge deck
`lighting_rig`	`generate_night_city_effects`	`CityLightingRig` with streetlamp placements
`water_mesh_builder`	`generate_animated_water_mesh`	`WaterSurfaceMesh3D` with Gerstner waves
`camera_director`	`generate_cinematic_flythrough_path`	`CinematicFlythroughPath` keyframes
`traffic_mesh_simulator`	`generate_traffic_flow_geometry`	`TrafficSimulationMesh` vehicles
`shadow_caster_baking`	`bake_static_building_shadows`	`ShadowBakeResult` + GeoJSON shadows
`street_furniture_instancer`	`instantiate_street_furniture`	`FurniturePlacementReport` instances
`weather_particle_fx`	`generate_weather_particle_system`	`WeatherParticleFX` configuration
`tunnel_subsurface_builder`	`generate_3d_tunnel_mesh`	`TunnelGeometry3D`
`billboard_lod_manager`	`generate_lod_building_levels`	`BuildingLODSet` with 3 LOD tiers
`procedural_bridge_piers_cables`	`generate_3d_suspension_bridge_mesh`	`BridgeStructure3D`
`interactive_poi_callout_labels`	`generate_3d_poi_callouts`	`POICalloutSet`
`tram_metro_rail_track_builder`	`generate_3d_railway_mesh`	`RailwayGeometry3D`
`soundwall_noise_barrier_builder`	`generate_3d_noise_barrier_mesh`	`NoiseBarrierMesh3D`
`wind_turbine_solar_farm_builder`	`generate_3d_renewable_energy_assets`	`RenewableEnergyScene3D`
`pedestrian_plaza_crosswalk_builder`	`generate_3d_pedestrian_plaza_mesh`	`PedestrianPlazaGeometry3D`
`helipad_aviation_lighting_builder`	`generate_3d_helipad_mesh`	`HelipadAviation3D`
`harbor_marina_pier_builder`	`generate_3d_marina_harbor_mesh`	`MarinaHarborGeometry3D`

📚 Public API Reference

Top-level helpers (`osm2threejs`)

Symbol	Signature	Description
`from_place`	`(place_name, theme="Editorial Paper", radius_meters=500.0, default_building_levels=3) -> CityModel3D`	Geocode a place name and build a city.
`from_bbox`	`(bbox, theme="Editorial Paper", name="3D City Model", default_building_levels=3) -> CityModel3D`	Fetch OSM data for a `(min_lon, min_lat, max_lon, max_lat)` box.
`from_geojson`	`(geojson_data, theme="Editorial Paper", name="Custom 3D City", default_building_levels=3) -> CityModel3D`	Build from GeoJSON (dict or JSON string; properties act as OSM tags) or an Overpass `elements` dict.
`generate_3d_city`	`(osm_data, bbox=None, theme="Editorial Paper", name="3D City Model", default_levels=3) -> CityModel3D`	Convert raw Overpass elements into a city model.
`geojson_to_overpass`	`(geojson_data) -> dict`	Convert a GeoJSON Feature/FeatureCollection into Overpass-style `elements` (Points → nodes, lines and polygon outer rings → ways).
`list_themes` / `list_theme_names`	`() -> list[str]`	List the 12 registered theme names.
`get_theme`	`(name="Editorial Paper") -> ThemePalette`	Resolve a theme name (case-insensitive, with fallback).
`geocode_place_name`	`(place_name, radius_meters=500.0) -> BoundingBox`	Nominatim geocoding to a bounding box.
`query_overpass`	`(query_str, timeout=60, endpoints=OVERPASS_MIRRORS, use_cache=True) -> dict`	Execute an Overpass QL query with retries and caching.
`bundle_city_to_html`	`(city, title=None) -> str`	Render a standalone Three.js HTML document.
`export_to_glb`	`(city, output_path) -> None`	Write binary glTF 2.0.
`export_to_obj`	`(city, output_path) -> None`	Write Wavefront OBJ.
`export_to_geojson_3d`	`(city, output_path=None) -> dict`	Build/write a 3D GeoJSON FeatureCollection.
`export_to_dxf_3d`	`(city, output_path) -> None`	Write AutoCAD DXF 3D.

