PATINA Material Extract turns any photograph or reference image into a complete seamlessly tiling PBR material set (basecolor, normal, roughness, metalness, height), guided by a text prompt. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
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$1.02每次運行

The wallpaper.

The wall.
Patina Material Extract extracts a seamlessly tiling PBR material from any reference image. Upload a photo of a real-world surface, describe which texture to extract, and the model produces a complete tileable material map set — isolating the target surface from complex scenes and converting it into production-ready PBR maps.
Surface extraction from complex scenes Isolate and extract a specific material from photos that contain multiple surfaces, objects, or backgrounds — guided by your text description.
Seamlessly tiling output Produces tileable material maps ready for use on any geometry without visible seams.
Tiling direction control Choose omnidirectional tiling (both), horizontal-only, or vertical-only to match your UV mapping needs.
Custom output size Specify any output resolution to match your target quality and performance requirements.
Production-ready PBR maps Output is formatted for direct use in game engines (Unreal, Unity), 3D tools (Blender, Maya), and real-time rendering pipelines.
| Parameter | Required | Description |
|---|---|---|
| image | Yes | Reference image URL to extract a tiling material from. |
| prompt | Yes | Text description guiding which texture to extract (e.g. "the stone wall surface", "the wood grain pattern"). |
| size | No | Output dimensions in width×height pixels. Default: 1024×1024. |
| tiling_mode | No | Seamless tiling direction: both (default), horizontal, or vertical. |
Just $1.02 per run (6 images).
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/patina/material-extract with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read URLs from data.outputs. Examples for Patina Material Extract below.
# Submit the prediction
curl --fail-with-body --connect-timeout 10 --max-time 60 \
-X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/patina/material-extract" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $WAVESPEED_API_KEY" \
-d '{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"image": "https://example.com/your-input.jpg",
"size": "1024*1024",
"tiling_mode": "both"
}'
# Wait at least 2 seconds, then poll. Safe GET requests may be retried.
curl --fail-with-body --connect-timeout 10 --max-time 30 \
--retry 4 --retry-all-errors --retry-delay 1 \
-X GET "https://api.wavespeed.ai/api/v3/predictions/{request_id}/result" \
-H "Authorization: Bearer $WAVESPEED_API_KEY"
# Start at 2 seconds and increase the interval for long-running tasks.
# Stop on completed, failed, cancelled, or timeout.// npm install wavespeed
const { Client } = require('wavespeed');
const apiKey = process.env.WAVESPEED_API_KEY;
if (!apiKey) throw new Error('Set WAVESPEED_API_KEY');
const client = new Client(apiKey);
try {
const result = await client.run("wavespeed-ai/patina/material-extract", {
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"image": "https://example.com/your-input.jpg",
"size": "1024*1024",
"tiling_mode": "both"
}, {
timeout: 3600,
pollInterval: 2.0,
});
console.log(result.outputs);
} catch (error) {
console.error('Generation failed:', error);
process.exitCode = 1;
}# pip install wavespeed
import os
from wavespeed import Client
client = Client(api_key=os.environ["WAVESPEED_API_KEY"])
try:
output = client.run(
"wavespeed-ai/patina/material-extract",
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"image": "https://example.com/your-input.jpg",
"size": "1024*1024",
"tiling_mode": "both"
},
timeout=3600.0,
poll_interval=2.0,
)
print(output["outputs"])
except Exception as error:
raise SystemExit(f"Generation failed: {error}") from errorPatina Material Extract is a WaveSpeedAI model for image editing, exposed as a REST API on WaveSpeedAI. PATINA Material Extract turns any photograph or reference image into a complete seamlessly tiling PBR material set (basecolor, normal, roughness, metalness, height), guided by a text prompt. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.
POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID. Poll the result endpoint starting around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. The playground generates production-oriented Python, JavaScript, and cURL examples with timeouts, transient-error handling, and safe GET retries. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/wavespeed-ai/patina-material-extract.
Patina Material Extract starts at $1.02 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.
Key inputs: `prompt`, `image`, `size`, `tiling_mode`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/wavespeed-ai/patina-material-extract.
Sign up for a free WaveSpeedAI account to claim starter credits, copy your API key from /accesskey, then call the endpoint shown in the API tab of the playground. The playground also auto-generates a code sample in Python, JavaScript, or cURL for the parameters you've set.
Commercial usage rights depend on the model's license, set by its provider (WaveSpeedAI). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.