City Map Poster Generator

Generate beautiful, minimalist map posters for any city in the world.

Examples

Installation

With uv (Recommended)

Make sure uv is installed. Running the script by prepending uv run automatically creates and manages a virtual environment.

# First run will automatically install dependencies
uv run ./create_map_poster.py --city "Paris" --country "France"

# Or sync dependencies explicitly first (using locked versions)
uv sync --locked
uv run ./create_map_poster.py --city "Paris" --country "France"

With pip + venv

python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate
pip install -r requirements.txt

Usage

Generate Poster

If you're using uv:

uv run ./create_map_poster.py --city <city> --country <country> [options]

Otherwise (pip + venv):

python create_map_poster.py --city <city> --country <country> [options]

Required Options

Optional Flags

Multilingual Support - i18n

Display city and country names in your language with custom fonts from google fonts:

Examples:

# Japanese
python create_map_poster.py -c "Tokyo" -C "Japan" -dc "東京" -dC "日本" --font-family "Noto Sans JP"

# Korean
python create_map_poster.py -c "Seoul" -C "South Korea" -dc "서울" -dC "대한민국" --font-family "Noto Sans KR"

# Arabic
python create_map_poster.py -c "Dubai" -C "UAE" -dc "دبي" -dC "الإمارات" --font-family "Cairo"

Note: Fonts are automatically downloaded from Google Fonts and cached locally in fonts/cache/.

Resolution Guide (300 DPI)

Use these values for -W and -H to target specific resolutions:

Usage Examples

Basic Examples

# Simple usage with default theme
python create_map_poster.py -c "Paris" -C "France"

# With custom theme and distance
python create_map_poster.py -c "New York" -C "USA" -t noir -d 12000

Multilingual Examples (Non-Latin Scripts)

Display city names in their native scripts:

# Japanese
python create_map_poster.py -c "Tokyo" -C "Japan" -dc "東京" -dC "日本" --font-family "Noto Sans JP" -t japanese_ink

# Korean
python create_map_poster.py -c "Seoul" -C "South Korea" -dc "서울" -dC "대한민국" --font-family "Noto Sans KR" -t midnight_blue

# Thai
python create_map_poster.py -c "Bangkok" -C "Thailand" -dc "กรุงเทพมหานคร" -dC "ประเทศไทย" --font-family "Noto Sans Thai" -t sunset

# Arabic
python create_map_poster.py -c "Dubai" -C "UAE" -dc "دبي" -dC "الإمارات" --font-family "Cairo" -t terracotta

# Chinese (Simplified)
python create_map_poster.py -c "Beijing" -C "China" -dc "北京" -dC "中国" --font-family "Noto Sans SC"

# Khmer
python create_map_poster.py -c "Phnom Penh" -C "Cambodia" -dc "ភ្នំពេញ" -dC "កម្ពុជា" --font-family "Noto Sans Khmer"

Advanced Examples

# Iconic grid patterns
python create_map_poster.py -c "New York" -C "USA" -t noir -d 12000           # Manhattan grid
python create_map_poster.py -c "Barcelona" -C "Spain" -t warm_beige -d 8000   # Eixample district

# Waterfront & canals
python create_map_poster.py -c "Venice" -C "Italy" -t blueprint -d 4000       # Canal network
python create_map_poster.py -c "Amsterdam" -C "Netherlands" -t ocean -d 6000  # Concentric canals
python create_map_poster.py -c "Dubai" -C "UAE" -t midnight_blue -d 15000     # Palm & coastline

# Radial patterns
python create_map_poster.py -c "Paris" -C "France" -t pastel_dream -d 10000   # Haussmann boulevards
python create_map_poster.py -c "Moscow" -C "Russia" -t noir -d 12000          # Ring roads

# Organic old cities
python create_map_poster.py -c "Tokyo" -C "Japan" -t japanese_ink -d 15000    # Dense organic streets
python create_map_poster.py -c "Marrakech" -C "Morocco" -t terracotta -d 5000 # Medina maze
python create_map_poster.py -c "Rome" -C "Italy" -t warm_beige -d 8000        # Ancient layout

# Coastal cities
python create_map_poster.py -c "San Francisco" -C "USA" -t sunset -d 10000    # Peninsula grid
python create_map_poster.py -c "Sydney" -C "Australia" -t ocean -d 12000      # Harbor city
python create_map_poster.py -c "Mumbai" -C "India" -t contrast_zones -d 18000 # Coastal peninsula

# River cities
python create_map_poster.py -c "London" -C "UK" -t noir -d 15000              # Thames curves
python create_map_poster.py -c "Budapest" -C "Hungary" -t copper_patina -d 8000  # Danube split

# Override center coordinates
python create_map_poster.py --city "New York" --country "USA" -lat 40.776676 -long -73.971321 -t noir