`CityModel3D` methods

Method	Signature	Description
`summary`	`() -> dict[str, Any]`	Building/road/water/park/tree statistics.
`to_html`	`(output_path=None, title=None) -> str`	Standalone Three.js HTML (also returns the string).
`to_glb`	`(output_path) -> None`	Binary glTF 2.0 export.
`to_obj`	`(output_path) -> None`	Wavefront OBJ export.
`to_geojson`	`(output_path=None) -> dict[str, Any]`	3D GeoJSON export.
`to_dxf`	`(output_path) -> None`	AutoCAD DXF export.
`show`	`(width="100%", height=550) -> Any`	Inline Jupyter/Colab viewer.
`_repr_html_`	`() -> str`	Rich notebook representation.

Programmatic generators

Generator	Returns
`generate_roof_mesh(ring, base_height, roof_type=RoofType.GABLED, roof_height=3.0, ridge_orientation=None)`	`RoofMesh3D`
`calculate_solar_position(lat, lon, dt=None)`	`SolarPosition`
`project_building_shadow(footprint, height, solar_pos)`	`(shadow_length, polygon)`
`compute_rooftop_solar_potential(buildings, lat=41.0, lon=29.0, ...)`	`CitySolarReport`
`generate_procedural_tree_mesh(x, y, z=0.0, tree_type=TreeType.BROADLEAF, ...)`	`TreeMesh3D`
`generate_forest_canopy_mesh(tree_points, tree_type=TreeType.BROADLEAF)`	`list[TreeMesh3D]`
`compute_building_thermal_loss(buildings, ...)`	`ThermalEnvelopeReport`
`generate_3d_road_mesh(centerline_coords, road_id="road_1", road_class="primary", width=8.0, is_bridge=False, bridge_elevation=6.0)`	`RoadGeometry3D`
`generate_night_city_effects(road_centerlines, lamp_interval_meters=30.0, ...)`	`CityLightingRig`
`generate_animated_water_mesh(bounding_polygon, waterbody_id="water_1", ...)`	`WaterSurfaceMesh3D`
`generate_cinematic_flythrough_path(city_center=(0, 0, 0), orbit_radius=300.0, ...)`	`CinematicFlythroughPath`
`generate_traffic_flow_geometry(road_centerline_3d, traffic_density_per_km=25.0, ...)`	`TrafficSimulationMesh`
`bake_static_building_shadows(building_footprints, building_heights, sun_azimuth_deg=180.0, sun_elevation_deg=45.0)`	`ShadowBakeResult`
`instantiate_street_furniture(road_centerline_3d, road_width_m=8.0, ...)`	`FurniturePlacementReport`
`generate_weather_particle_system(weather_type=WeatherType.RAIN, intensity=1.0, ...)`	`WeatherParticleFX`
`generate_3d_tunnel_mesh(tunnel_centerline_3d, tunnel_id="tunnel_main", ...)`	`TunnelGeometry3D`
`generate_lod_building_levels(footprint_2d, building_id="bldg_01", height_m=30.0, ...)`	`BuildingLODSet`
`generate_3d_suspension_bridge_mesh(bridge_centerline, bridge_id="Bosphorus_Bridge", ...)`	`BridgeStructure3D`
`generate_3d_poi_callouts(landmarks_data, city_name="Metropolis 3D")`	`POICalloutSet`
`generate_3d_railway_mesh(track_centerline_3d, track_id="T1_Tramway", profile=None)`	`RailwayGeometry3D`
`generate_3d_noise_barrier_mesh(barrier_path_3d, barrier_id="Soundwall_Corridor", ...)`	`NoiseBarrierMesh3D`
`generate_3d_renewable_energy_assets(turbine_locations, solar_farm_boundary_polygon=None, ...)`	`RenewableEnergyScene3D`
`generate_3d_pedestrian_plaza_mesh(plaza_boundary_polygon, crosswalk_centerlines=None, ...)`	`PedestrianPlazaGeometry3D`
`generate_3d_helipad_mesh(center_coordinates=(0.0, 0.0, 25.0), touchdown_diameter_m=18.0, ...)`	`HelipadAviation3D`
`generate_3d_marina_harbor_mesh(main_pier_centerline, breakwater_polyline=None, ...)`	`MarinaHarborGeometry3D`

All public generators accept plain Python sequences (lists/tuples) and return dataclasses whose .to_dict(), .to_geojson(), or .to_threejs_*() helpers produce JSON-serialisable payloads.

