Patina Image To Map

Patina Image To Map

Playground

PATINA generates seamless high-resolution PBR material maps (basecolor, normal, roughness, metalness, height) from a single image, ready for use in Unreal, Unity, Blender, and other 3D pipelines. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Patina Image-to-Map

Patina Image-to-Map generates a complete set of PBR (Physically Based Rendering) material maps from a single input image. Upload any photograph or render — the model produces all 5 map types in one run, ready for use in game engines, 3D tools, and real-time rendering pipelines.

Why Choose This?

• Complete PBR map generation Generates all 5 material maps from a single image in one run — no manual authoring or separate processing steps required.

• Works on any surface image Compatible with photographs of real-world materials, textures, and renders for versatile workflow integration.

• Production-ready output Maps are formatted for direct use in game engines (Unreal, Unity), 3D tools (Blender, Maya), and real-time rendering pipelines.

• Simple single-input workflow Just one image in, five maps out. No configuration required.

Parameters

How to Use

1. Upload your image — provide a photograph or render of the surface material via URL.
2. Submit — the model generates all 5 PBR material maps in a single run.
3. Download your complete map set ready for use in your 3D pipeline.

Pricing

Just $0.06 per run (5 maps).

Best Use Cases

• Game development — Generate complete PBR material sets from photo references for real-time game assets.
• 3D environment art — Rapidly produce material maps for architectural visualization and scene building.
• Texture authoring — Accelerate material creation workflows by generating map sets from existing photography.
• Asset digitization — Convert photographs of real-world surfaces into production-ready PBR materials.
• Indie & rapid prototyping — Quickly populate 3D scenes with physically accurate materials without manual map authoring.

Pro Tips

• Use well-lit, evenly illuminated surface photos for the most accurate albedo and normal map extraction.
• Avoid images with strong directional shadows — diffuse, neutral lighting produces the cleanest maps.
• Crop your input image to focus on the material surface and minimize irrelevant background areas.
• High-resolution input images produce more detailed and accurate map outputs.

Notes

• image is the only required field.
• Each run generates 5 PBR map types as output.
• Ensure image URLs are publicly accessible if using a link rather than a direct upload.
• Please ensure your content complies with WaveSpeed AI’s usage policies.

# Submit the task
curl --location --request POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/patina/image-to-map" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{}'

# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"