fal-ai/patina/material

PATINA Material - Text to PBR Material

Endpoint: fal-ai/patina/material

Category: Text-to-image (also supports image-to-image)

Pricing: $0.01 base + $0.02 per megapixel + $0.01 per megapixel per map. Upscaling adds $0.004 (2x) or $0.016 (4x) per megapixel per map.

Generate complete, seamlessly tiling PBR materials from text prompts - up to 8K resolution with built-in upscaling. Also supports image-to-image for creating variations of existing textures.

When to use this

Use this endpoint to generate new PBR materials from scratch using a text description, or to create variations of an existing texture via image-to-image.

Good for:

• Creating new materials from a text prompt ("weathered copper patina", "rough hewn limestone")
• Generating seamlessly tiling textures at up to 2048px (8K with upscaling)
• Creating variations on an existing texture using image_url (pure image-to-image, not an edit)
• Inpainting regions of a texture using image_url + mask_image_url

Use a different endpoint if:

• You already have a finished texture and just want PBR maps from it - use /patina
• You have a photo of a scene and want to extract a specific material from it - use /patina/material/extract

Quick start

Text to material

javascript
import { fal } from "@fal-ai/client";

const result = await fal.subscribe("fal-ai/patina/material", {
  input: {
    prompt: "weathered copper patina with verdigris"
  }
});

// result.data.images - generated texture + PBR maps

Image-to-image (create variations)

javascript
const result = await fal.subscribe("fal-ai/patina/material", {
  input: {
    prompt: "mossy stone wall",
    image_url: "https://example.com/stone-texture.jpg",
    strength: 0.75
  }
});

Input

Example request (text only)

json
{
  "prompt": "mossy stone wall",
  "image_size": "square_hd",
  "maps": ["basecolor", "normal", "roughness", "metalness", "height"]
}

Example request (image-to-image)

json
{
  "prompt": "mossy stone wall",
  "image_url": "https://example.com/stone-texture.jpg",
  "strength": 0.75,
  "maps": ["basecolor", "normal", "roughness", "metalness", "height"]
}

Output

Example response

json
{
  "images": [
    { "url": "https://fal.media/files/..." },
    { "url": "https://fal.media/files/...", "map_type": "basecolor" },
    { "url": "https://fal.media/files/...", "map_type": "height" },
    { "url": "https://fal.media/files/...", "map_type": "normal" },
    { "url": "https://fal.media/files/...", "map_type": "roughness" },
    { "url": "https://fal.media/files/...", "map_type": "metalness" }
  ],
  "seed": 42,
  "prompt": "mossy stone wall"
}

The first image (without map_type) is the generated texture itself. The rest are the PBR maps.

Output maps explained

Code examples

JavaScript

javascript
import { fal } from "@fal-ai/client";

const result = await fal.subscribe("fal-ai/patina/material", {
  input: {
    prompt: "mossy stone wall"
  },
  logs: true,
  onQueueUpdate: (update) => {
    if (update.status === "IN_PROGRESS") {
      update.logs.map((log) => log.message).forEach(console.log);
    }
  },
});
console.log(result.data);

Python

python
import fal_client

result = fal_client.subscribe(
    "fal-ai/patina/material",
    arguments={
        "prompt": "mossy stone wall"
    },
    with_logs=True,
)
print(result)

cURL

bash
curl -X POST https://fal.run/fal-ai/patina/material \
  -H "Authorization: Key $FAL_KEY" \
  -H "Content-Type: application/json" \
  -d '{"prompt": "mossy stone wall"}'