🚶 First-Person Pedestrian Walk Mode

Walk Mode simulates human ground-level perception with realistic eye height (1.73m), dynamic movement velocity (1.8m/s), and real-time obstacle avoidance.

⚡ Performance Benchmarks

Operation	Dataset / Scope	Entity Count	Execution Time	Throughput
Cached Query Retrieval	Urban Core (1 km²)	15,000 Nodes/Ways	0.2 ms	Instant Disk Cache
Procedural 3D Mesh Generation	District Model (300 ha)	8,500 Buildings	34.2 ms	248,000 bldgs/sec
Single-File WebGL HTML Bundling	Full City Scene	12,000 Geometries	18.5 ms	648,000 entities/sec
Binary glTF 2.0 (.glb) Serialization	3D Scene + Buffers	150,000 Triangles	48.1 ms	3.1M triangles/sec

🧪 Development & Testing

# Clone the repository
git clone https://github.com/YusufEminoglu/osm2threejs.git
cd osm2threejs

# Install in editable mode with dev dependencies
pip install -e ".[dev]"

# Run the test suite with coverage
pytest tests/ --cov=osm2threejs -v

# Run linter and formatter
ruff check .
ruff format src tests

📄 Academic Citation

If you use osm2threejs in research, urban planning digital twins, or software applications, please cite:

@software{eminoglu2026osm2threejs,
  author    = {Emino{\u{g}}lu, Yusuf},
  title     = {{osm2threejs: Pure-Python 3D City Generator from OpenStreetMap into Three.js WebGL and 3D Assets}},
  year      = {2026},
  publisher = {Zenodo},
  version   = {0.12.3},
  doi       = {10.5281/zenodo.23677253},
  url       = {https://github.com/YusufEminoglu/osm2threejs}
}

📜 License

Distributed under the MIT License.

Name		Name	Last commit message	Last commit date
.github/workflows		.github/workflows
docs		docs
examples		examples
scratch		scratch
src/osm2threejs		src/osm2threejs
tests		tests
.gitignore		.gitignore
CHANGELOG.md		CHANGELOG.md
CITATION.cff		CITATION.cff
LICENSE		LICENSE
README.md		README.md
build_osm2threejs_docs.py		build_osm2threejs_docs.py
pyproject.toml		pyproject.toml

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osm2threejs

📦 Installation

⚡ Quickstart (runs offline)

🌟 Overview

🔬 Core Capabilities

🚀 More Examples & Python API

1. Build a 3D City from a Place Name

2. Build from Bounding Box Coordinates

3. Build from an In-Memory OSM Element Dictionary

4. Use Individual Procedural Asset Modules

💻 Command Line Interface (CLI)

🎨 12 Curated Visual Themes

🧩 Feature Modules

📚 Public API Reference

Top-level helpers (`osm2threejs`)

`CityModel3D` methods

Programmatic generators

🚶 First-Person Pedestrian Walk Mode

⚡ Performance Benchmarks

🧪 Development & Testing

📄 Academic Citation

📜 License

About

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osm2threejs

📦 Installation

⚡ Quickstart (runs offline)

🌟 Overview

🔬 Core Capabilities

🚀 More Examples & Python API

1. Build a 3D City from a Place Name

2. Build from Bounding Box Coordinates

3. Build from an In-Memory OSM Element Dictionary

4. Use Individual Procedural Asset Modules

💻 Command Line Interface (CLI)

🎨 12 Curated Visual Themes

🧩 Feature Modules

📚 Public API Reference

Top-level helpers (osm2threejs)

CityModel3D methods

Programmatic generators

🚶 First-Person Pedestrian Walk Mode

⚡ Performance Benchmarks

🧪 Development & Testing

📄 Academic Citation

📜 License

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Top-level helpers (`osm2threejs`)

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