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Cartographic ControlNet

This repository contains ControlNet models for generating accurate maps in controlled styles, as discussed in our paper: Generative AI in Map-Making: A Technical Exploration and Its Implications for Cartographers.

Sourcehuggingface.co/claudaff/Cartographic-ControlNet/tree/3b1bf4800675af7ad87da62b4bae8a2f7662f24f
TypeOtherModèle de baselllyasviel/ControlNetVersionCombinedCClasse

Source du modèle

Type
Other
Taille du fichier
8,01–11,8 GB
Modèle de base
lllyasviel/ControlNet
Version
vCombined
Mis à jour
7 oct. 2026
Source
Hugging Face

Description de la source

Generative AI in Map-Making: A Technical Exploration and Its Implications for Cartographers

This repository contains ControlNet models for generating accurate maps in controlled styles, as discussed in our paper: Generative AI in Map-Making: A Technical Exploration and Its Implications for Cartographers.

Traditional map-making often relies heavily on Geographic Information Systems (GIS), requiring domain expertise and being time-consuming. This work leverages recent advances in generative AI, specifically image diffusion models like ControlNet, to integrate vector data and guide map generation in various styles specified by textual prompts. This approach aims to automate and democratize the map-making process, enabling the creation of accurate maps with controlled spatial composition and semantic layout.

For more details, code, and further instructions, please visit the corresponding GitHub repository.

Models

Our four ControlNet models can be downloaded here.

  1. Swisstopo.ckpt: Specialized model for Swisstopo style
  2. OldNational.ckpt: Specialized model for Old National style
  3. Siegfried.ckpt: Specialized model for Siegfried style
  4. Combined.ckpt: Combined model, capable of generating map tiles in all three styles and used in our web app.
Class labelRGB color codeSwisstopoOld NationalSiegfried
Background(255, 255, 255)✓✓✓
Building(82, 82, 82)✓✓✓
Coordinate grid(237, 240, 64)✓✓✓
Railway (single track)(219, 30, 42)✓✓✓
Railway (multi track)(144, 20, 28)✓✓✓
Railway bridge(226, 132, 115)✓
Highway(247, 128, 30)✓✓
Highway gallery(231, 119, 28)✓✓✓
Road(149, 74, 162)✓✓✓
Through road(255, 103, 227)✓
Connecting road(128, 135, 37)✓
Path(0, 0, 0)✓✓✓
Depth contour(63, 96, 132)✓✓
River(41, 163, 215)✓✓✓
Lake(55, 126, 184)✓✓✓
Stream(89, 180, 208)✓✓✓
Tree(63, 131, 55)✓
Contour line(164, 113, 88)✓✓
Forest(77, 175, 74)✓✓✓

Sources

1 source
Hugging FacePrincipalVersion 3b1bf4800675af7ad87da62b4bae8a2f7662f24f
huggingface.co/claudaff/Cartographic-ControlNet/tree/3b1bf4800675af7ad87da62b4bae8a2f7662f24f

Vérifié 7 oct.

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Artefacts du modèle

4 artefacts

Combined.ckpt

ckpt · 11,8 GB · SHA-256 580d23792d9a…5c0b · Hugging Face

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OldNational.ckpt

ckpt · 11,8 GB · SHA-256 2dcc27c27e3e…bde2 · Hugging Face

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Siegfried.ckpt

ckpt · 8,01 GB · SHA-256 a6c9b06ca701…061c · Hugging Face

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Swisstopo.ckpt

ckpt · 11,8 GB · SHA-256 3bff651b1379…8532 · Hugging Face

Download file

Extraits de sources

2 extraits
Readme30 juil.huggingface.co/claudaff/Cartographic-ControlNet

--- base_model: - lllyasviel/ControlNet license: unknown pipeline_tag: image-to-image --- # Generative AI in Map-Making: A Technical Exploration and Its Implications for Cartographers This repository contains ControlNet models for generating accurate maps in controlled styles, as discussed in our paper: [Generative AI in Map-Making: A Technical Exploration and Its Implications for Cartographers](https://huggingface.co/papers/2508.18959). Traditional map-making often relies heavily on Geographic Information Systems (GIS), requiring domain expertise and being time-consuming. This work leverages recent advances in generative AI, specifically image diffusion models like ControlNet, to integrate vector data and guide map generation in various styles specified by textual prompts. This approach aims to automate and democratize the map-making process, enabling the creation of accurate maps with controlled spatial composition and semantic layout. For more details, code, and further instructions, please visit the corresponding [GitHub repository](https://github.com/claudaff/generative-ai-mapmaking). --- ## Models Our four ControlNet models can be downloaded [here](https://huggingface.co/claudaff/Cartographic-ControlNet/tree/main). 1. `Swisstopo.ckpt`: Specialized model for *Swisstopo style* 2. `OldNational.ckpt`: Specialized model for *Old National style* 3. `Siegfried.ckpt`: Specialized model for *Siegfried style* 4. `Combined.ckpt`: Combined model, capable of generating map tiles in all three styles and used in our web app. | Class label | RGB color code | Swisstopo | Old National | Siegfried | | :------------------ | :-------------- | :-------- | :----------- | :-------- | | Background | (255, 255, 255) | ✓ | ✓ | ✓ | | Building | (82, 82, 82) | ✓ | ✓ | ✓ | | Coordinate grid | (237, 240, 64) | ✓ | ✓ | ✓ | | Railway (single track)| (219, 30, 42) | ✓ | ✓ | ✓ | | Railway (multi track)| (144, 20, 28) | ✓ | ✓ | ✓ | | Railway bridge | (226, 132, 115) | ✓ | | | | Highway | (247, 128, 30) | ✓ | ✓ | | | Highway gallery | (231, 119, 28) | ✓ | ✓ | ✓ | | Road | (149, 74, 162) | ✓ | ✓ | ✓ | | Through road | (255, 103, 227) | ✓ | | | | Connecting road | (128, 135, 37) | ✓ | | | | Path | (0, 0, 0) | ✓ | ✓ | ✓ | | Depth contour | (63, 96, 132) | ✓ | ✓ | | | River | (41, 163, 215) | ✓ | ✓ | ✓ | | Lake | (55, 126, 184) | ✓ | ✓ | ✓ | | Stream | (89, 180, 208) | ✓ | ✓ | ✓ |...

Note30 juil.huggingface.co/claudaff/Cartographic-ControlNet

Source context: 0 downloads · 1 likes · Pipeline image-to-image · Repo claudaff/Cartographic-ControlNet