# List available themes
python create_map_poster.py --list-themes

# Generate posters for every theme
python create_map_poster.py -c "Tokyo" -C "Japan" --all-themes

Distance Guide

Themes

17 themes available in themes/ directory:

Output

Posters are saved to posters/ directory with format:

{city}_{theme}_{YYYYMMDD_HHMMSS}.png

Adding Custom Themes

Create a JSON file in themes/ directory:

{
  "name": "My Theme",
  "description": "Description of the theme",
  "bg": "#FFFFFF",
  "text": "#000000",
  "gradient_color": "#FFFFFF",
  "water": "#C0C0C0",
  "parks": "#F0F0F0",
  "road_motorway": "#0A0A0A",
  "road_primary": "#1A1A1A",
  "road_secondary": "#2A2A2A",
  "road_tertiary": "#3A3A3A",
  "road_residential": "#4A4A4A",
  "road_default": "#3A3A3A"
}

Project Structure

map_poster/
├── create_map_poster.py    # Main script
├── font_management.py      # Font loading and Google Fonts integration
├── themes/                 # Theme JSON files
├── fonts/                  # Font files
│   ├── Roboto-*.ttf        # Default Roboto fonts
│   └── cache/              # Downloaded Google Fonts (auto-generated)
├── posters/                # Generated posters
└── README.md

Hacker's Guide

Quick reference for contributors who want to extend or modify the script.

Contributors Guide

• Bug fixes are welcomed
• Don't submit user interface (web/desktop)
• Don't Dockerize for now
• If you vibe code any fix please test it and see before and after version of poster
• Before embarking on a big feature please ask in Discussions/Issue if it will be merged

Architecture Overview

┌─────────────────┐     ┌──────────────┐     ┌─────────────────┐
│   CLI Parser    │────▶│  Geocoding   │────▶│  Data Fetching  │
│   (argparse)    │     │  (Nominatim) │     │    (OSMnx)      │
└─────────────────┘     └──────────────┘     └─────────────────┘
                                                     │
                        ┌──────────────┐             ▼
                        │    Output    │◀────┌─────────────────┐
                        │  (matplotlib)│     │   Rendering     │
                        └──────────────┘     │  (matplotlib)   │
                                             └─────────────────┘

Key Functions

Rendering Layers (z-order)

z=11  Text labels (city, country, coords)
z=10  Gradient fades (top & bottom)
z=3   Roads (via ox.plot_graph)
z=2   Parks (green polygons)
z=1   Water (blue polygons)
z=0   Background color

OSM Highway Types → Road Hierarchy

# In get_edge_colors_by_type() and get_edge_widths_by_type()
motorway, motorway_link     → Thickest (1.2), darkest
trunk, primary              → Thick (1.0)
secondary                   → Medium (0.8)
tertiary                    → Thin (0.6)
residential, living_street  → Thinnest (0.4), lightest

Typography & Script Detection

The script automatically detects text scripts to apply appropriate typography:

• Latin scripts (English, French, Spanish, etc.): Letter spacing applied for elegant "P A R I S" effect
• Non-Latin scripts (Japanese, Arabic, Thai, Korean, etc.): Natural spacing for "東京" (no gaps between characters)

Script detection uses Unicode ranges (U+0000-U+024F for Latin). If >80% of alphabetic characters are Latin, spacing is applied.

Adding New Features

New map layer (e.g., railways):

# In create_poster(), after parks fetch:
try:
    railways = ox.features_from_point(point, tags={'railway': 'rail'}, dist=dist)
except:
    railways = None

# Then plot before roads:
if railways is not None and not railways.empty:
    railways = railways.to_crs(g_proj.graph["crs"])
    railways.plot(ax=ax, color=THEME['railway'], linewidth=0.5, zorder=2.5)

New theme property:

1. Add to theme JSON: "railway": "#FF0000"
2. Use in code: THEME['railway']
3. Add fallback in load_theme() default dict

Typography Positioning

All text uses transform=ax.transAxes (0-1 normalized coordinates):

y=0.14  City name (spaced letters for Latin scripts)
y=0.125 Decorative line
y=0.10  Country name
y=0.07  Coordinates
y=0.02  Attribution (bottom-right)

Useful OSMnx Patterns

# Get all buildings
buildings = ox.features_from_point(point, tags={'building': True}, dist=dist)

# Get specific amenities
cafes = ox.features_from_point(point, tags={'amenity': 'cafe'}, dist=dist)

# Different network types
G = ox.graph_from_point(point, dist=dist, network_type='drive')  # roads only
G = ox.graph_from_point(point, dist=dist, network_type='bike')   # bike paths
G = ox.graph_from_point(point, dist=dist, network_type='walk')   # pedestrian

Performance Tips

• Large dist values (>20km) = slow downloads + memory heavy
• Cache coordinates locally to avoid Nominatim rate limits
• Use network_type='drive' instead of 'all' for faster renders
• Reduce dpi from 300 to 150 for quick previews