PATINA · Material
集成
模型 id
patina/material
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.com/v1/run/patina/material?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}'
# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.com/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/patina/material?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/patina/material", params={"wait": 20}, json=payload, headers=headers)
request = r.json()
if not r.ok:
raise RuntimeError(request["error"]["code"] + ": " + request["error"]["message"])
# Not finished yet: long-poll until it is
while request["status"] in ("queued", "running"):
request = requests.get(API + "/requests/" + request["id"], params={"wait": 20}, headers=headers).json()
if request["status"] != "succeeded":
raise RuntimeError(request["error"])
print([o["url"] for o in request["outputs"]], request["cost"]["credits"], "API credits", "$" + request["cost"]["usd"])
# 1. Connect once (Claude Code; Cursor, VS Code, Claude Desktop: https://doitong.com/zh/developers/docs/mcp)
claude mcp add --transport http doitong-models https://api.doitong.com/v1/mcp \
--header "Authorization: Bearer $DOITONG_API_KEY"
# 2. Your agent calls the "run" tool with:
{
"model_id": "patina/material",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
}
通过 Doitong API 调用 PATINA · Material 模型(patina/material)。智能体文档:https://doitong.com/zh/developers/models/patina/material.md
POST https://api.doitong.com/v1/run/patina/material?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json
{
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
如果响应状态为 "queued" 或 "running",请轮询 GET https://api.doitong.com/v1/requests/REQUEST_ID?wait=20,直到状态变为 "succeeded";文件位于 outputs[].url。使用相同请求体 POST https://api.doitong.com/v1/quote/patina/material,可在运行前返回确切价格。
与示例类似的文件: $0.08 80 API 积分 运行前会测量你的文件 在此页面运行
你的新 API 密钥。 它仅在此时显示,并且已填入下方的代码和 API 密钥字段中。请妥善保密:切勿将其放入在浏览器中运行的代码。
构建请求
控件根据模型架构生成。更改控件时,代码和价格会同步更新。
POST
/run/patina/material?wait=20
报价 → $0.08
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.com/v1/run/patina/material?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}'
# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.com/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/patina/material?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/patina/material", params={"wait": 20}, json=payload, headers=headers)
request = r.json()
if not r.ok:
raise RuntimeError(request["error"]["code"] + ": " + request["error"]["message"])
# Not finished yet: long-poll until it is
while request["status"] in ("queued", "running"):
request = requests.get(API + "/requests/" + request["id"], params={"wait": 20}, headers=headers).json()
if request["status"] != "succeeded":
raise RuntimeError(request["error"])
print([o["url"] for o in request["outputs"]], request["cost"]["credits"], "API credits", "$" + request["cost"]["usd"])
{
"jsonrpc": "2.0",
"id": 1,
"method": "tools/call",
"params": {
"name": "run",
"arguments": {
"model_id": "patina/material",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
},
"wait_seconds": 20
}
}
}
关于 PATINA · Material
