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0.4.2

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adaptive-terrain-diffusion

Fast difficulty-conditioned terrain generation with ONNX Runtime

consistencygenerationmodelsroboticssimulationterrain
Published12 Aug 2026
Direct dependencies7
Transitive dependenciesNot calculated

README

Version 0.4.2 documentation

Terrain Diffusion

Fast, difficulty-conditioned terrain generation with an endpoint-distilled one-step model and ONNX Runtime.

The teaser above shows all 100 difficulties across six simulator renderers.

Install

pip install adaptive-terrain-diffusion
pip install "adaptive-terrain-diffusion[render,images]"  # optional rendering and TIFF support

Python

from terrain_diffusion import TerrainGenerator, render_terrains, save_terrains

generator = TerrainGenerator()  # automatically selects CUDA when available

terrains, difficulties = generator.generate(
    4,
    shape=(256, 384),
    difficulty="random",       # or any integer from 1 to 100
    seed=7,
    return_difficulties=True,
)

variations = generator.generate_from(
    terrains[0], difficulty=75, strength=0.5, variants=4
)

save_terrains("terrains", terrains, suffix=".npy")
render_terrains(terrains, save_path="terrains.png")

generate_from also accepts batches and .txt, .csv, .npy, .npz, or TIFF files. Larger-than-native maps use overlapping, blended generation automatically.

CLI

terrain-diffusion generate --output terrains --num 4 --difficulty 60 --shape 256 384 --render
terrain-diffusion vary terrain.npy --output variants --difficulty 75 --variants 4
terrain-diffusion simulate mujoco --difficulty 100 --shape 1024 1024

Simulators

SimulatorTerrain.apply() supports IsaacLab, MuJoCo, MuJoCo Playground, MuJoCo Warp, PyBullet, and Gazebo without adding simulator packages as dependencies.

from terrain_diffusion import SimulatorTerrain

asset = SimulatorTerrain(terrains[0], horizontal_scale=0.1)
asset.apply("pybullet", client_id)

See the simulator tutorial for complete integrations.

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Declared dependencies 7

Native requirements
7 direct targetsNot calculated transitive count
Package / targetRequirementRelationship
numpy
Environment
{
  "extras": "",
  "marker": null,
  "requires_python": ">=3.10",
  "evaluation": "NOT_EVALUATED"
}
numpy>=1.23runtime
onnxruntime-gpu
Environment
{
  "extras": "",
  "marker": "sys_platform == \"linux\" and platform_machine == \"x86_64\"",
  "requires_python": ">=3.10",
  "evaluation": "NOT_EVALUATED"
}
onnxruntime-gpu>=1.18; sys_platform == "linux" and platform_machine == "x86_64"runtime
onnxruntime
Environment
{
  "extras": "",
  "marker": "sys_platform != \"linux\" or platform_machine != \"x86_64\"",
  "requires_python": ">=3.10",
  "evaluation": "NOT_EVALUATED"
}
onnxruntime>=1.18; sys_platform != "linux" or platform_machine != "x86_64"runtime
matplotlib
Environment
{
  "extras": "",
  "marker": "extra == \"render\"",
  "requires_python": ">=3.10",
  "evaluation": "NOT_EVALUATED"
}
matplotlib>=3.7; extra == "render"runtime
Pillow
Environment
{
  "extras": "",
  "marker": "extra == \"images\"",
  "requires_python": ">=3.10",
  "evaluation": "NOT_EVALUATED"
}
Pillow>=9.0; extra == "images"runtime
build
Environment
{
  "extras": "",
  "marker": "extra == \"dev\"",
  "requires_python": ">=3.10",
  "evaluation": "NOT_EVALUATED"
}
build>=1.0; extra == "dev"runtime
twine
Environment
{
  "extras": "",
  "marker": "extra == \"dev\"",
  "requires_python": ">=3.10",
  "evaluation": "NOT_EVALUATED"
}
twine>=5.0; extra == "dev"runtime

Distribution files

2 collected
adaptive_terrain_diffusion-0.4.2-py3-none-any.whl

bdist_wheel · 38,016.21 KB · Python py3

Source file
adaptive_terrain_diffusion-0.4.2.tar.gz

sdist · 38,009.27 KB · Python source

Source file

Repository

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youwyu/adaptive-diffusion-terrain

Shared repository data · GitHub

License detected in repository
MIT
License branch / ref
main
Last push
8 Oct 2026
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420
2026-10-23: 4 · observed 2026-10-23T13:11:20.2281456Z
23 Oct23 Oct

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package_version:071df35b6823d90bc7cf490e4473ad97dfbcfc67644d5b02a0186ce056c504ea

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