根据提示词创建可平铺纹理,并预测 PBR 贴图:basecolor、normal、roughness、metalness 和 height。使用 `tiling_mode` 设置双向、水平或垂直平铺,并使用 0、2 或 4 的 `upscale_factor` 放大贴图。传入 `image_url` 可启用图生图,添加 `mask_url` 可启用局部重绘。每次请求最多 4 张图像。
参数
发送规范名称或原生名称之一,不要同时发送两者。 规范名称
名称类型
默认值允许值
描述
prompt必填
类型string
要创建的材质或纹理的文本描述。
image_size可选
类型object
默认值square_hd
square_hdsquareportrait_4_3portrait_16_9landscape_4_3landscape_16_9
生成纹理的像素尺寸。
num_inference_steps可选
类型integer
默认值8
1 – 8
用于生成纹理的去噪步数。
seed可选
类型integer | null
使生成结果可复现的随机种子。
num_images可选
num_outputs
类型integer
默认值1
1 – 4
要创建的纹理图像数量。
enable_prompt_expansion可选
类型boolean
默认值true
启用基于 LLM 的提示词扩展以添加细节。
enable_safety_checker可选
类型boolean
默认值true
启用生成图像的安全检查。
tiling_mode可选
类型enum
默认值both
bothhorizontalvertical
平铺方向:'both' 表示全方向平铺,或选择 'horizontal'、'vertical'。
tile_size可选
类型integer
默认值128
32 – 256
潜空间平铺尺寸,其中 64 表示 512px,128 表示 1024px。在每个平铺轴上,生成图像的尺寸会设置自动上限。
tile_stride可选
类型integer
默认值64
16 – 128
设置潜空间平铺之间的步幅;自动上限会防止其超过有效平铺尺寸的一半。
image_url可选
image
类型url · image
源图像 URL;如果同时提供 mask_url,则用于图像修复,否则用于图像到图像处理。
mask_url可选
mask
类型url · image
与必需的 image_url 一起提供的图像修复遮罩 URL。遮罩会保留黑色区域不变,并重新生成白色区域。
strength可选
类型number
默认值0.6
≤ 1> 0
仅应用于通过 image_url 提供的图像的变换强度;其他情况下不使用。
maps可选
类型enum[]
默认值["basecolor","normal","roughness","metalness","height"]
用于预测的 PBR 贴图,默认选择全部五种。不选择任何贴图则完全跳过 PBR 估计。
upscale_factor可选
类型enum
默认值0
024
SeedVR 无缝放大倍数,影响预测的 PBR 贴图,但保持基础纹理的原始分辨率。选择 2 可将分辨率加倍,选择 4 可变为四倍,选择 0 可禁用放大。
output_format可选
类型enum
默认值png
jpegpngwebp
输出纹理和 PBR 贴图的图像文件格式。
必填
规范名称,也可接受
文件参数接受公开的 https:// URL、最大 10 MB 的 data: URI,或上传文件的 file_url。 文件
输出
GET /requests/req_8k2m4q7x1z9c3v5b6n0p2r4t
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "patina/material",
"status": "succeeded",
"created_at": "2026-10-20T12:00:00Z",
"started_at": "2026-10-20T12:00:02Z",
"completed_at": "2026-10-20T12:00:09Z",
"queue_position": null,
"cost": {
"credits": 80,
"usd": "0.08",
"charged": 80,
"refunded": 0
},
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
},
"output": {
"images": [
{
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
"content_type": "image/jpeg",
"file_name": "0-output.jpeg",
"file_size": 1843200,
"width": 1024,
"height": 768
}
],
"seed": 42,
"prompt": "string",
"timings": {}
},
"outputs": [
{
"type": "image",
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
"content_type": "image/jpeg",
"file_size": 1843200,
"width": 1024,
"height": 768,
"stored": true
}
],
"error": null,
"metrics": {
"inference_seconds": 6.8
},
"urls": {
"self": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
"cancel": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
}
}
你的文件,由你选择每个 outputs[].url 都是存储中的副本:可永久保存(按 GB-月付费),也可免费保存 7 天,由账户设置或 ?storage= 决定。
每个模型的结构相同图像、视频和音频均包含 type、url、content_type、width、height 和 duration。output 是模型自身的结果对象。
输出字段
- images
- array of any输出图像包含 PATINA 预测的 PBR 材质贴图,以及 z-image 生成的可平铺纹理。
- seed
- integer生成纹理时使用的种子。
- prompt
- string纹理生成提示词,包括应用的任何扩展内容。
- timings
- object覆盖完整处理过程的计时明细,单位为秒。
其他 Patina 变体
更多模型:文生图
对于 AI 代理:此页面的 Markdown 版本位于 https://doitong.com/zh/developers/models/patina/material.md. 所有模型和指南: https://doitong.com/developers/llms.txt







